Obesity is a worldwide health crisis and poses significant challenges in critical care. Many studies suggest an 'obesity paradox', in which obesity, defined by body mass index (BMI), is associated with better outcomes. However, the inability of BMI to discriminate between fat and muscle or between visceral adipose tissue and subcutaneous adipose tissue, limits its prediction of metabolic ill health. We suggest that the 'obesity paradox' may be more reflective of the limitations of BMI than the protective effect of obesity. We explore the biological processes leading to visceral fat accumulation, and the evidence linking it to outcomes in critical illness. In the 'spillover' hypothesis of adipose tissue expansion, caloric excess and impaired expansion of storage capacity in the subcutaneous adipose tissue lead to accumulation of visceral adipose tissue. This is associated with a chronic inflammatory state, which is integral to the link between visceral adiposity, type 2 diabetes mellitus, and ischaemic heart disease. We review the current evidence on visceral adiposity and critical illness outcomes. In COVID-19, increased visceral adipose tissue, irrespective of BMI, is associated with more severe disease. This is mirrored in acute pancreatitis, suggesting visceral adiposity is linked to poorer outcomes in some hyperinflammatory conditions. We suggest that visceral adiposity's chronic inflammatory state may potentiate acute inflammation in conditions such as COVID-19 and acute pancreatitis. Further work is required to investigate other critical illnesses, especially sepsis and acute respiratory distress syndrome, in which current evidence is scarce. This may give further insights into pathophysiology and inform tailored treatment and nutrition strategies based on body fat distribution.

To examine the correlation between dietary habits, anthropometric measurements, and microvascular reactivity with respect to sex in older adults (aged > 65 years) residing in organized accommodation within retirement homes.

Sixty-nine older persons who live in a retirement home in Osijek, Croatia volunteered to participate (34 men and 35 women) in this observational cross-sectional study. Study was performed in the period from May 1, 2024 to July 1, 2024. Subjects weight, height, waist circumference, hip circumference, blood pressure and heart rate were measured, and body mass index (BMI) and waist to hip ratio (WHR) were calculated. To assess microvascular endothelium-dependent vasodilation, skin microvascular post-occlusion reactive hyperemia (PORH) was assessed by Laser Doppler Flowmetry. Long-term dietary patterns and dietary habits were evaluated with validated EPIC-Norfolk food frequency questionnaire, in Croatian language. Study was approved by Ethical Committee of Faculty of Medicine Osijek (Class: 641-01/24-01/04, No: 2158-61-46-24-86).

Mean age (standard deviation, SD) of 34 older men was 83.8 (5.4) years, and of 34 older women 83.6 (5.5) years. The mean BMI of all subjects was 27.1 kg/m2 classifying them as overweight. Both men (WHR 0.99 (0.07)) and women (WHR 0.90 (0.06) had significantly higher than normal WHR (normal WHR, men <0.90, women <0.80), suggesting the visceral type of obesity. The mean intake of NaCl was higher (NaCl g/day men 6.91 (1.43), women 6.93 (2.51)), and intake of vitamin D lower (vitamin D µg/day men 3.64 (1.35), women 3.47 (2.61)) than recommended values (NaCl g/day <5 g/day, vitamin D 15 µg/day). Men consumed significantly more alcohol (alcohol g/day men 1.48 (3.36) vs women 0.17 (0.39), P = 0.03), while women had higher carotene intake (β-carotene, µg/day men 2603 (1020) vs women 3478 (1580), P = 0.009). Microvascular reactivity was similar in women and men (PORH, R-O% men 85.2 (30.6) vs women 76.2 (31.5), P > 0.05). However, women had a significant negative correlation of waist circumference (R = -0.350, P =0.04) and WHR (R = -0.406, P = 0.02) to PORH.

Dietary habits were similar between older men and women, except for higher alcohol intake in men and higher carotene intake in women. In older women, microvascular reactivity was negatively associated with waist circumference and WHR, underscoring central obesity as a key cardiovascular risk factor in this population. Given the increased cardiometabolic vulnerability in postmenopausal women, measures of central adiposity should be routinely monitored in geriatric care.

This study aims to identify the optimal anatomical site that best predicts the total thoracic subcutaneous adipose tissue (SAT) and skeletal muscle (SM) volumes on chest computed tomography (CT), and to evaluate the relationships between SAT and SM areas at optimal slice and lung function.

Healthy participants and chronic obstructive pulmonary disease (COPD) patients undergoing chest CT between January 2022 and April 2023 were retrospectively included. On chest CT, cross-sectional areas of SAT and SM at 14 specific anatomical levels, and thoracic SAT and SM volumes were measured using 3D Slicer software. Correlations were calculated by Spearman's correlation coefficients.

