The association between the triglyceride-glucose-a body shape index (TyG-ABSI) and depressive symptoms in US adults: A population-based cross-sectional study.

This study aimed to explore the relationship between A Body Shape Index (ABSI) and depressive symptoms, and to evaluate the moderating effects of sociodemographic, lifestyle, and health factors. We analyzed data from 19,659 participants in the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). ABSI was calculated from waist circumference, height, and BMI. Multiple linear regression models were employed to investigate the association between ABSI and depressive symptoms, with subgroup analyses to examine potential associations within specific populations. Higher ABSI was significantly associated with increased depressive symptoms, after adjusting for covariates including age, sex, race, marital status, poverty-income ratio, smoking, alcohol consumption, physical activity, diabetes, and hypertension. Individuals in the highest ABSI quartile (Q4) had significantly more depressive symptoms compared to those in the lowest quartile (Q1) (β = 0.22, 95% CI = 0.02-0.41, p = 0.0323). Subgroup analyses revealed that marital status and hypertension significantly moderated the association between ABSI and depressive symptoms. This study provides the first comprehensive analysis of the link between ABSI and depressive symptoms, suggesting that higher ABSI is associated with greater depressive symptoms. These findings highlight the potential importance of waist circumference and abdominal fat distribution in assessing depression risk. Future research should explore the causal mechanisms underlying this association and investigate the biological pathways involved, to inform more effective strategies for depression prevention and intervention.

Stress urinary incontinence (SUI) is common among women, but its link with A Body Shape Index (ABSI) is not well understood. This study investigates the association between ABSI and SUI risk in women, exploring variations across different subgroups. Data from National Health and Nutrition Examination Survey (2001-2020) were analyzed. A weighted multivariable logistic regression was performed to examine the relationship between ABSI and SUI risk, calculating odds ratios and 95% confidence intervals. A restricted cubic spline (RCS) analysis was used to assess any nonlinear associations. Subgroup analyses and interaction tests were conducted to explore the influence of factors on the ABSI-SUI relationship. Sensitivity analyses were also performed to ensure the robustness of the findings. The analysis, after adjusting for potential confounders, showed a significant association between ABSI and SUI risk (p < 0.001). The RCS analysis indicated a nonlinear relationship (p for nonlinear = 0.02) with a turning point at an ABSI of 0.081. Subgroup analyses revealed that the association between ABSI and SUI was stronger in women with lower BMI, non-Mexican ethnicity, and those without hypertension (p for interaction < 0.05). Sensitivity analyses confirmed the consistency of these findings, supporting their robustness. Higher ABSI is associated with an increased risk of SUI in US women, particularly in specific subgroups. This suggests that ABSI could be a valuable measure for identifying women at higher risk of SUI.

BackgroundOverweight and obese females demonstrate a significantly increased risk of anovulatory infertility. This study aims to investigate whether depression score could mediate the association between a body shape index (ABSI) and infertility, especially in overweight and obese population.MethodsWe included 5431 adult female Americans from the National Health and Nutrition Examination Survey (NHANES, 2013–2018) database. ABSI manifested the body shape using waist circumference, weight, and height. Infertility or fertility status was defined by interviewing female participants aged ≥ 18 through the reproductive health questionnaires. Depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) with total scores between 0 and 27. To investigate the association of infertility with ABSI and other individual components, survey-weighted multivariable logistic regression was performed. Mediation analysis of PHQ-9 score was conducted to disentangle the pathways that link ABSI to infertility among the NHANES participants.Results596 (10.97%) females were categorized with having infertility among 5431 participants. Participants with infertility showed higher ABSI and PHQ-9 score, appearing greater population proportion with depression symptoms. In the multivariable logistic regression model, ABSI (adjusted odds ratio = 0.14, 95% CI: 0.04 to 0.50) and PHQ-9 (adjusted odds ratio = 1.04, 95% CI: 1.01 to 1.07) were positively associated with infertility. PHQ-9 score was estimated to mediate 0.2% (P = 0.03) of the link between ABSI and infertility in all individuals, but to mediate 13.5% (P < 0.01) of the ABSI-infertility association in overweight and obese adult females.ConclusionThe association between ABSI and infertility seems to be mediated by depression symptoms scored by PHQ-9, especially in those adult females with overweigh and obesity. Future studies should be implemented to further explore this mediator in ABSI-infertility link.

