Waist to height ratio as a simple tool for predicting mortality: a systematic review and meta-analysis

Exploring the Science of Shape: How Physical Activity, Sleep, and Stress Affect Body Composition

In the contemporary context of health challenges, the focus on physical health has become a social and individual priority. Within this framework, body composition emerges as one of the key determinants of physical health, with deviations from normal body composition being associated with numerous pathological conditions that can lead to serious health issues. Consequently, there is an urgent need to synthesize the available knowledge and increase awareness regarding healthy body composition and the factors that shape its components. This narrative review aims to summarize the knowledge regarding the main components of body composition and the key factors that influence their development. The fundamental morphological characteristics and functions of the primary components of body composition-including adipose tissue, muscle mass, and bone tissue-are addressed. Furthermore, the available methods for assessing body composition are outlined. The role of three key factors that influence body composition is outlined, including, but not limited to, physical activity, sleep quality, and stress levels. Additionally, hormonal fluctuations that determine body composition in relation to the variability of these factors are discussed. The review provides evidence-based information that will be valuable both for disease prevention related to non-communicable diseases and for the promotion of health strategies aimed at long-term physical well-being.

From error to insight: Removing non-systematic responding data in the delay discounting task may introduce systematic bias

Delay discounting (DD), which reflects a tendency to devalue rewards as the time to their receipt increases, is associated with health behaviors such as sleep disturbances, obesity, and externalizing behavior among adolescents. Response patterns characterized by inconsistent or unexpected reward valuation, called non-systematic responding (NSR), may also predict health outcomes. Many researchers flag and exclude NSR trials prior to analysis, which could lead to systematic bias if NSR (a) varies by demographic characteristics or (b) predicts health outcomes. Thus, in this study we characterized NSR and examined its potential beyond error by comparing it against DD with a secondary data analysis of the Adolescent Brain Cognitive Development (ABCD) Study-a population-based study that tracked youths (N = 11,948) annually from 8 to 11 years of age over 4 years. We assessed DD and NSR using the Adjusting Delay Discounting Task when youths were approximately 9.48 years old (SD = 0.51). We also examined three maladaptive health outcomes annually: sleep disturbances, obesity, and externalizing psychopathology. Our analysis revealed variations in NSR across races, ethnicities, and body mass index categories, with no significant differences observed by sex or gender. Notably, NSR was a stronger predictor of obesity and externalizing psychopathology than DD and inversely predicted the growth trajectory of obesity. These findings suggest that removing NSR patterns could systematically bias analyses given that NSR may capture unexplored response variability. This study demonstrates the significance of NSR and underscores the necessity for further research on how to manage NSR in future DD studies.

Association of cardiometabolic index and new-onset stroke in middle-aged and elderly Chinese: a national prospective cohort study

BACKGROUND AND AIMS

The Cardiometabolic Index (CMI), a novel metabolic marker, has been associated with various metabolic diseases in previous studies. However, its relationship with stroke risk remains underexplored. This study investigates the potential correlation between CMI and stroke risk among Chinese adults aged 45 and older.

METHODS

In the China Health and Retirement Longitudinal Study (CHARLS), participants were categorized into four groups based on CMI quartiles. The primary outcome was the incidence of new strokes during the follow-up period. A Cox proportional hazards model was used to analyze the relationship between CMI and stroke risk among the elderly. Kaplan-Meier survival analysis compared incidence rates across CMI levels, and restricted cubic splines (RCS) assessed potential non-linear relationships between CMI and stroke. Subgroup analyses verified the robustness of these findings.

RESULTS

The study included 6620 patients (45% male), with 417 new stroke cases reported over an average follow-up of seven years. Multivariate analysis indicated a significant association between increased CMI and higher stroke risk [HR, 1.132 (1.021-1.273), P = 0.003]. The RCS model revealed a nonlinear increase in stroke risk with rising CMI levels (P for nonlinearity = 0.006). No significant interactions were detected between CMI and the selected subgroups (all P values for interaction > 0.05).

CONCLUSION

CMI significantly correlates with stroke risk in the elderly Chinese population, suggesting its potential utility in early risk stratification.