About 58 healthy participants and 68 COPD patients were included. In healthy participants, the T4 SAT area correlated most strongly with thoracic SAT volume (r = 0.888, P < 0.01), and the aortic arch SM area with SM volume (r = 0.941, P < 0.01). The combined Spearman's correlation coefficients reached their highest sum (1.816) at the aortic arch level. In COPD patients, correlations were identified between SAT area at the aortic arch slice with forced expiratory volume in the first second (FEV1)/forced vital capacity (FVC) (r = 0.472, P < 0.001), while SM area with both FEV1(r = 0.431, P < 0.001) and FVC (r = 0.522, P < 0.001).

Considering measurement simplicity and accuracy, the aortic arch slice was identified as the optimal single slice for predicting total thoracic SAT and SM volumes. Additionally, the clinical significance of SAT and SM area at this slice was verified with lung function in COPD patients. Key messages What is already known on this topic: Specific abdominal slices have been shown to estimate abdominal volumes accurately, while the optimal slice to predict thoracic volumes is uncertain. What this study adds: To identify the optimal slice for simultaneously predicting both thoracic SAT and SM volumes. How this study might affect research, practice or policy: The optimal slice in the chest for measurement is crucial for advancing research on thoracic SAT and SM.

Metabolic syndrome (MetS) poses a significant challenge to global public health, due to its strong association with Type 2 diabetes and cardiovascular disease. Waist circumference (WC) is a convenient metric for diagnosing MetS. Our study sought to establish waist circumference cut-off points that predict MetS among females of reproductive age in Wakiso district, central Uganda.The data collected were from a cross-sectional study conducted in Wakiso district, central Uganda, involving 697 randomly selected females aged 15 to 49, between 9th June 2021 and 17th August 2021. Data included MetS components: WC, High-Density Lipoprotein (HDL) Cholesterol, triglycerides, blood pressure, and fasting blood glucose. MetS status was identified based on two or more MetS components excluding WC. ROC analysis established the average optimal WC. The accuracy and performance of the cut-off points were evaluated through sensitivity, specificity, positive likelihood ratio, and the Youden Index. Of the 634 participants who were aged 18-49 years, 51.4% had two or more MetS risk factors. Their average optimal WC threshold was 80.3 cm. Variations in optimal WC thresholds were observed across different age groups: 80.4 cm (18-24 years), 79.9 cm (25-34 years), 85.6 cm (35-44 years), and 91.1 cm (45-49 years) respectively. The area under the ROC curve at the cut point for these age groups ranged from 0.78 to 0.86, indicating good discriminatory capability. The sensitivity ranged from 85% to 97%, specificity from 58% to 88%, and the Youden Index from 0.557 to 0.729. A waist circumference of 80.3 cm was the optimal threshold for identifying metabolic syndrome in females between the ages of 18 and 49 years in the setting. This finding concurs with the guidance set forth by the International Diabetes Federation. Additionally, study participants' WC cut-offs varied, ranging from 79.9 cm to 91.1 cm, depending on their age.

Several lipid metabolism-related profiles have been explored for their association with obesity, but no consensus has been reached. Therefore, this study aimed to comprehensively analyze the correlation between conventional and unconventional lipid profiles and visceral fat area (VFA) in overweight/obese patients with type 2 diabetes mellitus (T2DM). Emphasizing the overall relationship between lipid metabolism and visceral fat accumulation.

This cross-sectional study included 1288 overweight/obese T2DM patients, with VFA measured using bioelectrical impedance analysis and visceral fat obesity (VFO) was defined as VFA ≥ 100 cm². Both conventional lipid profiles include total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and lipoprotein(a), and unconventional lipid profiles include lipid composite index (LCI), platelet/ HDL-c ratio (PHR), remnant cholesterol (RC), TG/HDL-c, Castelli Risk Index I (CRI-I), Castelli Risk Index II (CRI-II), Non-HDL-c, atherogenic index of plasma (AIP) and atherogenic coefficient (AC) were analyzed. The study population was divided into non-VFO and VFO groups, The relationship between conventional and unconventional lipid profiles and VFO was evaluated.

Compared to the non-VFO group, the VFO group exhibited significantly higher levels of TG, lipoprotein(a), LCI, RC, TG/HDL-c, CRI-I, CRI-II, AIP, and AC (all P < 0.05). Univariate analysis revealed that RC, TG, LCI, TG/HDL-c, CRI-I, CRI-II, AIP, and AC were positively correlated with VFA and VFO, while HDL-c and lipoprotein(a) were negatively correlated (all P < 0.05). Logistic regression identified RC as an independent risk factor for VFO (OR: 1.667, 95% CI: 1.216-2.285, P = 0.001).