Obesity, a prevalent global health issue, is associated with testosterone deficiency (TD). A body shape index (ABSI) provides a more precise assessment of obesity and visceral fat, but its relationship with testosterone remains unclear. This study aimed to explore the association between ABSI and testosterone levels leading to TD. Data from 5256 adult males participating in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016 were collected to analyze of the association between ABSI and TD. The data underwent analysis using multivariate linear regression, logistic regression, restricted cubic spline (RCS) analysis, subgroup analysis, and interaction testing. The predictive ability of ABSI based on weight, height, and waist circumference, as well as body mass index (BMI) based on weight and height, alongside a multiplicative combination of both metrics, BMI × ABSI, and optimal proportional combination OBMI + ABSI for assessing TD risk, was valuated using receiver operating characteristic (ROC) curves. Following adjustment for all confounding factors, ABSI exhibited a negative linear correlation with testosterone (β = -6.99, 95% confidence interval (CI): -8.25 to -5.73; p < 0.001) and a positive association with TD risk (odds ratio (OR) = 1.06, 95% CI: 1.04-1.08; p < 0.001). Notably, these associations remained consistent in the subgroup analysis. Additionally, age and hypertension demonstrated significant interactions between ABSI and TD (p < 0.05). Moreover, combining metrics, such as BMI × ABSI and OBMI + ABSI, proved to be more reliable predictors of TD compared to BMI or ABSI alone. This study identified a negative linear correlation between ABSI and total testosterone levels in adult American males, as well as a positive linear correlation with TD prevalence. ABSI represents a valuable addition to BMI for assessing obesity and the association between obesity and TD.

BackgroundThis study aimed to investigate the association between A Body Shape Index (ABSI) and low back pain, with a focus on gender and age differences, using cross-sectional data from the NHANES database.MethodsA total of 14,268 participants were included from four NHANES cycles (1999–2004 and 2009–2010). Low back pain was assessed based on self-reported pain over the past three months, and ABSI was calculated using waist circumference, height, and weight. Multivariate logistic regression models were used to evaluate the association between ABSI and low back pain, adjusting for potential confounders. Restricted cubic spline (RCS) analysis was conducted to assess non-linear relationships, and subgroup analyses were performed based on gender, age and BMI.ResultsHigher ABSI was significantly associated with an increased risk of low back pain (OR for highest quartile = 1.27, 95% CI: 1.07–1.50, p = 0.008). RCS analysis indicated a linear relationship between ABSI and low back pain, with the risk significantly rising when ABSI exceeded 0.85. Subgroup analyses revealed that this association was more pronounced in males (OR = 25.89, 95% CI: 3.11-215.86, p = 0.004) and participants aged ≥ 60 years (OR = 11.11, 95% CI: 2.61–47.26, p = 0.002), while no significant association was observed in females.ConclusionsThe ABSI was associated with low back pain. This association was more prominent in males and older adults. Our findings suggest that ABSI may provide a more nuanced understanding of low back pain risk, particularly in populations with abdominal obesity. Further studies are needed to explore the underlying mechanisms and potential clinical applications of ABSI in low back pain risk assessment.