Physical activity, cardiovascular disease, and mortality across obesity levels

Aims

High physical activity (PA) is associated with decreased risk of cardiovascular disease (CVD) and mortality. However, whether PA can be sufficient to reduce the risk of CVD and mortality contributing to adiposity remains unclear. From the standpoint of predictive, preventive, and personalized medicine (PPPM/3PM), joint assessment of PA and adiposity provides novel insights for individual risk assessment, targeted prevention, and personalized intervention of CVD.

Methods

This prospective cohort study included 92,931 participants in the Kailuan study in Tangshan, followed between the years 2006 and 2020. Adiposity was assessed by body mass index (BMI) and waist circumference (WC). The CVD incidence and all-cause mortality associated with 3 PA levels (low, medium, and high PA) were analyzed by applying Cox regression models to different adiposity subgroups.

Results

After a median follow-up period of 14.02 years, 9997 incident CVD cases and 12,586 deaths occurred. Surprisingly, low PA and lean body mass were at a lower risk for CVD than other phenotypes. Participants with high PA still had a 35% higher CVD risk from obesity (hazard ratio (HR) BMI: 1.35, 95% confidence interval (CI): 1.18-1.54) and a 10% higher CVD risk from central obesity (HRcentral obesity: 1.10, 95% CI: 1.00-1.21) than those with lean. However, only in obese individuals, high PA has a protective effect on CVD (HR: 0.78, 95% CI: 0.64-0.95). Overall obesity and high PA were not associated with increased risk of all-cause mortality, whereas high PA could not attenuate mortality risk associated with central obesity.

Conclusion

High PA did not attenuate the risk of CVD associated with adiposity compared with lean body mass among the Chinese population, whereas the combination of high PA and healthy WC might improve healthy aging and longevity. In addition, this study revealed the importance of maintaining muscle health in obese individuals via PA or other ways. It provides a novel strategy for mitigating the risk of CVD by exercising intervention or maintaining body mass, thereby enhancing effective prevention and targeted intervention.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-025-00397-5.

The association between android-to-gynoid lean mass ratio and all-cause and specific-cause mortality in US adults: A prospective study

OBJECTIVE

The associations of lean mass distribution with mortality risk are not fully elucidated. We aimed to evaluate the effects of a new lean mass distribution indicator-android/gynoid lean mass ratio (AGLR) evaluated by dual-energy x-ray absorptiometry (DXA) on the risk of all-cause and specific-cause mortality in a NHANES cohort.

METHODS

This was a population-based cohort study, which included 18 542 subjects aged 20 years and older from the US National Health and Nutrition Examination Survey (US NHANES, 2003-2006 and 2011-2018). The primary outcomes of our study were all-cause mortality, cardiovascular (CVD) mortality and cancer mortality, which were obtained from the linkage to registries. Cox proportional hazard regression models were used to investigate the association between lean mass distribution and mortality risk among the US NHANES general population. Restricted cubic spline nested in Cox regression was also used to test whether there was a non-linear association of AGLR as a continuous variable with the risk of mortality.

RESULTS

During a median follow-up of 6.9 years, 1412 participants died, of whom 435 were due to CVD and 340 were due to cancer. The multivariable-adjusted (Model 4) hazard ratios (HRs) for each SD increase in AGLR were 1.53 (95% confidence interval [CI] 1.40-1.67) for all-cause mortality, 1.56 (95% CI 1.30-1.87) for cancer mortality and 1.64 (95% CI 1.47-1.84) for CVD mortality. The associations were robust in sensitivity analyses and present in most subgroups.

CONCLUSIONS

AGLR evaluated by DXA was associated with a higher risk of all-cause and specific-cause mortality among the general population from the US NHANES cohort.

Causal associations of immunophenotypes with metabolic dysfunction-associated fatty liver disease and mediating pathways: a Mendelian randomization study

Background

Increasing evidence suggests that immunophenotypes play a crucial role in Metabolic dysfunction-associated fatty liver disease (MAFLD), but the specific immunophenotypes contributing to its pathogenesis remain unclear.

Objectives

This study aimed to elucidate the causal associations between immunophenotypes and MAFLD and identify the underlying mediation pathways involved.