Among lipid profiles, RC is independently and significantly associated with VFO, underscoring its role in lipid metabolism and abdominal obesity management, especially in overweight/obese T2DM patients.

Evidence links body composition and inflammatory markers with type 2 diabetes (T2D). However, the comparative analysis of body composition markers derived from different modalities and inflammatory markers in relation to T2D remains unexplored. This study aims to evaluate and compare the association of body composition and inflammatory markers with T2D.

We included 4043 participants (2081 female, 51.4%) aged 20-84 enrolled in the population-based Study of Health in Pomerania. Multivariable logistic regression models adjusted for confounding were used to analyse associations of standardized body composition markers derived from classic anthropometry, bioelectrical impedance analysis, magnetic resonance imaging as well as inflammatory markers C-reactive protein, white blood cell count, fibrinogen, ferritin and CRP-to-albumin ratio with prevalent T2D.

Body composition markers were more strongly associated with T2D than inflammatory markers. Waist circumference exhibited the strongest association with T2D (female: odds ratio (OR) = 2.55; 95% confidence interval [CI]: 2.17-3.00; male: OR = 2.20; 95% CI: 1.86-2.60). Similarly, body weight (female: 2.07; 1.78-2.41; male: OR = 1.99; 95% CI = 1.71-2.31), waist-to-height ratio (female: OR = 2.39; 95% CI = 2.05-2.77; male: 2.28; 1.92-2.70) and visceral adipose tissue (female: 3.02; 95% CI = 2.11-4.32; male: 1.50; 1.19-1.89) showed strong associations with T2D. Among inflammatory markers, white blood cell count in male and CRP-to-albumin ratio in female exhibit the strongest association with T2D.

Body composition markers seem to be more tightly associated with prevalent T2D compared to inflammatory markers.

The visceral adiposity index is a valuable tool for assessing visceral fat accumulation. However, its non-linear association with prediabetes and diabetes requires further elucidation. Therefore, we aim to clarify the intricate interplay between the visceral adiposity index and these dysglycemic conditions.

The National Health and Nutrition Examination Survey database from 1999 to 2018 was utilized to analyze health data from 24,072 participants. A multivariate logistic regression model was employed to evaluate the independent association between the visceral adiposity index and prediabetes and diabetes while considering potential confounding factors. Generalized additive models were used to identify any non-linear relationships by fitting smooth curves. Additionally, a stratified analysis based on different baseline characteristics was conducted, along with an interactive analysis.

After accounting for all relevant variables, individuals in the lowest quartile of the visceral adiposity index had a notably diminished likelihood of progressing to prediabetes and diabetes when compared with those in the other three quartiles. The odds ratios and 95% confidence intervals were as follows: 1.37 (1.23, 1.53), 1.87 (1.65, 2.12), and 2.80 (2.33, 3.37). More importantly, a non-linear association was observed between the visceral adiposity index and prediabetes and diabetes, with a threshold identified at 2.10.

There exists a notable and positive association between the visceral adiposity index and prediabetes and diabetes, displaying non-linear attributes in this evaluation of the relationship. Risk assessment and early prevention strategies targeting the maintenance of low levels of visceral adiposity index may substantially diminish the likelihood of developing prediabetes and diabetes.

Recent studies have indicated that triglyceride glucose (TyG)-waist height ratio (WHtR) and TyG-waist circumference (TyG-WC) are effective indicators for evaluating insulin resistance. However, research on the association in TyG-WHtR, TyG-WC, and the risk and prognosis of major adverse cardiovascular events (MACEs) in type 2 diabetes mellitus (T2DM) cases are limited.

To clarify the relation in TyG-WHtR, TyG-WC, and the risk of MACEs and overall mortality in T2DM patients.

Information for this investigation was obtained from Action to Control Cardiovascular Risk in Diabetes (ACCORD)/ACCORD Follow-On (ACCORDION) study database. The Cox regression model was applied to assess the relation among TyG-WHtR, TyG-WC and future MACEs risk and overall mortality in T2DM cases. The RCS analysis was utilized to explore the nonlinear correlation. Subgroup and interaction analyses were conducted to prove the robustness. The receiver operating characteristic curves were applied to analysis the additional predicting value of TyG-WHtR and TyG-WC.

