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.

Hyperuricemia (HUA), a key risk factor for gout and cardiometabolic diseases, is underdiagnosed in elderly populations due to limited serum uric acid (SUA) testing in routine blood panels. Identifying noninvasive obesity-related indices for HUA could enhance early risk stratification, particularly in resource-constrained settings. This study evaluates the correlation and predictive performance of 6 obesity indices for HUA in Chinese elderly adults. A cross-sectional analysis of 8362 adults aged ≥ 65 years was conducted using 2021 health examination data from Guangdong, China. Multivariable logistic regression evaluated associations between obesity indices - Body Mass Index (BMI), Waist-to-Height Ratio (WHtR), Body Roundness Index (BRI), Weight-Adjusted-Waist Index (WWI), A Body Shape Index (ABSI), and Cardiometabolic Index (CMI) - and HUA. Receiver Operating Characteristic (ROC) curves with DeLong's test compared differences in Area Under the Curve (AUC). HUA prevalence was 48.62%, higher in females (53.07%) than males (43.20%). Adjusted for confounders, all indices showed significant associations: BMI (OR = 1.106, 95% CI = 1.090-1.121), WHtR (OR = 1.056 per 0.01-unit, 95% CI = 1.047-1.064), BRI (OR = 1.204, 95% CI = 1.173-1.236), WWI (OR = 1.185, 95% CI = 1.120-1.253), ABSI (OR = 1.083 per 0.01-unit, 95% CI = 1.002-1.171), and CMI (OR = 1.606, 95% CI = 1.488-1.735). CMI demonstrated the highest AUC (0.645, 95% CI = 0.633-0.656), significantly outperforming BMI, WHtR, BRI, WWI, and ABSI (DeLong's P < .001). WHtR (AUC = 0.621, 95% CI = 0.609-0.633) and BRI (AUC = 0.619, 95% CI = 0.608-0.631) showed comparable performance (P = .386). While CMI had superior predictive accuracy, its reliance on blood lipids limits practicality for routine screening. WHtR and BRI - requiring only waist circumference and height - offer optimal balance between performance and clinical feasibility, especially in primary care settings lacking laboratory infrastructure. These noninvasive tools could complement SUA testing to improve HUA risk assessment in elderly populations.

Colon cancer is one of the most prevalent malignancies globally. Anthropometric data are widely accessible. However, numerous anthropometric indicators exist, and no study has identified the most reliable predictor for colon cancer. This study aims to identify the most effective anthropometric indicators for predicting colon cancer.

Significant differences were observed in age, race, smoking, diabetes, hypertension, waist circumference, a body shape index (ABSI), Body Roundness Index (BRI), Conicity Index (ConI), Waist-to-Height Ratio(WHtR), and Weight-adjusted Waist Index(WWI) between colon cancer patients and controls (P < 0.05). ABSI (AUC: 0.68, 95% CI: 0.64-0.71), ConI (AUC: 0.68, 95% CI: 0.64-0.71), and WWI (AUC: 0.67, 95% CI: 0.63-0.70) were the most accurate anthropometric indices for predicting colon cancer. ABSI, ConI, and WWI demonstrated a strong correlation.

Analysis of NHANES data (2005-2018) identified ABSI, ConI, and WWI (AUC:0.67-0.68) as optimal anthropometric predictors of colon cancer, emphasizing abdominal obesity's clinical relevance. These cost-effective indices could enhance early screening in resource-limited settings.

Previous studies have suggested an intimate association between obesity and psoriasis. This study aimed to evaluate and compare the association between traditional and novel obesity biomarkers - waist circumference (WC), body mass index (BMI), a body shape index (ABSI), and body roundness index (BRI) - and the risk of psoriasis.

This cross-sectional study utilized data from the 2003-2006 and 2011-2014 National Health and Nutrition Examination Survey. The association between obesity biomarkers and psoriasis risk was evaluated using multivariate logistic regression and smoothed curve fitting. The diagnostic performance of various biomarkers for identifying psoriasis were calculated and compared using receiver-operating characteristic curves.

Overall, 12,406 participants without psoriasis, 287 with mild psoriasis, and 68 with moderate-severe psoriasis, were included. Compared to the lowest quartile of WC, BMI, and BRI, higher quartiles were associated with significantly higher risks of psoriasis (all P for trend < 0.05). The area under the curve for identifying psoriasis was highest for BRI, which was comparable to WC (0.581 vs 0.575, P=0.34) but significantly higher than that of ABSI (0.581 vs 0.546, P=0.04) and BMI (0.581 vs 0.569, P=0.007). The association between BRI and psoriasis risk was not influenced by participant's age, sex, smoking status, physical activity, hypertension and diabetes status.

BRI is positively associated with risk of psoriasis and outperforms BMI and ABSI in identifying psoriasis. Given the cross-sectional design of this study, future research employing prospectively designed longitudinal studies is necessary to validate our findings.

Hormonal and age-related differences in body composition require tailored approaches for predicting new-onset type 2 diabetes (NODM). Previous studies lacked in-depth stratified analyses. We investigate sex- and age-specific body composition indices associated with NODM.

A retrospective, nationwide, population-based cohort study.

We analysed 4 058 891 adults who underwent a health examination in the year 2009 and 10-year follow-up data from the National Health Insurance Service.

NODM risk stratified by sex and age groups in 20-year intervals according to quartiles or per 1 SD increase in body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI) and weight-adjusted waist index (WWI).

Among the total subjects, 625 715 individuals (15.4%) developed NODM during median 10-year follow-up. The fourth quartile of WHtR showed the highest HR for NODM compared with the first quartile among various indices across the entire population (HR 2.54, 95% CI 2.52 to 2.57). In men, WHtR consistently exhibited the strongest association with NODM across all age groups in analysis based on 1 SD increase; ages 20-39 years (HR 1.54, 95% CI 1.53 to 1.55), ages 40-59 years (HR 1.39, 95% CI 1.38 to 1.39), ages 60-79 years (HR 1.23, 95% CI 1.22 to 1.24). In women, the most relevant body composition index for NODM varied by age group; BMI for ages 20-39 years (HR 1.48, 95%CI 1.47 to 1.49), WHtR for ages 40-59 years (HR 1.46, 95% CI 1.45 to 1.47) and WC for ages 60-79 years (HR 1.23, 95%CI 1.22 to 1.24).

WHtR was the strongest predictor of NODM in men across all ages, while the relevant indices varied by age group in women. These findings highlight the need for sex- and age-specific body composition assessments in predicting NODM risk.

The association of novel anthropometrics and novel atherogenicity indices with mortality remains uncertain.