Design

Mendelian randomization (MR) study.

Methods

This study is a quasi-causal inference analysis using univariable and multivariable MR (UVMR and MVMR). Five MAFLD genome-wide association studies (GWASs) and the largest immunophenotype GWAS were analyzed to assess their causal associations. Two-step MR identified potential mediators and quantified their mediation proportions. Comprehensive MR methods, multiple sensitivity analyses, meta-analyses, and false discovery rate (FDR) further enhanced the robustness of our findings.

Results

Pooled inverse-variance weighted (IVW) estimates in UVMR identified 47 immunophenotypes having a suggestive causal association with MAFLD. After adjusting for FDR, three lymphocyte phenotypes remained significant: CD20 on IgD-CD24- B cells (OR: 1.035, p fdr: 0.006), terminally differentiated CD8+ T cells %T cells (OR: 1.052, p fdr: 0.006), and CD4 on CD39+ secreting CD4+ regulatory T cells (OR: 1.036, p fdr: 0.046). Meta-analysis of IVW MVMR estimates with confounders adjustment confirmed that CD20 on IgD-CD24- B cells and terminally differentiated CD8+ T cells %T cells had significant direct causal associations on MAFLD (p fdr < 0.05). Additionally, two-step MR analysis identified the waist-to-hip ratio as a mediator, accounting for 42.64% of the causal association between CD20 on IgD-CD24- B cells and MAFLD.

Conclusion

The causal associations of three lymphocyte phenotypes with increased MAFLD risk were identified in this study. CD20 on IgD-CD24- B cells may both directly and indirectly elevate MAFLD risk, while terminally differentiated CD8+ T cells have a direct causal relationship with MAFLD. These findings suggest new possibilities for targeted therapies and underscore the potential for personalized immunotherapy in managing MAFLD.

The waist-to-height ratio is a good predictor for insulin resistance in women with polycystic ovary syndrome

Objective

This study aimed to explore the role of the waist-to-height ratio (WHtR) in assessing insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS).

Materials and methods

We enrolled 882 PCOS-afflicted women in a cross-sectional analysis to evaluate the association of the WHtR with IR. Their demographic characteristics, anthropometric parameters, and fasting blood samples were collected and measured. Moreover, IR was evaluated by homeostatic model assessment of insulin resistance (HOMA-IR). We estimated the relationship between the WHtR and IR and the cut-off thresholds of the WHtR for IR using multivariable linear regression and logistic regression models, respectively.

Results

The prevalence rate of IR was 51.9%. The patients with PCOS and IR displayed significantly increased values for body mass index (BMI), waist circumference (WC), WHtR, systolic blood pressure (SBP), diastolic blood pressure (DBP), free androgen index (FAI), HOMA-IR, total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (ApoB). However, the patients with PCOS and IR showed a reduction in estradiol (E2), luteinizing hormone (LH), LH/FSH ratio, sex hormone binding globulin (SHBG), and high-density lipoprotein (HDL-C) values than those without IR. Moreover, BMI (log-transformed), WC, and HOMA-IR (log-transformed) were positively correlated with the WHtR. When adjusting for potential confounding variables, the WHtR was significantly associated with HOMA-IR (log-transformed), with a standardized regression coefficient of 0.271. Furthermore, the WHtR was significantly associated with an increased risk of IR, with the adjusted odds ratio (OR) of 3.15 (WHtR multiplied by 10). Additionally, the WHtR helped to identify IR in women with PCOS with an optimal cut-off point of 0.519 (Youden index = 0.433).

Conclusions

The WHtR had a positive association with IR in women with PCOS. Hence, we suggest that the WHtR, as a simple, practical, and reliable anthropometric measure, can be used to predict the risk of IR in patients with PCOS.