After full adjustment for confounding variables, the highest baseline TyG-WHtR cohort respectively exhibited a 1.353-fold and 1.420-fold higher risk for MACEs and overall mortality, than the lowest quartile group. Similarly, the highest baseline TyG-WC cohort showed a 1.314-fold and 1.480-fold higher risk for MACEs and overall mortality, respectively. Each 1 SD increase in TyG-WHtR was significantly related to an 11.7% increase in MACEs and a 14.9% enhance in overall mortality. Each 1 SD increase in TyG-WC corresponded to an 11.5% in MACEs and a 16.6% increase in overall mortality. Including these two indexes in conventional models significantly improved the predictive power for MACEs and overall mortality.

TyG-WHtR and TyG-WC were promising predictors of MACEs and overall mortality risk in T2DM cases.

This study compares three methods to determine central adiposity (waist circumference -WC - and visceral adipose tissue - VAT - estimated by dual-energy x-ray absorptiometry - DXA, and by magnetic resonance imaging - MRI) in their ability to predict increases in cardiometabolic risk (CMR) markers in young individuals. We examined their associations with CMR in 47 men and women aged 25-40.

VAT mass was assessed using DXA and MRI. Blood samples were analyzed for CMR markers. Associations between central adiposity measurements and CMR factors were analyzed using Spearman's correlation coefficient, and the ability of these three central adiposity measurements to detect increased CMR was compared using receiver operating characteristic (ROC) curves. Similar to what was observed for the MRI-DXA and VAT-DXA, WC showed strong correlations with LDL-c and triglycerides (TG) and an inverse correlation with HDL-c (rho = -0.657 MRI, rho = -0.628 DXA, and rho = -0.604 WC, p < 0.01). On the other hand, only MRI-VAT and WC were associated with insulin and HOMA-IR (rho = 0.341 MRI and rho = 0.421 WC, p < 0.01). Central adiposity measurements were negatively associated with cold-induced 18F-FDG uptake in subcutaneous adipose tissue and positively associated with VAT TG content. No significant differences were observed when comparing the three central adiposity measurements in ROC curve analysis, and all measurements could predict increases in CMR markers and the combined CMR index.

This study reinforces the importance of using WC to assess increases in CMR markers among young adults. Given its practicality and efficacy, WC should be recommended in health centers to assess CMR risk.

To investigate the etiology of spontaneous percutaneous nephrostomy (PCN) catheter dislodgements and evaluate factors potentially associated with these dislodgements, including muscle-to-fat composition and tissue characteristics of catheter traces.

Data from 92 patients (63 males, 29 females; mean age 63.9 ± 11.4 years, range 28-88) undergoing 151 PCN catheter replacements between January 2016 and June 2021 were analyzed. Patients were divided into Group 1 (prophylactic replacements every 3 months, n = 41) and Group 2 (at least one spontaneous dislodgement, n = 51). Associations were evaluated for factors including intraabdominal visceral adipose tissue index (IAVATI), subcutaneous adipose tissue index (SATI), and abdominal perimeter. Other variables assessed were Eastern Cooperative Oncology Group (ECOG) performance status scores, psoas muscle index (PMI), renal size, renal parenchymal thickness, renal cortex-to-skin distance, posterolateral abdominal wall muscle thickness, and PCN replacement frequency.

No significant differences were identified between Group 1 and Group 2 in IAVATI, SATI, or abdominal perimeter values (p = 0.210-0.412). A significant difference in ECOG performance status scores (p = 0.0001), PMI (p = 0.04) and lower renal size, renal parenchymal thickness, renal cortex-to-skin distance, and posterolateral abdominal muscle thickness (p = 0.0001-0.039) were observed in Group 2. PCN replacements were significantly more frequent in Group 2 (p = 0.0001). Multivariate regression identified renal parenchymal thickness and abdominal wall muscle thickness as significant independent predictors (p = 0.0001, p = 0.02). ROC analysis yielded an AUC of 0.843 (95% CI: 0.769-0.917) for renal parenchymal thickness and 0.694 (95% CI: 0.610-0.778) for abdominal wall muscle thickness. Sensitivity and specificity rates were 73.1% and 96.4% for a 16 mm cutoff in renal parenchymal thickness, and 50.7% and 79.8% for an 8 mm cutoff in abdominal wall muscle thickness.

A significant association was identified between spontaneous PCN catheter dislodgement and both the psoas muscle index and ECOG performance status scores, while no notable relationship was observed with abdominal visceral or subcutaneous fat tissue volumes or abdominal perimeter. The risk of dislodgement was found to increase with reduced renal parenchymal and abdominal wall muscle thickness, as well as with more frequent nephrostomy replacements, suggesting these parameters may serve as useful markers for identifying patients at higher risk.