To compare the association of novel anthropometrics and atherogenicity indices with all-cause, cardiovascular (CVD), and non-CVD mortality in Iranian adults.

Utilizing data from Isfahan Cohort Study, 5432 participants aged older than 35 years were enrolled. Three anthropometrics indices including a body shape index (ABSI), body roundness index (BRI) and abdominal volume index (AVI), and three atherogenicity indices including atherogenic index of plasma (AIP), Castelli risk index (CRI) and the cholesterol index (CI) were calculated. Cox proportional hazards regression models were used to explore the association between indices and mortality.

After a median follow-up of 11.25 years, the ABSI was independently associated with increased risk of all-cause mortality (HRQ4 vs. Q1 = 1.43, 95 % CI: 1.07, 1.92; P trend = 0.02). A positive, independent association was also observed between CRI-II (HRQ4 vs. Q1 = 1.49, 95 % CI: 0.99, 2.25; P trend = 0.04) and AIP (HRQ4 vs. Q1 = 1.81, 95 % CI: 1.92, 2.27; P trend = 0.01) and CVD mortality. For non-CVD mortality, despite a direct link for ABSI (HRQ4 vs. Q1 = 1.92, 95 % CI: 1.32, 2.80; P trend = 0.001), an inverse association was found for CI (HRQ4 vs. Q1 = 0.68, 95 % CI: 0.49, 0.95; P trend = 0.007).

Amongst various investigated anthropometric indices, ABSI was directly related to all-cause and non-CVD mortality. However, atherogenicity indices including CRI-II and AIP could predict the incidence risk of CVD mortality among Iranians. Further studies are warranted to confirm these findings.

Waist circumference (WC), an abdominal obesity index in the current metabolic syndrome (MetS) criteria, may not adequately reflect visceral fat accumulation. This brief review aims to examine the clinical significance of utilizing a body shape index (ABSI), a novel abdominal obesity index, to modify the MetS criteria, considering the predictive ability for vascular dysfunction indicated by the cardio-ankle vascular index (CAVI), as well as kidney function decline. First, the relationship of CAVI with kidney function is presented. Next, whether modification of the MetS diagnostic criteria by replacing the current high waist circumference (WC-MetS) with high ABSI (ABSI-MetS) improves the predictive ability for vascular and kidney dysfunction is discussed. Although limited to Asian populations, several cross-sectional and longitudinal studies support the relationship of CAVI with kidney function. Increased CAVI is associated with kidney function decline, and the CAVI cutoff for kidney outcomes is considered to be 8-9. In urban residents who underwent health screening, an increase in ABSI, but not body mass index (BMI) or WC, was associated with increased CAVI, suggesting that ABSI reflects vasoinjurious body composition. In several cross-sectional studies, ABSI-MetS was superior to WC-MetS in identifying individuals with increased CAVI. Furthermore, the predictive ability of ABSI-MetS in assessing kidney function decline was enhanced only in individuals with MetS, as determined in a longitudinal analysis. Using WC as a major criterion for MetS diagnosis may not adequately identify individuals at risk of vascular dysfunction and kidney function decline. This review shows that this problem may be solved by replacing WC with ABSI. Future research should explore whether ABSI-MetS also predicts cardiovascular events, and whether therapeutic intervention that reduces ABSI improves clinical outcomes.

Cumulative evidence consistently shows that anthropometric and body composition measurements are strongly linked to the risk of incident diabetes, typically based on baseline measurements. This study aims to assess whether repeated measurements enhance the prediction of diabetes risk beyond baseline assessments alone.

We utilized data from a 16-year population-based follow-up cohort within the Korean Genome and Epidemiology Study, comprising 6,030 individuals aged 40 to 69 years at baseline. We included eight indices: a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), weight-adjusted skeletal muscle index (SMI), percent body fat, and fat-to-muscle ratio. The effect of these measurements for incident diabetes was estimated using Harrell's C-indexes and hazard ratios with 95% confidence intervals, employing time-dependent Cox proportional hazard models.

Over the 16-year follow-up, 939 new diabetes cases were identified (cumulative incidence, 15.6%). The median number of indicator measurements per participant was eight. The basic model, including 10 features (sex, age, education levels, physical activity, alcohol intake, current smoking, total energy intake, dietary diversity score, and log-transformed C-reactive protein levels, and quartiles of unweighted genetic risk score at baseline), yielded a Harrell's C-index of 0.610. The highest C-index in repeated measurements was for WC (0.668) across the general population, weight-adjusted SMI in men, and WHR in women. However, except for ABSI and BAI, the diabetes predictive power of the other indicators was comparable. Additionally, repeated measurements of WC, BMI, and WHR in women were found to contribute to improved discrimination compared to baseline measurements, but not in men.

Utilizing repeated measurements of general and central adiposity to predict diabetes may be helpful in predicting hidden risks, especially in women.

Previous studies have emphasized the independent effects of anthropometric indices-including body mass index (BMI), A Body Shape Index (ABSI), waist-to-height ratio (WHtR), body roundness index (BRI), and Conicity Index-on mortality. However, their combined impact, especially in diabetic populations with distinct obesity patterns, has been less frequently explored. This study investigates both the independent and combined effects of these anthropometric indices on mortality in diabetic Americans and compares their individual and combined diagnostic value.

A nationally representative cohort study was conducted using NHANES data (2005-2018), including 6,572 diabetic adults. Weighted Cox proportional hazards models and restricted cubic splines were applied to evaluate the independent and combined associations of anthropometric indices (BMI, ABSI, WHtR, BRI, and Conicity Index) with all-cause mortality. The weighted receiver operating characteristic (ROC) curve was used to assess the diagnostic value of individual anthropometric indices and their combinations in predicting mortality.

Among all the anthropometric indices, ABSI exhibited the strongest independent association with all-cause mortality, outperforming other measures such as BMI, WHtR, BRI, and Conicity Index. A clear linear relationship was identified, with higher ABSI tertiles consistently linked to an increased risk of mortality. Notably, within each BMI tertile, ABSI effectively differentiated mortality risk, particularly in the highest tertile. Furthermore, ABSI demonstrated the highest predictive performance among individual metrics (weighted AUC = 0.653) and showed further improvement when combined with BMI (weighted AUC = 0.669).

BMI and ABSI collectively provide a comprehensive evaluation of mortality risk in diabetic populations, capturing the synergistic effects of general and central obesity. These findings highlight the importance of integrating BMI and ABSI into risk assessments to identify high-risk individuals and guide targeted interventions for reducing mortality.