Cohort profile of a prospective cohort study among middle-aged community-dwellers in rural Vietnam: The Khánh Hòa Cardiovascular Study

Disease burden associated with cardiovascular diseases (CVDs) in low- and middle-income countries has been on an increasing trend in the past decades. Despite the worldwide genetic, cultural, and environmental variations in determinants of CVDs, few studies have attempted the identification of risk factors of CVDs in low- and middle-income countries. This article aims to introduce the Khánh Hòa Cardiovascular Study, a prospective cohort study among middle-aged community dwellers in rural Khánh Hòa, Vietnam. A total of 3000 individuals, aged 40-60 years at baseline, participated in the baseline survey conducted from June 2019 to June 2020 and will be followed up for the subsequent 10 years. The baseline survey collected information on sociodemographic variables, disease history, lifestyle, social environment, and mental health via questionnaires, physical examinations, and biochemical measurements. Information on the incidence of severe health outcomes (i.e., mortality, CVDs, and cancer) has been and will be collected using a study-specific disease registry. Results showed that the prevalences of excess body weight (body mass index ≥25 kg/m2), hypertension, diabetes mellitus, and dyslipidemia were 25.9%, 39.6%, 10.2%, and 45.1%, respectively. Furthermore, by March 2023, 21 participants had died, including 5 CVD deaths and 12 cancer deaths. Moreover, we recorded 22 and 31 cases of nonfatal CVDs and cancer, respectively. These results suggest that many rural residents in Vietnam have high cardiometabolic risk, and underscore the importance of advancing research to identify risk factors and prevent the onset of serious health events.

Prevalence Rates of Abdominal Obesity, High Waist-to-Height Ratio and Excess Adiposity, and Their Associated Cardio-Kidney-Metabolic Factors: SIMETAP-AO Study

BACKGROUND/OBJECTIVE

In addition to obesity, adiposity and abdominal obesity (AO) are parameters included in the cardiovascular-kidney-metabolic (CKM) syndrome. However, their prevalence and association with the other CKM factors have been less studied. Our study aimed to determine the prevalence rates of AO, high waist-to-height ratio (WtHR), and excess adiposity (EA), and to compare their associations with CKM factors.

METHODS

A cross-sectional observational study was conducted with a random population-based sample of 6,588 study subjects between 18 and 102 years of age. Crude and sex- and age-adjusted prevalence rates of AO, high-WtHR, and EA were calculated, and their associations with CKM variables were assessed by bivariate and multivariate analyses.

RESULTS

The adjusted prevalence rates for AO, high-WtHR, and EA were 39.6% (33.6% in men; 44.9% in women), 30.6% (31.1% in men; 30.6% in women), and 65.6% (65.6% in men; 65.3% in women), respectively, and they increased with age. The main independent factors associated with AO, high-WtHR, and EA were hypertension, diabetes, prediabetes, low HDL-C, hypercholesterolaemia, hypertriglyceridemia, physical inactivity, hyperuricemia, and chronic kidney disease.

CONCLUSIONS

Two-thirds of the adult population have EA, one-third have AO, and one-third have high-WtHR. These findings support that the other factors of CKM syndrome, in addition to hyperuricemia and physical inactivity, show an independent association with these adiposity-related variables.

Hyperuricaemia Prevalence Rates According to Their Physiochemical and Epidemiological Diagnostic Criteria and Their Associations with Cardio-Renal-Metabolic Factors: SIMETAP-HU Study

Background: Scientific societies disagree on serum uric acid (SUA) thresholds for the diagnosis of hyperuricaemia (HU) according to epidemiological or physiochemical criteria (SUA ≥ 7.0 mg/dL for men and ≥6.0 mg/dL for women [HU-7/6]; SUA ≥ 7.0 mg/dL for both genders [HU-7/7], respectively). HU is not included among the diagnostic criteria for metabolic syndrome or cardiovascular-renal-metabolic syndrome (CKM), although it promotes atherosclerosis and is associated with renal and cardiometabolic diseases. Both issues are of utmost importance and need to be clarified, hence the present study aims to assess the prevalence rates of HU and their associations with CKM factors. Methods: A cross-sectional observational study was conducted on a random population-based sample of 6489 adults. Bivariate and multivariate analyses were performed on the most well-known renal and cardiometabolic variables of the populations with and without HU-7/7 and HU-7/6. Results: The adjusted prevalence rates for HU-7/6 were 13.4% in adult population (18.4% in men; 9.6% in women) and 10.2% (18.4% in men; 3.8% in women) for HU-7/7. The main factors associated independently with HU for both genders were low estimated glomerular filtration rate, hypertension, hypertriglyceridaemia, and alcoholism, regardless of the criteria chosen, as well as albuminuria in women and central obesity in men. Conclusions: The prevalence rates of HU increase linearly with age for both genders. The associations of CKM factors with HU diagnosed according to physiochemical criterion are more similar between men and women than those using epidemiological criteria.