Computed tomography (CT) captures the quantity, density, and distribution of subcutaneous and visceral (SAT and VAT) adipose tissue compartments. These metrics may change with age and sex.

The study aims to provide age-, sex-, and vertebral level-specific reference values for SAT on chest CT and for SAT and VAT on abdomen CT.

This secondary analysis of an observational study describes SAT and VAT measurements in participants of the Framingham Heart Study without known cancer diagnosis who underwent at least 1 of 2 CT examinations between 2002 and 2011. We used a previously validated machine learning-assisted pipeline and rigorous quality assurance to segment SAT at the fifth, eighth, and tenth thoracic vertebra (T5, T8, T10) and SAT and VAT at the third lumbar vertebra (L3). For each metric, we measured cross-sectional area (cm 2 ) and mean attenuation (Hounsfield units [HU]) and calculated index (area/height 2 ) (cm 2 /m 2 ) and gauge (attenuation × index) (HU × cm 2 /m 2 ). We summarized body composition metrics by age and sex and modeled sex-, age-, and vertebral level-specific reference curves.

We included 14,898 single-level measurements from up to 4 vertebral levels of 3797 scans of 3730 Framingham Heart Study participants (1889 [51%] male with a mean [standard deviation] age of 55.6 ± 10.6 years; range, 38-81 years). The mean VAT index increased with age from 65 (cm 2 /m 2 ) in males and 29 (cm 2 /m 2 ) in females in the <45-year-old age group to 99 (cm 2 /m 2 ) in males and 60 (cm 2 /m 2 ) in females in >75-year-old age group. The increase of SAT with age was less pronounced, resulting in the VAT/SAT ratio increasing with age. A free R package and online interactive visual web interface allow access to reference values.

This study establishes age-, sex-, and vertebral level-specific reference values for CT-assessed SAT at vertebral levels T5, T8, T10, and L3 and VAT at vertebral level L3.

The study aimed to explore potential links between long-term digestive issues (specifically diarrhea and constipation) and body roundness index (BRI) in a representative U.S. population sample.

This study adopted a design that is cross sectional, drawing on data from the NHANES, gathered from 2005 to 2010 with health information from a total of 11,235 individuals. Persistent bowel movement patterns were categorized based on the BSFS-Bristol Stool Form Scale, while stool types 1 and 2 were designated as indicators of long-term constipation and types 6 and 7 were identified as markers of persistent diarrhea. To assess the relationship between digestive health and the BRI, this study employed weighted logistic regression analysis. To capture and visualize the nuanced interplay between BRI and gastrointestinal patterns, we utilized advanced nonlinear regression methods, specifically restricted cubic spline (RCS) analyses. Additionally, the research compared the efficacy of various physical measurements-including BRI, WC, BMI (body roundness index, waist circumference, and body mass index, respectively)-to determine their respective diagnostic power for chronic diarrhea and constipation through comparative analysis of receiver operating characteristic (ROC) curves.

After comprehensive adjustment in the final statistical model (Model 3), the BRI demonstrated the statistically significant associations with diarrhea and persistent constipation. RCS analysis further uncovered statistically significant nonlinear positive associations of BRI and with diarrhea (P = 0.005) and constipation (P = 0.037). Further stratified analyses revealed that the relationship between BRI and persistent diarrhea was particularly evident among individuals with diabetes. In contrast, the association between BRI and constipation was stronger in individuals under 60 years of age. ROC analysis indicated that BRI outperformed conventional anthropometric measures (AUC, area under the curve: 0.601). Specifically, BMI resulted in an AUC of 0.569, while WC produced an AUC of 0.572. However, the AUC value of BRI (0.537) was less effective than BMI (0.551) and WC (0.570) in diagnosing constipation.

BRI is strongly associated with changes in the individual's bowel habits, particularly in diagnosing chronic diarrhea. This study highlighted the potential significance of maintaining moderate BRI levels to improve bowel health and prevent diarrhea.