Obesity is associated with a high risk of diabetes mellitus (DM); therefore, obesity-related indices are strongly associated with DM. This study evaluated the association of obesity indices, including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and a body shape index (ABSI), with DM in Korean middle-aged and older adults.

Data from three population-based cohorts (Ansan and Ansung, Health Examinee, and Cardiovascular Disease Association Study, derived from the Korean Genome and Epidemiology Study) were analyzed. Logistic analysis was used to evaluate the association of BMI, WC, WHR, and ABSI with DM, after adjusting for covariates according to sex and age. The integrated discrimination index (IDI) and category-free net reclassification improvement (cfNRI) and area under the curve (AUC) of the receiver operating characteristic (ROC) curve were analyzed by age group to investigate index-specific model performance.

Among the 160,585 participants, 13,846 had DM (6,837; men [11.86%] and 7,009 women [6.81%]). Age increase was associated with an increased prevalence of DM: 2,339 (4.01%), 5,313 (8.74%), and 6,194 (14.93%) in the 40-49, 50-59, and ≥ 60 years age groups. After adjusting for covariates, the odds ratios (OR) for DM of WHR and WC were higher than those of the other indices in every age group. However, the OR for WHR, WC, and BMI decreased with age in both sexes. ABSI showed steady and slightly increasing ORs with increasing age although the ORs in both sexes were generally low for DM. For IDI and cfNRI, WHR had the highest values among all age groups. The AUC of the ROC curve showed that the WHR had the highest value in all age groups.

The WHR had the strongest association with DM, but was not a good DM index in older people. Therefore, age-related index criteria for DM, especially in women, were needed for the effective prevention and management of DM.

To provide an overview of the predictive value of A Body Shape Index (ABSI) for the risk of cardiovascular events.

ABSI has been reported to have an association with development of cardiovascular diseases, and its usefulness for predicting major cardiovascular events including cardiovascular mortality, nonfatal coronary syndrome and nonfatal stroke has been investigated. The formula for ABSI includes waist circumference, which is not included in the conventional calculation of body mass index (BMI), along with BMI and height. High ABSI is independently associated with a high incidence of cardiovascular events. ABSI with specific cutoff values can be a useful tool for cardiovascular risk stratification by detecting the presence of abdominal obesity and it can be used for evaluation of the risk of cardiovascular events. Nonetheless, other factors such as race, gender, age, and physical, environmental and socioeconomic purviews also need be taken into consideration.

Colorectal cancer (CRC) is linked to obesity, particularly visceral fat. A more accurate measure of visceral fat accumulation is offered by a body shape index (ABSI). Currently, the direct application of the ABSI to populations with varying ethnic backgrounds might be restricted. Moreover, there is less evidence about the correlation between ABSI and CRC among individuals from different ethnical backgrounds.

A total of 40,998 individuals who took part in the National Health and Nutrition Examination Survey (NHANES) spanning from 2003 to 2023 were subjected to analysis. Logistic regression was utilized to examine the associations between the ABSI and the risk of CRC. In addition, restricted cubic spline curves (RCS) were utilized, and subgroup analyses along with interaction tests were also carried out. The receiver operating characteristic curve (ROC) was employed to predict the risk of CRC relying on various anthropometric indicators.

After adjusting for covariates, ABSI demonstrated a positive association with the incidence of CRC (OR = 1.03 [95% CI: 1.01-1.05], p = 0.018). Individuals in the upper quartile of ABSI exhibited a greater prevalence of CRC than those in the lower quartile (OR = 1.88 [95% CI: 1.19-2.96], p = 0.006). RCS analysis indicated a nonlinear correlation between ABSI and CRC (P for nonlinear = 0.030). Subgroup analysis indicated a notable interaction between age and BMI subgroups (interaction p < 0.05), and ROC curves indicated that the ABSI was effective in predicting CRC risk (AUC = 0.658), demonstrating good sensitivity, particularly in individuals under 60 years of age.

A positive correlation exists between ABSI levels and the increased incidence of CRC among U.S. adults. This is especially true for people under 60 years of age (40-60 years), with a BMI below 25 kg/m2, and those with a BMI of 30 kg/m2 or beyond. ABSI can be used as a simple anthropometric predictor of CRC.

Women with previous hypertensive disorders of pregnancy (HDP) have increased risk of cardiovascular disease (CVD). Overweight is a modifiable risk factor for both conditions. Anthropometric indices such as waist circumference, hip circumference, waist-to-hip ratio, estimated total body fat, a body shape index, waist-to-hip-to-height ratio, and index of central obesity improve estimation of cardiovascular death risk in the general population as compared to body mass index (BMI).

We aimed to assess whether alternative body mass composition indices associate more strongly with postpartum blood lipid levels, as a proxy for CVD risk, than BMI. We also aimed to investigate whether associations differ between women with previous normotensive or hypertensive index pregnancies.

In this cross-sectional study, we examined 296 women 1 or 3 years after an index pregnancy that was normotensive (n = 116) or complicated by a hypertensive pregnancy disorder, including preeclampsia (n = 133) or gestational hypertension (n = 47).

Uni- and multivariable regression analyses, adjusted for age and smoking, were conducted to evaluate associations between postpartum body mass composition indices and blood lipids. p < 0.05 was considered statistically significant.

Median BMI and overweight rates were higher in women with previous HDP than in controls (23.9 kg/m2 versus 22.8 kg/m2 and 44.4% versus 30.2%, both p ⩽ 0.03). No body mass composition indices in any pregnancy complication group showed stronger associations with adverse lipid levels than BMI. However, women with previous HDP more often displayed significant associations between adverse body mass composition indices and adverse lipid levels, compared with controls.

Alternative anthropometric measurements are not better suited to evaluate circulating lipids as proxy for CVD risk after HDP, compared to BMI. We hence recommend using BMI in CVD risk assessment after HDP due to its current widespread use and feasibility.

Compared to the general population of Hawai'i, Native Hawaiians and Other Pacific Islanders (NHPI) shoulder a disproportionately high risk for obesity-related cardiometabolic disorders, such as type 2 diabetes and cardiovascular disease. The gut microbiome is an area of rapid research interest for its role in regulating adjacent metabolic pathways, offering novel opportunities to better understand the etiology of these health disparities. Obesity and the gut microbiome are influenced by regional, racial-ethnic, and community-specific factors, limiting the generalizability of current literature for understudied populations. Additionally, anthropometric and directly measured obesity indices are variably predictive of adiposity and metabolic health risk in this diverse population. Thus, further NHPI-inclusive research is required to adequately characterize community-specific factors in the context of obesity-related disease etiology. Culturally responsible research ethics and scientific communication are crucial to conducting such research, especially among indigenous and understudied populations. In this review, we explore these limitations in current literature, emphasizing the urgent need for NHPI-inclusive research to assess community-specific factors accurately. Such accuracy in Indigenous health research may ensure that findings relevant to individual or public health recommendations and/or policies are meaningful to the communities such research aims to serve.