Central Lean Mass Distribution and the Risks of All-Cause and Cause-Specific Mortality in 40,283 UK Biobank Participants

INTRODUCTION

The purpose of this study was to investigate the association of central lean mass distribution with the risk of mortality.

METHODS

This cohort study included 40,283 UK Biobank participants. Cox proportional hazards regression models were used to estimate the association of central lean mass distribution, i.e., trunk-to-leg lean mass ratio, assessed by dual-energy X-ray absorptiometry, with the risk of mortality.

RESULTS

The median age of the participants was 65 years, and 52% were women. During a median follow-up of 4.18 years, 674 participants died, of whom 366 were due to cancer and 126 were due to cardiovascular causes. Compared with the lowest tertile of a trunk-to-leg lean mass ratio, the multivariable-adjusted (age, sex, ethnicity, lifestyle, comorbidities, body mass index, and appendicular muscle mass index) hazards ratios of the highest tertile of trunk-to-leg lean mass ratio were 1.55 (95% CI: 1.23-1.94), 1.69 (95% CI: 1.26-2.26), and 1.14 (95% CI: 0.72-1.80) for all-cause, cancer, and cardiovascular mortality, respectively. Neutrophil-to-lymphocyte ratio mediated 9.3% (95% CI: 3.3%-40.4%) of the association of trunk-to-leg lean mass ratio with all-cause mortality. There was evidence for additive interactions of trunk-to-leg lean mass ratio with older age and poor diet quality for all-cause mortality.

CONCLUSION

Trunk-to-leg lean mass ratio, assessed by dual-energy X-ray absorptiometry, was positively associated with the risks of all-cause and cancer mortality, independent of general obesity and central obesity, in UK middle-aged and older adults. Central lean mass distribution may interact synergistically with aging and poor diet quality to further increase the risk of death.

Is systemic inflammation a missing link between cardiometabolic index with mortality? Evidence from a large population-based study

BACKGROUND

This study sought to elucidate the associations of cardiometabolic index (CMI), as a metabolism-related index, with all-cause and cardiovascular mortality among the older population. Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we further explored the potential mediating effect of inflammation within these associations.

METHODS

A cohort of 3029 participants aged over 65 years old, spanning six NHANES cycles from 2005 to 2016, was enrolled and assessed. The primary endpoints of the study included all-cause mortality and cardiovascular mortality utilizing data from National Center for Health Statistics (NCHS). Cox regression model and subgroup analysis were conducted to assess the associations of CMI with all-cause and cardiovascular mortality. The mediating effect of inflammation-related indicators including leukocyte, neutrophil, lymphocyte, systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR) were evaluated to investigate the potential mechanism of the associations between CMI and mortality through mediation package in R 4.2.2.

RESULTS

The mean CMI among the enrolled participants was 0.74±0.66, with an average age of 73.28±5.50 years. After an average follow-up period of 89.20 months, there were 1,015 instances of all-cause deaths and 348 cardiovascular deaths documented. In the multivariable-adjusted model, CMI was positively related to all-cause mortality (Hazard Ratio (HR)=1.11, 95% CI=1.01-1.21). Mediation analysis indicated that leukocytes and neutrophils mediated 6.6% and 13.9% of the association of CMI with all-cause mortality.

CONCLUSION

Elevated CMI is positively associated with all-cause mortality in the older adults. The association appeared to be partially mediated through inflammatory pathways, indicating that CMI may serve as a valuable indicator for poor prognosis among the older population.

Associations of diabesity with all-cause and cardiovascular disease mortality: Findings from the Mexico City Prospective Study

AIM

To investigate the joint associations of diabetes and obesity with all-cause and cardiovascular disease (CVD) mortality in the Mexico City Prospective Study.