A Body Shape Index (ABSI) serves as a potential indicator of fat distribution, offering a more reliable association with all-cause mortality compared to overall adiposity. The present cohort study aims to explore the relationship between ABSI and all-cause mortality in US adults with Type 2 Diabetes (T2D). For this cohort study, we extracted information on 5,461 US adults with T2D from the National Health and Nutrition Examination Survey (NHANES) and the NHANES Linked Mortality File. Trends in ABSI from 1999 to 2018 were calculated and analyzed using partial Mann-Kendall tests. To assess the relationship between ABSI and all-cause mortality, as well as the robustness of the association results, we employed weighted restricted cubic splines (RCS), weighted Cox proportional hazards models, sensitivity analyses, and stratified analyses. Additionally, we conducted time-dependent receiver operating characteristic (ROC) curve analysis to evaluate ABSI's predictive capability for all-cause mortality over 3, 5, and 10years. Among US adults with Type 2 Diabetes (T2D), the mean ABSI gradually increased from 0.08333 to 0.08444 between 1999 and 2018. Following a median follow-up period of 90months, 1,355 deaths (24.8% of the participants) occurred due to all causes. A left J-shaped association was observed between ABSI and all-cause mortality, with a 39% increased risk among US adults with T2D who had an ABSI below 0.08105 after full adjustment. Our research has demonstrated a significant association between an elevated ABSI and the risk of all-cause mortality among US adults with T2D. These findings support the potential use of ABSI as a noninvasive tool to estimate mortality risk among US adults with T2D. The online version contains supplementary material available at 10.1007/s40200-025-01570-3.

BackgroundInsulin resistance, represented by increased triglyceride-glucose (TyG) index levels, shows interplay with visceral obesity and together promotes cardiovascular diseases and mortality. However, significant controversies exist regarding whether modified TyG indices, such as TyG-BMI, TyG-WC, and TyG-WHtR, outperform the TyG index in predicting cardiovascular outcomes. We aimed to explore whether there was a synergistic effect of a body shape index (ABSI), a better parameter reflecting visceral obesity, and the TyG index on cardiovascular mortality.MethodsWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) 2001–2018 of 17,329 individuals. The associations of the TyG index and ABSI with cardiovascular mortality were investigated via Cox regression analysis and restricted cubic splines. Receiver operating characteristic (ROC) curve analysis was performed to compare the predictive value. Mediation analysis was used to explore the potential mediator.ResultsA total of 673 (3.9%) cardiovascular deaths occurred during a median follow-up of 8.92 years. Individuals with high TyG and high ABSI (TyG > 9.04 and ABSI > 0.085) were at the highest cardiovascular mortality risk both in individuals with (HR = 1.714, 95% CI 1.123–2.616) and without diabetes (HR = 1.402, 95% CI 1.003–1.960), suggesting a synergistic effect. Next, we multiplied these two indicators and established TyG-ABSI. It showed a J-shaped relationship and a positive linear relationship with cardiovascular mortality in individuals with and without diabetes, respectively. Arterial stiffness, represented by estimated pulse wave velocity, partially mediated the effect of TyG-ABSI on cardiovascular mortality, with a mediation proportion of 42.7%. The predictive value of TyG-ABSI was greater than that of the TyG index, TyG-BMI, TyG-WC, and TyG-WHtR (Harrell’s C-index: 0.710 vs 0.623 vs 0.539 vs 0.612 vs 0.622, all p < 0.001).ConclusionsThe simultaneous assessment of the TyG index and ABSI revealed a synergistic effect on cardiovascular mortality. We recommended the use of TyG-ABSI instead of the TyG index and other modified TyG indices in cardiovascular risk assessment.

Uncertainty persists regarding the associations between a body shape index (ABSI) and diabetic kidney disease (DKD), albuminuria, and low estimated glomerular filtration rate (eGFR). Data from 2,770 participants in the 2005–2016 U.S. National Health and Nutrition Examination Survey (NHANES) were analyzed in this study. Multiple logistic regression models and subgroup analyses were utilized to evaluate the relationships between ABSI and DKD, albuminuria, and low eGFR. A restricted cubic spline (RCS) plot was applied to examine trends in these associations. In the fully adjusted model, each unit increase in ABSI was associated with a 33% higher risk of DKD (adjusted OR = 1.33, 95% CI: 1.09–1.61, p = 0.0043) and a 50% higher risk of albuminuria (adjusted OR = 1.50, 95% CI: 1.23–1.84, p < 0.0001). In contrast, no significant relationship was observed with low eGFR (adjusted OR = 1.13, 95% CI: 0.88–1.46, p = 0.3444). These relationships exhibited variation across age, sex, and comorbidity subgroups. Results based on standardized ABSI (z-score) were similar, confirming significant associations with DKD and albuminuria. RCS plots showed that ABSI was significantly and linearly associated with the risks of DKD (P-overall = 0.026, P-nonlinear = 0.577) and albuminuria (P-overall = 0.001, P-nonlinear = 0.658), indicating that the risk of DKD and albuminuria increased with higher ABSI levels. In contrast, no significant association was observed between ABSI and low eGFR (P-overall = 0.298, P-nonlinear = 0.238). Higher ABSI levels are associated with increased risks of DKD and albuminuria, particularly in specific subgroups.