Nocturia, marked by frequent nighttime urination, significantly impacts quality of life. This study explores the association of METS-IR (Metabolic Score for Insulin Resistance) and ABSI (A Body Shape Index) with nocturia, using data from the National Health and Nutrition Examination Survey (NHANES). A cross-sectional analysis of NHANES data from 2005 to 2020 was performed. Multivariable logistic regression assessed the associations between METS-IR, ABSI, and nocturia, adjusting for demographic characteristics, chronic diseases, and lifestyle factors. Generalized additive models and smoothing splines were used to describe relationship dynamics. Among the 16,450 participants, both METS-IR (OR = 1.15, 95% CI: 1.11-1.20, p < 0.0001) and ABSI (OR = 1.14, 95% CI: 1.10-1.19, p < 0.0001) were significantly associated with nocturia based on z-scores. An incremental rise in the quartiles of METS-IR and ABSI was associated with a higher risk of nocturia. Specifically, compared to the lowest quartile (Q1), participants in the highest quartile (Q4) had an OR of 1.45 (95% CI: 1.30-1.61, p < 0.0001) for METS-IR and 1.38 (95% CI: 1.23-1.55, p < 0.0001) for ABSI. Subgroup analyses showed a stronger association between ABSI and nocturia among individuals living alone and those aged 20-38 years. Nonlinear modeling indicated a threshold effect for ABSI, with nocturia risk significantly increasing when ABSI exceeded 76.2. Higher METS-IR and ABSI indices are closely linked to a greater prevalence of nocturia, indicating that these indices can be valuable in clinical assessments for evaluating nocturia risk and supporting preventive strategies.

A Body Shape Index (ABSI) has been reported to have associations with cardiovascular risk factors. However, there is no information on the association between ABSI and incidence of cardiovascular events.

We investigated the associations between ABSI and first major cardiovascular events (death from cardiovascular disease, nonfatal acute coronary syndrome, and nonfatal stroke) in 1857 subjects from the database of Flow-Mediated Dilation Japan registry and from Hiroshima University Vascular Function registry.

The areas under the curves of ABSI to predict the first major cardiovascular events were superior to BMI (men: P = .032, women: P = .015) and waist circumference in women (men: P = .078, women: P = .002). The subjects were divided into 2 groups based on the cutoff value of ABSI for predicting first major cardiovascular events: a low ABSI group (<0.0822 in men and <0.0814 in women) and a high ABSI group (≥0.0822 in men and ≥0.0814 in women). During a median follow-up period of 41.6 months, 56 subjects died (23 from cardiovascular causes), 16 had nonfatal acute coronary syndrome, and 14 had nonfatal stroke. The Kaplan-Meier curves for first major cardiovascular events were significantly different between the 2 groups (men, P < .001; women, P < .001). Multivariate analysis revealed that high ABSI remained an independent predictor of first major cardiovascular events (men: hazard ratio, 2.33; 95% CI, 1.07 to 5.06; P = .033; women: hazard ratio, 8.33; 95% CI, 1.06 to 65.49; P = .044).

High ABSI is independently associated with incidence of cardiovascular events. ABSI calculation should be performed for evaluation of risk of cardiovascular events.

The association between body shape and depressive symptoms has been reported in adults. The present study aimed to investigate the association between body shape-specific abdominal obesity and depressive symptoms among multi-regional Asian adults.

The 2011-2012 China Health and Retirement Longitudinal Study and 2022-2023 Hangzhou study were used as the discovery and validation datasets, respectively. Body shape was assessed by body mass index categories. Abdominal obesity was defined as a body shape index (ABSI) ≥ 75th centile. Depression was measured using 10-item Centre for Epidemiological Studies Depression Scale and Geriatric Depression Scale short 15-item version, respectively. General linear and multinomial logistic models were used to explore the association of ABSI, abdominal obesity with depressive scores and presence, respectively.

A total of 12,229 and 1210 participants were included in the discovery and validation datasets, respectively. A non-linear reverse L-shaped association was found between ABSI and depressive scores. Participants with abdominal obesity had higher depressive scores (β = 0.05, 95%CI = 0.01-0.09; and β = 0.13, 95%CI = 0.01-0.24; respectively). Stratified analyses showed that abdominal obesity was associated with higher depressive scores (β = 0.09, 95%CI = 0.00-0.17; and β = 0.25, 95%CI = 0.05-0.46; respectively) and presence (OR = 1.46, 95%CI = 1.02-2.10; and OR = 3.95, 95%CI = 1.58-9.84; respectively) in overweight adults. Furthermore, abdominal obesity was associated with depressive symptoms among overweight females, but not among males.

Causal links weren't addressed because of the observational study design.

Abdominal obesity exhibited a positive association with depressive symptoms among Asian overweight adults, particularly in females. Prevention and early diagnosis of depressive symptoms should focus on overweight females.

This study aimed to compare the diagnostic accuracy of four indicators, including waist-to-height ratio (WHTR), vascular adiposity index (VAI), TG/HDL-C, and BMI/HDL-C for metabolic syndrome (MS) in Chinese adults aged 40 years and above. Additionally, the study aimed to develop an efficient diagnostic model displayed by a nomogram based on individual's BMI and circulating HDL-C level.

A cross-sectional study was conducted on 699 participants aged 40 years and above. Quartiles of BMI/HDL-C, TG/HDL-C, VAI, and WHTR were used as independent variables, and metabolic syndrome was used as the dependent variable. Logistic regression was conducted to explore the impact of each parameter on the risk of MS. The areas under the receiver operating characteristics were compared to determine the accuracy of the indicators in diagnosing MS in the participants. Logistic regression was run to construct the nomograms, and the performance of the nomogram was assessed by a calibration curve.

MS subjects had higher levels of BMI, BFM, PBF, VFA, AMC, WC, SCR, TG, and insulin, but lower LDH and HDL-C levels than the subjects without MS. The BMI/HDL-C ratio was positively correlated with the prevalence of MS and its components. The final diagnostic model included five variables: gender, BFM, WC, TG, and BMI/HDL-C. The model showed good calibration and discrimination power with an AUC of 0.780. The cut-off value for the nomogram was 0.623 for diagnosing MS.

