Secular Trends and Prognostic Value of the Body Shape Index in U.S. Adults.

BackgroundIndividuals with cardiovascular-kidney-metabolic (CKM) syndrome exhibit a substantially elevated risk of all-cause and cardiovascular-specific mortality. Although estimated glucose disposal rate (eGDR) and a body shape index (ABSI) are commonly used indicators for assessing insulin resistance and atherosclerotic risk, respectively, evidence regarding their combined effect on all-cause and cardiovascular-specific mortality in patients with CKM syndrome remains insufficient. Investigating this combined impact may help improve risk stratification in this population.MethodsThis study utilized data from the National Health and Nutrition Examination Survey (NHANES, 1999–2018), including 18,186 individuals with stage 0–4 CKM syndrome. Cox proportional hazards models, Kaplan–Meier curves and subgroup analyses were used to evaluate the associations between eGDR and ABSI and mortality risk. The integrated discrimination improvement (IDI) and net reclassification index (NRI) were used to assess the incremental prognostic value of eGDR and ABSI. Finally, six machine learning algorithms were applied to develop predictive models.ResultsDuring the follow-up period, a total of 2536 all-cause mortality and 790 cardiovascular-specific mortality were documented. After multivariable adjustment, both low eGDR and high ABSI independently predicted mortality risk. Combined analysis revealed that individuals with both Low-eGDR and High-ABSI had the highest mortality risk: all-cause mortality hazard ratio (HR) = 2.79 (95% CI 2.30–3.38) and cardiovascular-specific mortality HR = 4.53 (95% CI 2.96–6.92). However, the interaction effect was not statistically significant. Among the six machine learning algorithms, XGBoost demonstrated the best performance, with areas under the curve (AUC) of 0.877 and 0.850 for predicting all-cause and cardiovascular-specific mortality, respectively.ConclusionBoth eGDR and ABSI are independent and combined predictors of mortality risk among individuals with CKM syndrome. Their combined use significantly improves risk stratification and machine learning models provide an effective tool for precise risk assessment in this population.Graphical abstractSupplementary InformationThe online version contains supplementary material available at 10.1186/s12933-026-03127-x.

Limited research has focused on how anthropometric measures relate to mortality risk, specifically among postmenopausal women. Our study aimed to explore the association between anthropometric indices and risks of all-cause and cardiovascular mortality in American postmenopausal women. Data from the NHANES cycles 1999-2018 were extracted. Firstly, weighted multivariable Cox proportional hazards models and restricted cubic splines (RCS) were used to detect the association between six body indicators, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and weight-adjusted waist index (WWI), and all-cause and CVD mortality risk in postmenopausal women. Furthermore, the predictive power of different anthropometric indices for mortality was assessed by time-dependent receiver operator characteristic (ROC) curves. Subgroup and sensitivity analyses were further employed to evaluate the consistency and robustness of the findings. During an average follow-up of 10.04 years, 2522 deaths were reported from any cause, and 783 participants died of CVD in total. A fully adjusted multivariate Cox regression model indicated a significant positive association between WWI and ABSI and all-cause and CVD mortality in postmenopausal Americans. The RCS revealed a significant nonlinear relationship between BRI and WC and all-cause mortality, whereas the relationships between WWI and ABSI and CVD/all-cause mortality were positively linear. For all-cause mortality prediction, WWI outperformed other anthropometric parameters, with an AUC of 0.616 (95% CI 0.594-0.637) for 5 year, 0.624 (95% CI 0.608-0.640) for 10-year, and 0.641 (95% CI 0.624-0.658) for 15-year. Consistently, WWI showed the highest AUC of 0.642 (95% CI 0.605-0.679), 0.656 (95% CI 0.631-0.681)and 0.675 (95% CI 0.651-0.699) when predicting 5-year, 10-year and 15-year CVD mortality, respectively. Subgroup and sensitivity analyses confirmed the stability and robustness of our findings. Higher ABSI and WWI values were linearly associated with increased all-cause and CVD mortality in postmenopausal women in the U.S. WWI and ABSI anthropometric indicators may be useful tools to detect CVD and all-cause mortality risks and to support early intervention strategies for individuals after menopause in clinical practice.