MATERIALS AND METHODS

In total, 154 128 participants (67.2% women) were included in this prospective analysis. Diabetes was self-reported, while body mass index was used to calculate obesity. Using diabetes and obesity classifications, six groups were created: (a) normal (no diabetes and normal weight); (b) normal weight and diabetes; (c) overweight but not diabetes (overweight); (d) overweight and diabetes (prediabesity); (e) obesity but not diabetes (obesity); and (f) obesity and diabetes (diabesity). Associations between these categories and outcomes were investigated using Cox proportional hazard models adjusted for confounder factors.

RESULTS

During 18.3 years of follow-up, 27 197 (17.6%) participants died (28.5% because of CV causes). In the maximally adjusted model, participants those with the highest risk {hazard ratio (HR): 2.37 [95% confidence interval (CI): 2.24-2.51]}, followed by those with diabesity [HR: 2.04 (95% CI: 1.94-2.15)]. Similar trends of associations were observed for CVD mortality. The highest CV mortality risk was observed in individuals with diabesity [HR: 1.80 (95% CI: 1.63-1.99)], followed by normal weight and diabetic individuals [HR: 1.78 (95% CI: 1.60-1.98)].

CONCLUSION

This large prospective study identified that diabetes was the main driver of all-cause and CVD mortality in all the categories studied, with diabesity being the riskiest. Given the high prevalence of both conditions in Mexico, our results reinforce the importance of initiating prevention strategies from an early age.

Resveratrol Effects on Metabolic Syndrome Features: A Systematic Review and Meta-Analysis

Resveratrol is a natural polyphenol with important anti-inflammatory and antioxidant properties for treating cardiometabolic disorders. Therefore, the present meta-analysis aimed to review and investigate the oral resveratrol supplementation effects on metabolic syndrome (MetS) components. The bibliographic search was carried out in 2023 in the following databases: PubMed, Web of Science, and Scopus. Studies that investigated the oral resveratrol effects on the MetS parameters were included. Statistical analyses were performed using RevMan Software V.5.3. The main findings showed that resveratrol significantly decreased systolic and diastolic blood pressure while having no significant effects on waist circumference and high-density lipoprotein levels. In addition, glucose level was significantly decreased in the subgroup of studies reporting change from baseline means, although the overall effect was not statistically significant (p = 0.81), while triglyceride levels were increased after the treatment period. In conclusion, the present meta-analysis evidenced the potential therapeutic effect of resveratrol on improving some MetS features, especially regarding systolic blood pressure, diastolic blood pressure, and glucose reduction; however, the results are still borderline and sometimes controversial, which might be justified by the methodological and statistical heterogeneity of the studies, with the latter varying from 17 to 57%.

Explainable machine learning using echocardiography to improve risk prediction in patients with chronic coronary syndrome

Aims

The European Society of Cardiology guidelines recommend risk stratification with limited clinical parameters such as left ventricular (LV) function in patients with chronic coronary syndrome (CCS). Machine learning (ML) methods enable an analysis of complex datasets including transthoracic echocardiography (TTE) studies. We aimed to evaluate the accuracy of ML using clinical and TTE data to predict all-cause 5-year mortality in patients with CCS and to compare its performance with traditional risk stratification scores.

Methods and results

Data of consecutive patients with CCS were retrospectively collected if they attended the outpatient clinic of Amsterdam UMC location AMC between 2015 and 2017 and had a TTE assessment of the LV function. An eXtreme Gradient Boosting (XGBoost) model was trained to predict all-cause 5-year mortality. The performance of this ML model was evaluated using data from the Amsterdam UMC location VUmc and compared with the reference standard of traditional risk scores. A total of 1253 patients (775 training set and 478 testing set) were included, of which 176 patients (105 training set and 71 testing set) died during the 5-year follow-up period. The ML model demonstrated a superior performance [area under the receiver operating characteristic curve (AUC) 0.79] compared with traditional risk stratification tools (AUC 0.62-0.76) and showed good external performance. The most important TTE risk predictors included in the ML model were LV dysfunction and significant tricuspid regurgitation.

Conclusion

This study demonstrates that an explainable ML model using TTE and clinical data can accurately identify high-risk CCS patients, with a prognostic value superior to traditional risk scores.