BMI/HDL-C ratio was an independent risk factor for MS in Chinese adults. BMI/HDL-C was significantly correlated with MS and its components. BMI/HDL-C was the most powerful diagnostic indicator compared to other indicators, including TG/HDL-C, VAI and WHTR for diagnosing MS. The nomogram drawn based on the diagnostic model provided a practical tool for diagnosing MS in Chinese adults.

This study aims to demonstrate that demographics combined with biometrics can be used to predict obesity related chronic disease risk and produce a health risk score that outperforms body mass index (BMI)-the most commonly used biomarker for obesity. We propose training an ensemble of small neural networks to fuse demographics and biometrics inputs. The categorical outputs of the networks are then turned into a multi-dimensional risk map, which associates diverse inputs with stratified, output health risk. Our ensemble model is optimized and validated on disjoint subsets of nationally representative data (N~100,000) from the National Health and Nutrition Examination Survey (NHANES). To broaden applicability of the proposed method, we consider only non-invasive inputs that can be easily measured through modern devices. Our results show that: (a) neural networks can predict individual conditions (e.g., diabetes, hypertension) or the union of multiple (e.g., nine) health conditions; (b) Softmax model outputs can be used to stratify individual- or any-condition risk; (c) ensembles of neural networks improve generalizability; (d) multiple-input models outperform BMI (e.g., 75.1% area under the receiver operator curve for eight-input, any-condition models compared to 64.2% for BMI); (e) small neural networks are as effective as larger ones for the inference tasks considered; the proposed models are small enough that they can be expressed as human-readable equations, and they can be adapted to clinical settings to identify high-risk, undiagnosed populations.

A body Shape index (ABSI), defined as waist circumference (WC)/(body mass index (BMI)2/3 × height1/2), is unique in that the ABSI is positively associated with visceral obesity and is independent of BMI. The ABSI has also been shown to be positively and linearly correlated with the amount of visceral adiposity in the general population and with all-cause and cardiovascular disease (CVD). However, it is uncertain whether ABSI is associated with periodontitis in hypertensive patients. A cross-sectional study of 2,482 hypertensive patients (mean age 65.2 ± 9.1 years) was conducted using the ABSI Z score, periodontitis as a dichotomous variable, the ABSI Z score as a continuous variable, and multiple covariates such as age, gender, and race. The data were analyzed using descriptive statistics, multiple regression model, subgroup analysis with EmpowerStats (version 4.2), and curve transformation plots were generated. In multiple regression model analysis, ABSI Z score showed a significant positive association with periodontitis in the hypertensive population in all three models. When ABSI Z score was divided into low, moderate, and high three groups, we observed that those with the highest ABSI Z score had a 20% increased risk of periodontitis among people with hypertension (OR 1.2; 95% CI 1.0, 1.5; p = 0.046). We used smooth curve fitting to confirm the results and found that these results were still supported, and additional subgroup analyses showed that the positive association between ABSI Z score and periodontitis in hypertensive population was stable and consistent in the general population. The present cross-sectional investigation showed a positive association between ABSI Z score and periodontitis in a hypertensive population.

The distribution of body fat and metabolic health may contribute to the onset of metabolic syndrome (MetS), but the associations between body fat anthropometric indices (AIs) and mortality in individuals with MetS remain unclear.

Participants aged 18 years or older with MetS were recruited from the NHANES 1999-2018. The body fat anthropometric indices included the a body shape index (ABSI), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), waist triglyceride index (WTI), lipid accumulation product (LAP), atherogenic index of plasma (AIP), and triglyceride‒glucose (TyG) index. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII) criteria. Mortality data were obtained from the National Death Index through December 31, 2019.

Data were collected from 8,379 individuals with MetS, with a median follow-up of 8.5 years, of whom 1,698 died from all causes and 568 from the CCD. The random survival forest (RSF) analysis indicated that the ABSI had the strongest predictive power for both all-cause mortality and CCD mortality among the eight body fat AIs. After adjusting for multiple variables, the ABSI was found to be linearly and positively associated with all-cause and CCD mortality in individuals with MetS. Participants in the highest quartile of ABSI had an increased risk of all-cause (HR = 1.773 [1.419-2.215]) and CCD (HR = 1.735 [1.267-2.375]) mortality compared with those in the lowest quartile. Furthermore, the ABSI predicted areas under the curve (AUCs) of 0.735, 0.723, 0.718, and 0.725 for all-cause mortality at 3, 5, 10, and 15 years, respectively, and 0.774, 0.758, 0.725, and 0.715 for CCD mortality, respectively.

Among eight body fat AIs, the ABSI exhibited the strongest predictive power for mortality in individuals with MetS. Higher ABSI values significantly increased all-cause mortality and CCD mortality in participants with MetS.

This research aimed to assess the correlation between the Adjusted Body Shape Index (ABSI) and the presence of abdominal aortic calcification (AAC) among middle-aged and older American adults.

Employing a cross-sectional design, this study analyzed data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES), focusing on 3077 participants aged 40 and above. AAC detection was conducted using dual-energy X-ray absorptiometry (DXA). ABSI was determined based on waist circumference (WC), weight, and height data. The association between ABSI and AAC was examined through multiple linear regression, smoothed curve analysis, threshold effect evaluation, subgroup analysis, and interaction testing.

The study encompassed 3077 individuals aged 40 and above. Findings indicated a noteworthy positive relationship between ABSI and AAC when adjusting various covariates. Analysis of threshold effects identified a K-point at 0.0908, showing no significant effect to its left but a significant effect to its right. Further, subgroup and interaction analyses highlighted the ABSI-AAC connection specifically within different age groups and among individuals with diabetes.

Higher ABSI was correlated with higher AAC score.

Sex disparity between metabolic-obesity (defined by body mass index, BMI) phenotypes and obesity-related cancer (ORC) remains unknown. Considering BMI reflecting overall obesity but not fat distribution, we aimed to systematically assess the association of our newly proposed metabolic-anthropometric phenotypes with risk of overall and site-specific ORC by sex.

A total of 141,579 men (mean age: 56.37 years, mean follow-up time: 12.04 years) and 131,047 women (mean age: 56.22 years, mean follow up time: 11.82 years) from the UK Biobank was included, and designated as metabolic-anthropometric phenotypes based on metabolic status (metabolically healthy/unhealthy), BMI (non-obesity/obesity) and body shape (pear/slim/apple/wide). The sex-specific association of different phenotypes with overall and site-specific ORC was assessed by hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression models.