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is burdened by significant all-cause and cardiovascular mortality, yet simple and effective predictive indices for long-term outcomes are currently lacking. In this study, we investigated the prognostic value of the triglyceride glucose–a body shape index (TyG-ABSI), a novel composite of insulin resistance and visceral adiposity, for mortality in MASLD.MethodsThis prospective cohort study included 7515 adults with MASLD from the National Health and Nutrition Examination Survey (NHANES, 1999–2018). MASLD was defined as a Fatty Liver Index ≥ 60 accompanied by at least one cardiometabolic risk factors. The primary outcomes were all-cause mortality (ACM) and cardiovascular mortality (CVM). Kaplan-Meier survival curves, multivariable Cox regression, restricted cubic splines (RCS), and receiver operating characteristic (ROC) analyses were employed to evaluate the predictive value of TyG-ABSI. Additionally, subgroup, sensitivity, and mediation analyses were conducted to verify robustness and explore underlying mechanisms.ResultsDuring a median follow-up of 138 months, 1368 all-cause and 376 cardiovascular deaths were recorded. TyG-ABSI demonstrated improved predictive accuracy compared to TyG, TyG-BMI, TyG-WC, and TyG-WHtR, as evidenced by higher AUC values and significant Net Reclassification Improvement（NRI). In fully adjusted models, participants in the highest TyG-ABSI quartile faced significantly elevated risks of ACM (HR 1.49, 95% CI 1.03–2.14) and CVM (HR 2.32, 95% CI 1.02–5.30) relative to the lowest quartile. RCS analysis indicated a linear dose-response relationship, and the associations remained robust across subgroup and sensitivity analyses. Mediation analysis revealed that accelerated biological aging significantly mediated mortality risks, with KDM and HD explaining 24.75% and 32.15% of ACM, and 34.89% and 46.53% of CVM, respectively.ConclusionsTyG-ABSI serves as a robust, independent predictor of mortality in patients with MASLD, outperforming traditional TyG-related metrics. The association is significantly associated with the pathway of accelerated biological aging, highlighting the utility of TyG-ABSI for enhanced risk stratification in clinical practice.Graphical abstractSupplementary InformationThe online version contains supplementary material available at 10.1186/s12933-026-03112-4.

While novel adiposity indices such as the body roundness index (BRI), a body shape index (ABSI), the visceral adiposity index (VAI), and the Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index outperform body mass index (BMI) in predicting cardiovascular disease (CVD) risk, their long-term trajectories remain unstudied in Iran. We investigated the patterns of the BRI/ABSI/VAI/CUN-BAE index and their associations with the risk of CVD, all-cause mortality, and specific-cause mortality among Iranian adults. This prospective cohort study analyzed 11,394 Iranian adults (55.5% women, mean age 41.2 ± 15.0 years) from the Tehran Lipid and Glucose Study (1999–2018). Latent class growth mixture modeling identified trajectories of adiposity indices over a median of 18.0 years. Cox models assessed associations between the trajectories and incident CVD (n = 728), all-cause mortality (n = 532), and cause-specific mortality, adjusting for various socio-demographic, lifestyle, and metabolic confounders. Three distinct trajectories (low, moderate, and high-increase) emerged for all indices, with the high-increasing trajectories showing the strongest associations for CVD risk, the CUN-BAE index (HR: 2.45, 95%CI: 1.73–3.49), BRI (HR: 2.12, 95%CI: 1.65–2.73), ABSI (HR: 2.02, 95%CI: 1.38–2.95), and VAI (HR: 1.92, 95% CI: 1.49–2.49). Besides, the high-increase in BRI was associated with a higher risk of all-cause mortality (HR: 1.47, 95% CI: 1.10–1.96) and cardiovascular mortality (HR: 3.25, 95% CI: 1.85–5.69) compared with the low-increase group. There was no relationship between trajectory in the CUN-BAE index, VAI, and ABSI and risk of all-cause and cause-specific mortality. Notably, no significant associations were observed between any adiposity index trajectories and cancer mortality. Longitudinal trajectories of adiposity indices particularly BRI strongly predict CVD and mortality risks in Iranian adults. These findings support the incorporation of dynamic adiposity measures into clinical risk stratification.

A body shape index is a better predictor of overall and cardiovascular mortality than body mass index: Results from the ENAH study.

ObjectiveTo quantify the association of indices of central obesity, including waist circumference, hip circumference, thigh circumference, waist-to-hip ratio, waist-to-height ratio, waist-to-thigh ratio, body adiposity index, and A body shape index,...