This study aims to examine the prevalence of abdominal obesity-dynapenia phenotype, identified by the presence of abdominal obesity and dynapenia, and understand its associated factors with a representative sample of the Brazilian population. Data were collected from the baseline of the Brazilian Longitudinal Study of Aging (ELSI-Brasil) 2015-2016. Abdominal obesity was determined by a waist-to-height ratio ≥ 0.55cm, while dynapenia was identified by evidence of low handgrip strength assessed via dynamometry, according to cutoff points proposed for the Brazilian population. The dependent variable was the coexistence of both conditions (abdominal obesity and dynapenia), and its association with independent variables (sociodemographic characteristics, behavior and health conditions, chronic diseases, and place of residence by Brazilian region) was analyzed using Poisson regression to obtain crude and adjusted prevalence ratios by sex, age, and education level. The prevalence of isolated abdominal obesity was 57.8%, isolated dynapenia was 5.7%, and abdominal obesity-dynapenia was 12.3%. In the adjusted model, significant associations were found with smoking (0.7; 95%CI: 0.5-0.9), alcohol consumption (0.7; 95%CI: 0.5-0.9), physical activity (0.6; 95%CI: 0.5-0.8), poor self-rated health (1.7; 95%CI: 1.4-2.2), multimorbidity (1.3; 95%CI: 1.1-1.6), and regions of residence. These factors indicate key points for the development of prevention and treatment strategies for abdominal obesity associated with low muscle strength, and we suggest that methodologies discussed here for abdominal obesity diagnosis be used as a reliable and practical means to identify this condition in older adults.

Visceral adipose tissue (VAT) is known to play a role in the development of metabolic and cardiovascular disease (CVD). However, the age- and sex-specific associations between VAT and these diseases remain unclear.

In this cross-sectional study, 1,150 participants (39.5% women; mean age 61.5 years) underwent VAT measurement using dual abdominal bioelectrical impedance analysis (BIA). The four age groups that the participants were divided into were 18-44, 45-59, 60-74, and ≥ 75 years. The relationships between VAT and cardiometabolic outcomes were analyzed by age and sex using multivariable logistic regression.

Significant associations between VAT and metabolic health status were observed in middle-aged (45-59 years; OR = 1.41, 95% CI: 1.04-1.92) and elderly adults (60-74 years; OR = 1.45, 95% CI: 1.10-1.92). VAT demonstrated age-dependent relationships with cardiovascular risk factors, with the strongest associations found in the 60-74 years group for hypertension (OR: 1.55, 95% CI: 1.22-1.98) and low high-density lipoprotein cholesterol (OR: 1.66, 95% CI: 1.33-2.08). Notably, the VAT-CVD association was most pronounced in elderly women (60-74 years; OR: 1.86, 95% CI: 1.14-3.11), while no significant associations were observed in men across all age groups.

The impact of VAT on metabolic and cardiovascular disease risk varies by age and sex, with particularly strong associations observed in elderly women. This highlights the need for tailored prevention and treatment strategies.

Introduction: Metabolic syndrome (MetS) and hypertriglyceridemic waist (HTW) are two multifactorial pathological conditions that have been increasing in prevalence worldwide. The objective of this study was to evaluate how various sociodemographic variables and healthy habits are associated with the presence or absence of MetS and HTW. Methodology: This study employed a mixed-methods approach, consisting of a retrospective longitudinal study and a cross-sectional descriptive study, analyzing 44,939 healthcare workers with MS and HTW across four professional categories to evaluate the relationship between age, sex, smoking, physical activity, and adherence to the Mediterranean diet using three diagnostic criteria. Descriptive analysis included categorical and quantitative variables, which were assessed through frequencies, Student's t-test, chi-square, and binary logistic regression models. Logistic regression and Cohen's kappa were used to evaluate associations and concordances. Age, sex, and lack of physical activity showed the strongest associations with MetS (OR: 2.65-2.84). The results highlight the importance of physical activity and other factors in metabolic prevention. Results: Age, sex, and physical activity were the variables most strongly associated with MetS and HTW across the three evaluated diagnostic criteria. The odds ratios revealed significant values: age (9.07-13.71 for MetS and 13.42 for HTW), sex (2.82-3.31 for MetS and 3.72 for HTW), and physical activity (2.65-2.84 for MetS and 2.40 for HTW). Conclusions: The risk of developing MetS and HTW among healthcare personnel is influenced by lifestyle habits, sex, and age, with the highest ORs observed in nursing assistants and orderlies. Future research that delves deeper into the causal relationship between lifestyle factors and the severity of MetS and HTW in healthcare personnel will improve understanding and facilitate the development of preventive activities to reduce their incidence.

To explore the association between the non-high-density lipoprotein cholesterol (HDL-C)/HDL-C ratio (NHHR) and the risk of major adverse cardiovascular events (MACEs) and overall mortality in patients with type 2 diabetes mellitus (T2DM).