We found metabolically unhealthy and/or obesity phenotypes conveyed a higher risk in men than in women for overall ORC and colorectal cancer compared with metabolically healthy non-obesity phenotype (Pinteraction < 0.05). Of note, metabolically healthy obesity phenotype contributed to increased risks of most ORC in men (HRs: 1.58 ~ 2.91), but only correlated with higher risks of endometrial (HR = 1.89, 95% CI: 1.54-2.32) and postmenopausal breast cancers (HR = 1.17, 95% CI: 1.05-1.31) in women. Similarly, even under metabolically healthy, men carrying apple and wide shapes phenotypes (metabolically healthy apple/wide and metabolically healthy non-obesity apple/wide) suffered an increased risk of ORC (mainly colorectal, liver, gastric cardia, and renal cancers, HRs: 1.20 ~ 3.81) in comparison with pear shape or non-obesity pear shape.

There was a significant sex disparity between metabolic-anthropometric phenotypes and ORC risk. We advised future ORC prevention and control worth taking body shape and sex disparity into account.

Fecal incontinence (FI) is highly prevalent with substantial impacts on quality of life and health care utilization. The impact of obesity on FI remains unclear, with differing conclusions using body mass index (BMI) as a risk factor. We aimed to determine the association between obesity and FI, and whether this relationship is dependent on the distribution of adiposity (waist circumference-to-height ratio [WHtR]).

This was a population-based analysis of the National Health and Nutrition Examination Survey, including participants who responded to the bowel health survey in 2005 to 2010. FI was defined by the accidental bowel leakage of solid stool, liquid, or mucus at least once in the past month. Stepwise multivariable logistic regression models were constructed to assess risk factors for FI.

A total of 7606 participants were included, with an overall FI prevalence of 9.2%. When stratified by quartiles of body measurements, FI was increasingly prevalent from the 1st to the 4th quartile for both WHtR (range, 5.3%-12.5%) and BMI (range, 7.1%-10.5%). WHtR was associated with FI and was a stronger predictor than BMI in all quartiles of body measurement. On multivariable analysis, WHtR remained a significant predictor of FI comparing the 4th with the 1st quartile of body measurements (odds ratio [OR], 1.77; 95% confidence interval [CI], 1.11-2.80; P = .017), whereas BMI was not. A WHtR cutoff of >0.592 optimized the Youden index in prediction of FI in the overall sample.

WHtR was independently associated with increased odds of FI in this nationally representative sample of United States adults, whereas BMI was not consistently correlated. This suggests bowel continence may depend more on how body mass is distributed.

Dietary diversity refers to the consumption of a variety of foods or food groups over a given reference period, which is crucial for improving nutrition and overall health. This longitudinal study aimed to investigate the association between dietary diversity and anthropometric indices in community-dwelling older adults living in Tehran in 2017 and 2021.

The current study was conducted on 368 older adults [204 (55.4%) women and 164 (44.6%) men] over 60 years of age living in Tehran, who were selected by a systematic cluster sampling method at two-time points, 2017 and 2021. Anthropometric measures (weight, height, hip circumference, and waist circumference) were assessed with standard methods. The participants' dietary intake was assessed by completing two non-consecutive 24-hour recalls, and dietary diversity score (DDS) was calculated based on Kant's method. Statistical analysis was performed using R software by the mixed effect model method.

The mean DDS of the participants in 2017 (5.07 ± 1.20) was higher than that in 2021 (4.94 ± 1.09) (p < 0.05). DDS and dairy diversity score decreased significantly over time. After adjusting for confounders, there was an inverse relationship between the DDS and Body Mass Index (BMI) (B = -0.22; SE = 0.09), but the interaction effect of year × DDS (B = 0.19; SE = 0.10) was not significant (p = 0.06). However, there was a positive relationship between the DDS and A Body Shape Index (ABSI) (B = 0.00; p = 0.022), after adjusting for confounders, this relationship was no longer significant. Additionally, the interaction effect of year and DDS on the ABSI was not significant.

The dietary intake and dietary diversity of older adult residents of Tehran declined dramatically with age, and a higher DDS was associated with improved anthropometric indices. DDS had an inverse relationship with general obesity in the studied participants, and the passage of time did not affect this relationship. The DDS can be used as a predictive index and is a powerful tool for investigating changes in nutritional status in longitudinal studies of old age. However, longer-duration studies are needed to obtain more conclusive results.

The allometric body shape index (ABSI) and hip index (HI), as well as multi-trait body shape phenotypes, have not yet been compared in their associations with inflammatory markers. The aim of this study was to examine the relationship between novel and traditional anthropometric indexes with inflammation using data from the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts.

Participants from EPIC (n = 17,943, 69.1% women) and UK Biobank (n = 426,223, 53.2% women) with data on anthropometric indexes and C-reactive protein (CRP) were included in this cross-sectional analysis. A subset of women in EPIC also had at least one measurement for interleukins, tumour necrosis factor alpha, interferon gamma, leptin, and adiponectin. Four distinct body shape phenotypes were derived by a principal component (PC) analysis on height, weight, body mass index (BMI), waist (WC) and hip circumferences (HC), and waist-to-hip ratio (WHR). PC1 described overall adiposity, PC2 tall with low WHR, PC3 tall and centrally obese, and PC4 high BMI and weight with low WC and HC, suggesting an athletic phenotype. ABSI, HI, waist-to-height ratio and waist-to-hip index (WHI) were also calculated. Linear regression models were carried out separately in EPIC and UK Biobank stratified by sex and adjusted for age, smoking status, education, and physical activity. Results were additionally combined in a random-effects meta-analysis.

Traditional anthropometric indexes, particularly BMI, WC, and weight were positively associated with CRP levels, in men and women. Body shape phenotypes also showed distinct associations with CRP. Specifically, PC2 showed inverse associations with CRP in EPIC and UK Biobank in both sexes, similarly to height. PC3 was inversely associated with CRP among women, whereas positive associations were observed among men.

Specific indexes of body size and body fat distribution showed differential associations with inflammation in adults. Notably, our results suggest that in women, height may mitigate the impact of a higher WC and HC on inflammation. This suggests that subtypes of adiposity exhibit substantial variation in their inflammatory potential, which may have implications for inflammation-related chronic diseases.