Objective: To describe and analyze the distribution characteristics of a body shape index (ABSI) and its association with all-cause mortality in the elderly in communities of Beijing. Methods: The baseline and follow-up data of 10 423 subjects in Beijing Healthy Aging Cohort Study were used. The endpoint outcome was all-cause mortality in follow-up. The associations of ABSI, BMI and waist circumference with all-cause mortality were analyzed with a Cox proportional hazard regression model. Results: The mean follow-up time in this cohort was 6.36 years and the all-cause mortality was 15.27%. The restricted cubic spline results showed that ABSI showed a "U" association with all-cause mortality in the total population. After adjustment for confounding factors, compared with the normal ABSI group, the risk for all-cause mortality was higher in the low ABSI group (HR=1.69, 95%CI: 1.32-2.17) and high ABSI group (HR=1.75, 95%CI: 1.40-2.18). Compared with the normal BMI group, low BMI was associated with an increased risk for all-cause mortality (HR=1.70, 95%CI: 1.40-2.08). Compared with the normal waist circumference group, central obesity was associated with a decreased risk for all-cause mortality (HR=0.89, 95%CI: 0.80-0.99). The results of gender specific analysis on ABSI association with all-cause mortality were similar to that in total population, but the strength of association varied among different age groups. Cross-grouping results showed that older people with normal BMI and waist circumference and abnormal ABSI had an increased risk of all-cause mortality (HR=1.91, 95%CI: 1.22-2.99). Conclusions: In Beijing, ABSI is correlated with the risk for all-cause mortality in the elderly population, which is more sensitive and specific than the traditional indicators (BMI and waist circumference). They can be used as one of the physical measurement indicators for all-cause mortality risk prediction in the health risk assessment and management in the elderly.

Estimates indicate that household air pollution caused by solid fuel burning accounted for about 1.03 million premature mortalities in China in 2016. In the country's rural areas, more than half the population still relies on biomass fuels and coals for cooking and heating. Understanding the health impact of indoor air pollution and socioeconomic indicators is essential for the country to improve its developmental targets. We aimed to describe demographic and socioeconomic characteristics associated with solid fuel users in a rural area in China. We also estimated the risk of cardiovascular disease and all-cause mortality in association with solid fuel use and described the relationship between solid fuel use, socioeconomic status and mortality. We also measured the risk of long-term use, and the effect of ameliorative action, on mortality caused by cardiovascular disease and other causes. We used the China Kadoorie Biobank (CKB) site in Pengzhou, Sichuan, China. We followed a cohort of 55 687 people over 2004-13. We calculated the mean and standard deviation among subgroups classified by fuel use types: gas, coal, wood and electricity (central heating additionally for heating). We tested the mediation effect using the stepwise method and Sobel test. We used Cox proportional models to estimate the risk of incidences of cardiovascular disease and mortality with survival days as the time scale, adjusted for age, gender, socioeconomic status, physical measurements, lifestyle, stove ventilation and fuel type used for other purposes. The survival days were defined as the follow-up days from the baseline survey till the date of death or 31 December 2013 if right-censored. We also calculated the absolute mortality rate difference (ARD) between the exposure group and the reference group. The study population had an average age of 51.0, and 61.9% of the individuals were female; 64.8% participants (n = 35 543) cooked regularly and 25.4% participants (n = 13 921) needed winter heating. With clean fuel users as the reference group, participant households that used solid fuel for cooking or heating both had a higher risk of all-cause mortality: hazard ratio (HR) for: cooking, 1.11 [95% confidence interval (CI) 1.02, 1.26]; heating, 1.34 (95% CI 1.16, 1.54). Solid fuel used for winter heating was associated with a higher risk of mortality caused by cerebrovascular disease: HR 1.64 (95% CI 1.12, 2.40); stroke: HR 1.70 (95% CI 1.13, 2.56); and cardiovascular disease: HR 1.49 (95% CI 1.10, 2.02). Low income and poor education level had a significant correlation with solid fuel used for cooking: odds ratio (OR) for income: 2.27 (95% CI 2.14, 2.41); education: 2.34 (95% CI 2.18, 2.53); and for heating: income: 2.69 (95% CI 2.46, 2.97); education: 2.05 (95% CI 1.88, 2.26), which may be potential mediators bridging the effects of socioeconomic status factors on cardiovascular disease and all-cause mortality. Solid fuel used for cooking and heating accounted for 42.4% and 81.1% of the effect of poor education and 55.2% and 76.0% of the effect of low income on all-cause mortality, respectively. The risk of all-cause mortality could be ameliorated by stopping regularly cooking and heating using solid fuel or switching from solid fuel to clean fuels: HR for cooking: 0.90 (95% CI 0.84, 0.96); heating: 0.76 (95% CI 0.64, 0.92). Our study reinforces the evidence of an association between solid fuel use and risk of cardiovascular disease and all-cause mortality. We also assessed the effect of socioeconomic status as the potential mediator on mortality. As solid fuel use was a major contributor in the effect of socioeconomic status on cardiovascular disease and all-cause mortality, policies to improve access to clean fuels could reduce morbidity and mortality related to poor education and low income.