NHHR, calculated as (total cholesterol - HDL-C)/HDL-C, was evaluated in 10,188 participants. Cox proportional hazard regression models were employed to assess the association of NHHR with future risk of MACEs and overall mortality. Restricted cubic spline analysis, smooth curve fitting and piecewise regression models were utilized to explore the non-linear correlation and establish the threshold. Subgroup and interaction analyses verified the robustness of the findings. The area under the receiver operating characteristic area under the curve assessed the additional predictive value of NHHR beyond conventional risk factors.

After adjusting for confounding factors, each 1-unit increase in NHHR was associated with a 12% increased risk of MACEs (hazard ratio [HR]: 1.12, 95% confidence interval [CI]: 1.07-1.16; p < 0.0001), a 5% increase in overall mortality (HR: 1.05, 95% CI: 1.01-1.10; p = 0.0256), a 10% increase in cardiovascular disease mortality (HR 1.10, 95% CI: 1.03-1.18; p = 0.0074), an 12% increase in non-fatal myocardial infarction (HR: 1.12, 95% CI: 1.05-1.18; p = 0.0002), and an 11% increase in non-fatal stroke (HR: 1.11, 95% CI: 1.02-1.20; p = 0.0123). Analyses showed a non-linear relationship between NHHR and MACEs in patients with T2DM (non-linearity p < 0.001). A two-stage linear regression model identified a threshold for MACEs at 6.28. Integration NHHR into the conventional model significantly enhanced predictive accuracy for MACEs.

NHHR is a predictor of the risk of developing MACEs and overall mortality in patients with T2DM, with higher NHHR values independently associated with increased future MACE risks after full adjustment for confounders.

This study was conducted to perform deep learning-based body shape cluster analysis using 3D Body Scanner.

For this study, 54 variables were measured using 3D Body Scanner on 366 adult men and women at Korea National Sport University in 2022. Transformer learning and dimensionality reduction models were used to perform cluster analysis on the measured data. Mann-Whitney test and Kruskal-Wallis test were applied to compare the principal component differences of new scale characteristics, and all statistical significance levels were set at .05.

First, among the two methods for classifying body types, the transformer algorithm had a higher performance in body type classification. Second, in the classification of body type clusters, two clusters, endomorphic body type and ectomorphic body type, were divided into six clusters, two for cluster 1 and four for cluster 2.

The six clusters provide more granular information than previous body type classifications, and we believe that they can be used as basic information for predicting health and disease.

The duration of sleep is linked to a range of disorders. Osteoarthritis (OA) stands as one of the most prevalent forms of arthritis and serves as a leading cause of disability. The correlation between the duration of sleep and OA remains ambiguous. Research indicates that waist circumference correlates with sleep duration and OA, respectively. This study aimed to investigate the association of sleep duration with OA and the mediated effect of waist circumference.

The study sample comprised adults who were participants in the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2018. Insufficient sleep is characterized by a duration of less than seven hours, whereas 7-8 h is considered appropriate, and 9 h or more is categorized as a long sleep duration. Three models were employed in this study. Model 1 was not adjusted for any covariates, while Model 2 was adjusted for sex, age, and race. Model 3 has been adjusted to account for all covariates. Utilizing multivariable logistic regression, subgroup analysis, interaction tests and smoothing curve fitting, the correlation between sleep duration and OA was explored. The mediating effect of waist circumference on the association between sleep duration and OA was investigated through mediation analysis.

In this study, 9380 did not have OA, while 2424 were diagnosed with the ailment. After multivariable adjustment, the odds ratios (OR) for OA were 1.19 (95% CI 1.06, 1.34; P = 0.0026) for people with insufficient sleep duration and 1.18 (95% CI 1.03, 1.35 P = 0.0142) for participants with long sleep duration. Sleep duration and the incidence of OA were found to be related in a U-shaped manner. Additionally, 12.1% of the correlation between sleep duration and OA appeared to be mediated by waist circumference.

Increased OA was found to be correlated in a U-shaped manner with sleep duration in the middle-aged and elderly cohorts. Both insufficient and long sleep duration contribute to an elevated risk of developing OA. A potential mediating factor in the association between OA and sleep duration is waist circumference. Focus on sleep health and visceral obesity in middle-aged and older adults is necessary.

Diabetic peripheral neuropathy (DPN) is a chronic complication of diabetes that can potentially escalate into ulceration, amputation and other severe consequences. The aim of this study was to construct and validate a predictive nomogram model for assessing the risk of DPN development among diabetic patients, thereby facilitating the early identification of high-risk DPN individuals and mitigating the incidence of severe outcomes.