Background Abdominal aortic calcification (AAC) is prevalent in chronic kidney disease (CKD) patients and linked to elevated cardiovascular disease (CVD) risk. Obesity, linked to both CKD and CVD, can be better assessed by A Body Shape Index (ABSI), a novel index measuring central obesity and fat distribution. We posit that ABSI may correlate with AAC risk in CKD patients. This research explores the association using 2013–2014 National Health and Nutrition Examination Survey (NHANES) data. Materials and methods From the 2013–2014 NHANES dataset, we excluded participants lacking data on AAC or ABSI A total of 961 CKD subjects remained. Before analyzing ABSI as a continuous variable, we standardized it, denoting the result as ABSIa. We then plotted restricted cubic splines (RCS). Follow-up univariate and multivariate regression, subgroup, and interaction analyses were conducted to explore the ABSIa-AAC relationship. Results The analysis revealed a significant positive relationship between ABSIa and AAC in CKD patients (OR = 1.41, 95% CI: 1.23–1.61, p < 0.001). Even after adjustment for multiple confounders, ABSIa remained independently associated with AAC (OR = 1.38, 95%CI: 1.17–1.64, p < 0.001). Subgroup analyses further validated this association across various patient subgroups. Conclusions In patients with CKD, this cross-sectional study identified a significant positive association between ABSI and AAC, persisting after adjusting for confounders. This suggests ABSI may be a biomarker for AAC risk assessment and CVD risk stratification in CKD patients.

Abdominal obesity is recognized as a key risk factor for developing OAB. However, traditional measures of obesity, such as the waist-to-height ratio (WHtR), waist circumference, and body mass index (BMI), may not sufficiently capture fat distribution in the body. This study aims to evaluate the relationship between novel anthropometric indices and OAB, providing a more accurate assessment of obesity-related risk factors. The National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2018 were utilized, comprising 27,560 participants. To assess the association and discriminative ability of novel anthropometric indices, including the Body Roundness Index (BRI), A Body Shape Index (ABSI), Waist-to-Weight Index (WWI), and Relative Fat Mass (RFM), with OAB, we employed multivariable logistic regression, restricted cubic spline (RCS) analysis, subgroup analysis, and receiver operating characteristic (ROC) curve methods. Multivariable logistic regression analysis indicated that higher levels of novel anthropometric indices were positively associated with OAB prevalence. One z-score increase in WWI, BRI, RFM, and ABSI was associated with a 16, 31, 57, and 5% higher likelihood of OAB, respectively. RCS analysis revealed a non-linear relationship between RFM and OAB. ROC analysis indicated that WWI (AUC = 0.680) and RFM (AUC = 0.661) provided better diagnostic accuracy than traditional measures such as BMI (AUC = 0.599). Subgroup analyses supported the robustness of these findings. Novel anthropometric indices were positively associated with OAB prevalence. WWI and RFM demonstrated significantly better diagnostic value for OAB than BMI and WHtR. Future studies should investigate the potential of combining multiple anthropometric indices to improve predictive accuracy and conduct prospective studies to determine causality.