That elevated heart rate (HR) is a risk factor for cardiovascular morbidity and mortality in healthy people as well as in patients with cardiac diseases is supported by numerous epidemiological association studies.1–4 Increased HR has been recognized as a negative prognostic factor independent of many other clinical parameters that can influence the HR, including physical activity scores, left ventricular function, or use of β-blockers. Thus, HR appears to satisfy all epidemiological criteria for being considered as a true risk factor, and its predictive value for cardiovascular disease appeared to be as strong as that of most important cardiovascular risk factors. This is particularly true for the results obtained in hypertensive patients. Elevated HR is a common feature among hypertensive individuals.1 Among the young hypertensive subjects participating in the HARVEST study, >15% had a baseline resting HR ≥85 bpm and 27% had a HR ≥80 bpm.5 According to the Tensiopulse study, which evaluated 38 145 patients cared for by 2000 general practitioners all across Italy, >30% of the hypertensive patients had a resting HR ≥80 bpm.6 In a large French population, untreated hypertensive subjects had approximately a 6-bpm faster HR than normotensive individuals.7 Elevated HR is frequently associated with high blood pressure (BP) and metabolic disturbances and increases the risk of new onset hypertension and diabetes.1 Many experimental data obtained both in animals and in human beings support the importance of HR as a true risk factor for atherosclerosis and cardiovascular disease, providing convincing evidence for this pathogenetic mechanism.1–3 The pathogenetic connection between HR and cardiovascular disease has been discussed in several reports1–3,8,9 and is beyond the scope of this review. ### High HR as a Precursor of Hypertension, Obesity, and Diabetes Numerous studies have demonstrated that tachycardia is frequently associated with hypertension in …

Association of a body shape index (ABSI) with chronic kidney disease prevalence, all-cause and cardiovascular mortality: A 20-year prospective cohort study of 29,189 U.S. adults.

Cardiorespiratory fitness: an independent and additive marker of risk stratification and health outcomes.

Conflicting evidence exists on the association of obesity, depression and mortality risk. This study evaluates a cohort of subjects with depression from the USA NHANES and all-cause and cardiovascular mortality risks based on baseline BMI and ABSI. A nationally representative cohort study was conducted using NHANES data (2005-2018), including 2854 adults with depression. Weighted Cox regression and restricted cubic spline (RCS) models were applied to assess anthropometric associations with mortality. Weighted receiver operating characteristic (ROC) curves evaluated the diagnostic value of BMI and ABSI. Each 1-SD BMI increase was predictive of reduced all-cause (HR = 0.81, 95 % CI:0.67-0.98) and cardiovascular mortality (HR = 0.62, 95 % CI:0.43-0.89). Each 1-SD ABSI increase was predictive of elevated all-cause (HR = 1.27, 95 % CI:1.06-1.51) and cardiovascular mortality (HR = 1.60, 95 % CI:1.20-2.15). In these depressed individuals, BMI showed the U-shaped and ABSI the expected curvi-linear relationships with mortality as established from the studies of the NHANES cohorts. In ROC analyses, ABSI showed the best predictive performance for all-cause mortality (AUC = 0.678) and for cardiovascular mortality (AUC = 0.706). BMI Tertile 1 & ABSI Tertile 3 had the highest mortality risks (all-cause HR = 3.09, 95 % CI:1.38-6.93; cardiovascular HR = 5.45, 95 % CI:1.36-21.85). Due to the approximate statistical independence of BMI and ABSI, combining them further improved AUC values (all-cause: 0.691; cardiovascular: 0.722). Among individuals with depression ABSI predicts mortality similar to the general population, while obesity as defined by BMI was "paradoxically" associated with lower mortality. Personalized mortality risk for an individual can be derived by combining the independent risks based on BMI and ABSI.