Background: This study evaluates insulin resistance prevalence in young females without diabetes, assessing risk factors and adiposity indices for early detection of cardiometabolic disorders. Methods: A cross-sectional study was conducted, involving 282 females aged 18-35 years from suburban and rural areas of Sri Lanka. Anthropometric measurements [height, weight, waist circumference (WC)] were obtained and biochemical parameters [fasting glucose, insulin, insulin resistance (IR), total cholesterol, high-density lipoproteins, (HDL), low-density lipoproteins, triglycerides] were measured. The anthropometric and biochemical data were compared between the groups of normal weight controls and overweight/obese cases, as well as between females with or without IR. Results: The prevalence of IR in controls and cases were 48.6% and 57.1%, respectively. Both groups had mean Homeostasis Model Assessment-IR values greater than the normal cutoff value of 2.5. Females with IR showed higher prevalence of dyslipidemia than those without IR. Compared to the controls (2.81%), the prevalence of metabolic syndrome (MetS) was substantially greater among cases (46.42%). Both groups showed a statistically significant association between IR and MetS, but the association was considerably stronger in cases [r = 0.616, odds ratio (OR) >8] than in controls (r = 0.175, OR >1). Controls exhibited lower HDL levels, hypertriglyceridemia, and elevated IR levels (P < 0.05), and their ORs for acquiring MetS were >2, <1, and >3, respectively. Importantly, overweight/obese cases exhibited a significant association (P < 0.05) with all the MetS risk variables. Visceral adiposity index (VAI) proves to be a precise measurement for identifying IR and cardiovascular disease (CVD) among young females (Z = -3.651), surpassing the accuracy of other indices. Body mass index, body round index, a body shape index, and WC were also reliable measurements to assess IR and the risk of CVD (P < 0.05). Conclusion: The study underscores the importance of assessing IR in nondiabetic young females to identify early cardiometabolic risks. VAI emerges as a precise measurement for identifying IR and CVD risk, surpassing the accuracy of other indices.

The prevalence of obesity and hypertension is increasing, particularly in the urban areas. However, there is limited research on the relationship between obesity and hypertension in the rural areas of southeastern Nigeria. The present study aimed to investigate the association between anthropometric parameters and adiposity indicators and the risk of hypertension with obesity-related conditions, based on a descriptive study of people living in the southeastern rural areas of Nigeria. The cluster sampling procedure randomly recruited study participants. Finally, 200 participants (100 male and 100 female) aged 18 to 25 years were included in the study. A simplified correlation analysis was used to derive the adjusted indicators in relation to age and sex. This study found that females generally had a higher body mass index (BMI), waist circumference (WC), and Z-score, whereas systolic blood pressure (SBP) was higher in men. A high correlation was found between the body shape index (ABSI) and BMI (r = -.529, P < .001), WC (r = .399, P < .001) and Z-score (r = .982, P < .001) in male participants. In females, there was a high correlation between ABSI and BMI, blood pressure (BP), and Z score in female participants (r = -.481, P < .000; r = -.267, P = .007; r = .941, P < .000). In male participants, BMI was correlated with diastolic blood pressure (DBP; r = .236, P = .018), SBP (r = .282, P = .005), Z score (r = -.539, P < .000), and WC (r = .541, P < .001). This study highlights the importance of considering a range of anthropometric measurements and health parameters when assessing health risks and identifying potential interventions. In addition, the body shape index may be a particularly useful tool for predicting health risks in both men and women. In contrast, correlations between various health parameters can provide insights into the underlying mechanisms and risk factors.

This study investigated the associations between several obesity-related anthropometric indices and mortality in middle-aged and elderly populations to compare the indices' predictive ability with that of the body mass index (BMI).

We analyzed data on 12 indices calculated from 19,805 community-based cohort participants (average age, 63.27 years; median follow-up, 13.49 years). Each index was calculated using directly measured values of height, weight, waist circumference (WC), and hip circumference (HC). We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for each index using Cox regression and evaluated mortality prediction with the Harrell concordance index (c-index).

Adding anthropometric indices to the basic mortality model (c-index, 0.7723; 95% CI, 0.7647 to 0.7799) significantly increased the predictive power of BMI (c-index, 0.7735; 95% CI, 0.7659 to 0.7811), a body shape index (ABSI; c-index, 0.7735; 95% CI, 0.7659 to 0.7810), weight-adjusted waist index (WWI; c-index, 0.7731; 95% CI, 0.7656 to 0.7807), and waist to hip index (WHI; c-index, 0.7733; 95% CI, 0.7657 to 0.7809). The differences between the BMI model and the other 3 models were not statistically significant.

In predicting all-cause mortality, the ABSI, WWI, and WHI models based on WC or HC had stronger predictive power than conventional risk factors but were not significantly different from the BMI model.

Estimating the change rates in body size following the weight loss programs is very important in the compliance of those programs. Although, there is enough evidence on the significant association of body weight change with the other anthropometric indices and/ or body composition, there is so limited studies that have depicted this relationship as mathematical formulas. Therefore, the present research designed to use a mathematical model to predict changes of anthropometric indices following a weight-loss diet in the overweight and obese women. In this longitudinal study, 212 overweight/obese women who received an individualized low-calorie diet (LCD) were selected and followed-up for five months. Anthropometric measurements such as weight, waist circumference (WC), hip circumference (HC), and body composition (lean mass and fat mass) were performed. Then, body mass index, waist to hip ratio (WHR), waist to height ratio (WHtR), a body shape index (ABSI), abdominal volume index (AVI), and body adiposity index (BAI) were calculated using the related formula. Following the LCD led to the substantial and consistent changes in various anthropometric indices over time. All of these anthropometric variations were significantly related with the percent change (PC) of body weight except than WHR. Moreover, according to the mathematical formulas, weight loss was closely related to the decrease of WC (PC-WC =  - 0.120 + 0.703 × PC-WT), HC (PC-HC =  - 0.350 + 0.510 × PC-WT), body fat percentage (PC-Body Fat =  - 0.019 + 0.915 × PC-WT), WHtR (PC-WHtR =  - 0.113 + 0.702 × PC-WT), and improvements in ABSI (PC-ABSI =  - 0.112 + 0.034 × PC-WT) and AVI (PC-AVI =  - 0.324 + 1.320 × PC-WT). The decreasing rates of WC, HC, body fat percentage, WHtR, ABSI, and AVI in relation to the weight loss were clinically and statistically significant. This means that a healthy weight lowering diet would be accompanied by decreasing the body fat, body size and also the risk of morbidities.