ABSTRACTBackground and AimThis study investigated the correlation between obesity‐related indices and diabetic nephropathy (DN) in patients with type II diabetes mellitus (T2DM). It aimed to provide a new predictive assessment tool for the clinic and a scientific basis for managing DN.MethodsThe data utilised in this study were obtained from the National Health and Nutrition Examination Survey (NHANES) database, spanning 2007 to 2018. A total of 843 patients diagnosed with DN were included in the analysis. The association between obesity‐related indices and DN was investigated using multivariable logistic regression models. These relationships were further validated by restricted cubic spline (RCS) modelling.ResultsThe multivariable logistic regression analysis indicated that A Body Shape Index (ABSI), weight‐to‐waist index (WWI), body roundness index (BRI) and waist‐to‐height ratio (WHtR) levels were independently associated with DN. In particular, WWI, BRI, and WHtR levels were found to be independently associated factors with DN. Patients in the highest quartile of WWI, BRI, and WHtR exhibited a 1.19‐fold, 1.30 fold, and 1.30‐fold increased risk of DN, respectively, compared to patients in the lowest quartile. RCS analyses further confirmed the positive association between ABSI, WWI, BRI, and WHtR and DN. The ABSI offers incremental value in model predictive power for DN in patients with DM compared to other obesity‐related indices. As renal function deteriorates, BRI and WHtR show a significant negative correlation with estimated glomerular filtration rate (eGFR).ConclusionCompared with other obesity‐related indices, the ABSI offers incremental value in model predictive power for DN in patients with DM.

Background This study aimed to evaluate the association between A Body Shape Index (ABSI) and hyperlipidemia, and assess nonlinear relationships via restricted cubic spline (RCS) analysis. Methods Data from 21,013 adults in the National Health and Nutrition Examination Survey (NHANES, 2005–2020) were analyzed. Hyperlipidemia was defined using National Cholesterol Education Program (NCEP) criteria. ABSI was calculated as waist circumference/(BMI^(2/3) × H^(1/2)) and stratified into quartiles (Q1–Q4). Multivariable logistic regression models, adjusted for demographic characteristics, health behaviors, and clinical features, assessed the association between ABSI and hyperlipidemia. RCS and subgroup analyses explored nonlinearity and interactions, with sensitivity analyses excluding lipid-lowering medication users and participants who died within two years. Results Higher ABSI was significantly associated with increased hyperlipidemia risk across models. In the fully adjusted model, each ABSI unit increase correlated with a 24% higher risk (OR=1.24, 95% CI:1.17-1.31). Quartile analysis showed gradually elevated risk, with Q4 (highest) having 68% higher odds than Q1 (lowest; OR=1.68, 95% CI:1.46-1.94, P-trend<0.001). RCS revealed a significant nonlinear inverse U-shaped relationship (P for nonlinearity<0.001) with a threshold of 0.084; participants with ABSI>0.084 had a 28% higher risk (OR=1.28, 95% CI:1.13-1.44) versus ABSI≤0.084. Subgroup analyses identified significant interactions with age (P<0.001), marital status (P=0.028), hypertension (P=0.005), and diabetes (P=0.001). Sensitivity analyses confirmed result robustness. Conclusion This study provides the first comprehensive evidence of a significant ABSI-hyperlipidemia association. The threshold effect suggests ABSI may serve as a valuable anthropometric tool for hyperlipidemia risk stratification. Future studies should validate causality and explore mechanisms underlying the observed nonlinear dynamics.

A body shape index (ABSI) is an abdominal obesity index developed based on epidemiological statistics and high ABSI indicates that waist circumference (WC) is higher than expected for a given height and weight and corresponds to a more central concentration of body volume. The objective of this study was to determine whether there is a linear or nonlinear relationship between ABSI and total femur bone mineral density (BMD) in older Americans and whether the relationship between the ABSI and total femur BMD varies across populations. This cross-sectional study was based on data from the 2007-2018 National Health and Nutrition Examination Survey (NHANES). Weighted multiple linear regression, restricted cubic spline (RCS) curves, subgroup analysis, and interaction tests were used to examine the association between ABSI and total femur BMD. This study included 2505 older adults. This study found a negative linear correlation between ABSI and total femur BMD (β = -3.2, 95%CI: -5.0, -1.4, p < 0.001). When participants were grouped according to quartiles of ABSI, those in the upper quartile had lower total femur BMD compared to those in the bottom quartile of ABSI. This negative association remained consistent across gender, age, education level, smoking, physical activity and BMI subgroups. However, in the diabetes subgroup, ABSI showed a stronger negative association with total femur BMD. The study shows a negative linear association between ABSI and total femur BMD in older Americans, with this negative association being stronger in the diabetic population.