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.

Optimizing clinical outcomes resulting from glucose‐lowering therapies in type 2 diabetes: increased confidence about the <scp>DPP</scp>‐4 inhibitors and continued concerns regarding sulphonylureas and exogenous insulin

BackgroundThe American Heart Association (AHA) proposed the concept of cardiovascular–kidney–metabolic (CKM) syndrome, underscoring the interconnectedness of cardiovascular, renal, and metabolic diseases. The stress hyperglycemia ratio (SHR) represents an innovative indicator that quantifies blood glucose fluctuations in patients experiencing acute or subacute stress, correlating with detrimental clinical effects. Nevertheless, the prognostic significance of SHR within individuals diagnosed with CKM syndrome in stages 0 to 3, particularly with respect to all-cause or cardiovascular disease (CVD) mortality risks, has not been fully understood yet.MethodsThe current study analyzed data from 9647 participants with CKM syndrome, covering stages 0 to 3, based on the NHANES (National Health and Nutrition Examination Survey) collected from 2007 to 2018. In this study, the primary exposure variable was the SHR, computed as fasting plasma glucose divided by (1.59 * HbA1c − 2.59). The main endpoints of study were all-cause mortality as well as CVD mortality, with death registration data sourced through December 31, 2019. The CHARLS database (China Health and Retirement Longitudinal Study) was utilized as validation to enhance the reliability of the findings.ResultsThis study included 9647 NHANES participants, who were followed for a median duration of 6.80 years. During this period, 630 all-cause mortality cases and 135 CVD-related deaths in total were recorded. After full adjustment for covariates, our results displayed a robust positive association of SHR with all-cause mortality (Hazard ratio [HR] = 1.09, 95% Confidence interval [CI] 1.04–1.13). However, the SHR exhibited no significant relationship with CVD mortality (HR = 1.00, 95% CI 0.91–1.11). The mediation analysis results suggested that the relationship between SHR and all-cause mortality risk is partially mediated by RDW, albumin, and RAR. Specifically, the mediating effects were − 17.0% (95% CI − 46.7%, − 8.7%), − 10.1% (95% CI − 23.9%, − 4.7%), and − 23.3% (95% CI − 49.0%, − 13.0%), respectively. Additionally, analyses of the CHARLS database indicated a significant positive correlation between SHR and all-cause mortality among individuals diagnosed with CKM across stages 0–3 during the follow-up period from 2011 to 2020.ConclusionsAn increased SHR value is positively associated with an elevated likelihood of all-cause mortality within individuals diagnosed with CKM syndrome across stages 0–3, yet it shows no significant association with CVD mortality. SHR is an important tool for predicting long-term adverse outcomes in this population.Graphical abstractResearch insights summaryCardiovascular–kidney–metabolic (CKM) syndrome emphasizes the interconnectedness of cardiovascular, kidney, and metabolic diseases. The stress hyperglycemia ratio (SHR) is a novel marker reflecting stress-induced glucose fluctuations, but its prognostic value in individuals with CKM syndrome (stages 0–3) remains uncertain. This study explores the association between SHR and all-cause and cardiovascular disease (CVD) mortality in this population. Our findings indicate that SHR is significantly associated with an increased risk of all-cause mortality (HR = 1.09, 95% CI 1.04–1.13), but not with CVD mortality (HR = 1.00, 95% CI: 0.91–1.11). Mediation analysis results suggested that the relationship between SHR and all-cause mortality risk is partially mediated by RDW, albumin, and RAR. Specifically, the mediating effects were − 17.0% (95% CI − 46.7%, − 8.7%), − 10.1% (95% CI − 23.9%, − 4.7%), and − 23.3% (95% CI − 49.0%, − 13.0%), respectively. Validation using the CHARLS database supports these findings. These results suggest that SHR could serve as a prognostic biomarker for long-term mortality risk in CKM patients, offering potential clinical utility in risk stratification and management.