Adipose tissues serve as an energy reservoir and endocrine organ, yet the mechanisms that coordinate these functions remain elusive. Here, we show that the transcriptional coregulators, YAP and TAZ, uncouple fat mass from leptin levels and regulate adipocyte plasticity to maintain metabolic homeostasis. Activating YAP/TAZ signalling in adipocytes by deletion of the upstream regulators Lats1 and Lats2 results in a profound reduction in fat mass by converting mature adipocytes into delipidated progenitor-like cells, but does not cause lipodystrophy-related metabolic dysfunction, due to a paradoxical increase in circulating leptin levels. Mechanistically, we demonstrate that YAP/TAZ-TEAD signalling upregulates leptin expression by directly binding to an upstream enhancer site of the leptin gene. We further show that YAP/TAZ activity is associated with, and functionally required for, leptin regulation during fasting and refeeding. These results suggest that adipocyte Hippo-YAP/TAZ signalling constitutes a nexus for coordinating adipose tissue lipid storage capacity and systemic energy balance through the regulation of adipocyte plasticity and leptin gene transcription.

Obesity is a complex chronic metabolic disorder characterized by abnormalities in lipid metabolism. Obesity is not only associated with various chronic diseases but also has negative effects on physiological functions such as the cardiovascular, endocrine and immune systems. As a global health problem, the incidence and prevalence of obesity have increased significantly in recent years. Therefore, understanding assessment methods and measurement indicators for obesity is critical for early screening and effective disease control. Current methods for measuring obesity in adult include density calculation, anthropometric measurements, bioelectrical impedance analysis, dual-energy X-ray absorptiometry, computerized imaging, etc. Measurement indicators mainly include weight, hip circumference, waist circumference, neck circumference, skinfold thickness, etc. This paper provides a comprehensive review of the literature to date, summarizes and analyzes various assessment methods and measurement indicators for adult obesity, and provides insights and guidance for the innovation of obesity assessment indicators.

The associations of body fat parameters with arterial stiffness measured by brachial-ankle pulse wave velocity in hypertensive patients were scarce.

This cross-sectional study analyzed 4322 hypertensive adults. The correlations between the anthropometric indexes (body mass index [BMI], waist circumference, waist-tohip ratio [WHR], waist-to-height ratio [WHtR], a body shape index [ABSI], body round index [BRI]) and ba-PWV values were analyzed using multivariable linear regression model.

In both sex categories, linear regression models showed that BMI levels were inversely related to baPWV (adjusted-β per SD increase in male: -0.51, 95% CI -0.66 to -0.36, P < 0.001; female: -0.50, 95% CI -0.63 to -0.37, P < 0.001). Waist circumference positively correlated with baPWV only in male hypertensive individuals. BaPWV positively correlated to WHR or WHtR levels (adjusted-β per SD increase: 0.32, 95% CI 0.21 to 0.43, P < 0.001; 0.64, 95% CI 0.47 to 0.82, P < 0.001; respectively), ABSI (adjusted-β per SD increase for ABSI × 100: 0.27, 95% CI 0.18 to 0.36, P < 0.001) and BRI (adjusted-β per SD increase: 0.64, 95% CI 0.46 to 0.81, P < 0.001) levels. The relationship between anthropometric indices and arterial stiffness based on baPWV values were also consistent. ABSI had the highest predictive power of arterial stiffness (area under the curve, 0.594; P < 0.001).

In Chinese adults with hypertension, BMI was inversely related to baPWV, while WHR, WHtR, ABSI and BRI were positively related. Waist circumference positively correlated with baPWV only in male hypertensive individuals.

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.

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).

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.

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.

To study the utility of A Body Shape Index (ABSI) alongside body mass index (BMI) to predict mortality and frailty in an aging community population.

Participants (n = 1,580) were drawn from the first Israeli national health and nutrition survey of older adults ("Mabat Zahav") conducted from 2005 to 2006, constituting adults aged ≥65 years. Socio-demographic, clinical, behavioral, and psychosocial data were collected. Baseline weight, height, and waist circumference (WC) were measured and expressed as the allometric indices BMI (kg/m2) and ABSI, a BMI-independent measure of abdominal obesity [WC/(BMI2/3*m1/2)]. Mortality follow-up lasted through 2019. Frailty was assessed in 2017-2019 by the Fried Biological Phenotype in a sub-cohort of 554 survivors. Cox and logistic regression models assessed associations of BMI and ABSI with mortality and frailty.

At baseline, mean [SD] age was 74.5 [6.1] years, and 52.4% were women. The correlation between BMI and WC Z scores was 0.71, reduced to -0.11 for BMI and ABSI. Over a median follow-up of 13 years, 757 deaths occurred. The multivariable-adjusted hazard ratios (95% CIs) for mortality per standard deviation increase in BMI and ABSI were 1.07 (0.99;1.17) and 1.13 (1.05;1.21), respectively. Among participants assessed for frailty, 77 (14%) met the frailty criteria. After multivariable adjustment, the odds ratios (95% CIs) for frailty were 0.83 (0.69-1.01) for BMI and 1.55 (1.34-1.79) for ABSI.

In a nationwide cohort of older adults, ABSI was independently associated with mortality risk. Furthermore, ABSI, but not BMI, was a strong predictor of frailty.

Aims: The present study aimed to clarify the relationships between novel and traditional anthropometric indices and insulin sensitivity (SI) in young and middle-aged Japanese persons with normal glucose tolerance (NGT), and middle-aged Japanese persons with NGT and glucose intolerance. Methods: Plasma glucose and insulin levels were measured in 1270 young (age <40 years) and 2153 middle-aged persons with NGT (n = 1531) and glucose intolerance (n = 622) during a 75-g oral glucose tolerance test. Height (Ht), weight, and waist circumference (WC) were measured. The body mass index (BMI), WC, and the WC/Ht ratio were used as traditional anthropometric indices. A body shape index (ABSI) and the body roundness index (BRI) were calculated as novel indices. Indices of SI (Matsuda index and 1/homeostasis model assessment of insulin resistance) were calculated and compared with anthropometric indices. Results: The ABSI showed a weak correlation with SI indices in all groups. The BRI showed almost the same correlation with SI indices as the BMI, WC, and WC/Ht in all groups. The inverse correlation between each of the anthropometric indices other than ABSI and SI indices was weak in young persons, at 0.16-0.27 (Spearman's ρ values), but strong in middle-aged persons, at 0.38-1.00. On receiver-operating characteristic (ROC) curve analysis for detection of insulin resistance, the ABSI had a lower area under the ROC curve (AUC) than the other anthropometric indices, and the BRI and the WC/Ht ratio showed similar AUCs. The AUCs for the BRI and WC/Ht ratio were the highest in middle-aged men with NGT and glucose intolerance. Conclusions: The BRI, not the ABSI, was better correlated with SI in young and middle-aged Japanese persons. The BRI and WC/Ht ratio were comparable in their correlations with SI and the detection of insulin resistance in the participants of the present study.