ObjectiveThis study explored how the weight-adjusted waist index (WWI) and a body shape index (ABSI) are related to serum neurofilament light chain (sNfL) levels among U.S. adults. We aimed to evaluate sNfL, which plays key roles in neuronal injury in neurological diseases, given its understudied connection to obesity.MethodsWe used cross-sectional data from the 2013–2014 National Health and Nutrition Examination Survey (NHANES) of people with complete information on the weight-adjusted waist index (WWI), a body shape index (ABSI), and serum neurofilament light chain (sNfL). Multiple linear regression analysis allowed us to investigate the separate connections among the WWI, ABSI, and sNfL. Moreover, interaction testing and subgroup analysis were performed to improve the general validity of our results. To assess any nonlinear correlations, we also performed threshold effect analysis and smoothed curve fitting.ResultsWWI and ABSI were positively linked with sNfL (WWI: β = 0.05, 95% CI 0.01–0.09; ABSI: β = 1.65, 95% CI 3.53–13.72). There was no clear reliance on this association according to subgroup analysis and interaction tests. Smoothed curve fitting and saturation effects also demonstrated nonlinear associations between WWI and ABSI and sNfL, with inflection points of 10.38 and 0.38, respectively.ConclusionIn the adult American population, while the WWI and ABSI are linearly positively correlated with serum neurofilament light protein (sNfL), the effect size is greater for the ABSI. This correlation provides fresh evidence connecting obesity to neurological conditions, deepening our comprehension of the extensive health impacts associated with obesity.Level of Evidence Level I, experimental studies.

BackgroundPrevious studies have explored the associations between obesity and Parkinson’s disease (PD), often using body mass index (BMI) as the main metric. However, findings remain inconsistent. Anthropometric indices—quantitative measures of body shape, size, and fat distribution—offer alternative ways to assess adiposity. This study aimed to evaluate the associations between eight anthropometric indices and PD prevalence.MethodsData were obtained from the National Health and Nutrition Examination Survey (NHANES), conducted in the U.S. from 1999 to 2020. A total of 41,374 participants aged 20 years and older were included, among whom 354 were diagnosed with PD. Eight anthropometric indices were analyzed: waist-to-weight index (WWI), conicity index (CI), a body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), BMI, waist circumference (WC), and weight (WT). Weighted multivariable logistic regression models were used to assess the association between these indices and PD. Restricted cubic spline (RCS) models were employed to examine dose–response relationships. Subgroup and sensitivity analyses were conducted to validate the robustness of the findings.ResultsSignificant differences were observed between the study groups, with positive and independent correlations identified between PD and all anthropometric measures, except BMI. After full adjustment, each 1-standard deviation increase in WWI, CI, ABSI, BRI, WHtR, WC, and WT was associated with an elevated PD risk by 34, 42, 36, 18, 21, 25, and 16%, respectively. RCS analysis revealed a linear relationship between CI, ABSI, BRI, WtHR, WC, WT, and PD prevalence, whereas WWI exhibited a nonlinear association. The subgroup and sensitivity analyses confirmed the consistency of these associations.ConclusionHigher values of several anthropometric indices, particularly the ABSI, WWI, and CI, were associated with increased PD prevalence. These findings highlight the potential role of fat distribution rather than overall adiposity in PD pathogenesis. Anthropometric measures may be valuable tools for early PD risk identification and targeted prevention strategies.