1185 patients were included in this study from June 2020 to June 2023. All patients underwent peripheral nerve function assessments, of which 801 were diagnosed with DPN. Patients were randomly divided into a training set (n =711) and a validation set (n = 474) with a ratio of 6:4. The least absolute shrinkage and selection operator (LASSO) logistic regression analysis was performed to identify independent risk factors and develop a simple nomogram. Subsequently, the discrimination and clinical value of the nomogram was extensively validated using receiver operating characteristic (ROC) curves, calibration curves and clinical decision curve analyses (DCA).

Following LASSO regression analysis, a nomogram model for predicting the risk of DPN was eventually established based on 7 factors: age (OR = 1.02, 95%CI: 1.01 - 1.03), hip circumference (HC, OR = 0.94, 95%CI: 0.92 - 0.97), fasting plasma glucose (FPG, OR = 1.06, 95%CI: 1.01 - 1.11), fasting C-peptide (FCP, OR = 0.66, 95%CI: 0.56 - 0.77), 2 hour postprandial C-peptide (PCP, OR = 0.78, 95%CI: 0.72 - 0.84), albumin (ALB, OR = 0.90, 95%CI: 0.87 - 0.94) and blood urea nitrogen (BUN, OR = 1.08, 95%CI: 1.01 - 1.17). The areas under the curves (AUC) of the nomogram were 0.703 (95% CI 0.664-0.743) and 0.704 (95% CI 0.652-0.756) in the training and validation sets, respectively. The Hosmer-Lemeshow test and calibration curves revealed high consistency between the predicted and actual results of the nomogram. DCA demonstrated that the nomogram was valuable in clinical practice.

The DPN nomogram prediction model, containing 7 significant variables, has exhibited excellent performance. Its generalization to clinical practice could potentially help in the early detection and prompt intervention for high-risk DPN patients.

Understanding children's eating behaviors is crucial for elucidating the etiology of childhood obesity. However, the relationship between these behaviors and abdominal fat accumulation remains poorly understood. This study aims to investigate this association in primary school children.

This study included 1,475 children aged 8-10 years in Ningbo, China. Body composition was measured both at baseline (September 2022) and after 9 months of follow-up (June 2023). Primary caregivers completed the Children's Eating Behavior Questionnaire (CEBQ). A mixed-effects linear model was applied to analyze the relationships between children's eating behaviors and body composition.

Greater visceral fat area (VFA) was associated with greater slowness in eating [β = 0.25 (0.02, 0.49)], greater food responsiveness [β = 0.29 (0.14, 0.43)], increased emotional undereating [β = 0.35 (0.17, 0.54)], and more emotional overeating [β = 0.21 (0.02, 0.39)]. Children with greater trunk fat mass (TrFM) tended to have greater food responsiveness [β = 0.02 (0.01, 0.03)] and greater enjoyment of food [β = 0.01 (0.00, 0.03)], increased emotional undereating [β = 0.02 (0.01, 0.03)] and emotional overeating [β = 0.02 (0.00, 0.03)]. Prospectively, positive correlations were observed between VFA and food responsiveness [β = 0.18 (0.02, 0.35)], as were emotional undereating [β = 0.31 (0.10, 0.52)] and emotional overeating [β = 0.24 (0.03, 0.46)]. Similarly, TrFM was positively correlated with food responsiveness [β = 0.02 (0.00, 0.03)], enjoyment of food [β = 0.02 (0.00, 0.04)], emotional undereating [β = 0.02 (0.01, 0.04)] and emotional overeating [β = 0.02 (0.01, 0.04)].

Our findings suggest that eating behaviors are significantly associated with abdominal fat accumulation in primary school children. Addressing specific eating behaviors may be crucial in mitigating abdominal fat and its related health risks.

Obstructive sleep apnea (OSA) predominantly affects patients who are obese and causes systemic organ damage. Little is known about the relationship between fat distribution and bone impairment in these patients. We aimed to evaluate the impact of the visceral adipose tissue (VAT) on the bone quality of patients with OSA. In our prospective study, 49 untreated patients with mild-to-severe OSA underwent dual-energy X-ray absorptiometry. Polygraphy data were also collected. According to the recent reference values for European adults, patients were divided by the sex-related threshold of the VAT index into two categories: VAT index within limits (normal VAT [nVAT]) and increased VAT (iVAT). In all, 63% of the patients were in the iVAT category. Compared to patients with nVAT, those with iVAT had a higher prevalence of arterial hypertension (52% versus 22%) and diabetes (32% versus 6%), and higher values of mean nocturnal desaturation. Patients with iVAT had, in comparison to those with nVAT, lower values of the lumbar spine trabecular bone score (TBS; mean 1.24 versus 1.39; p < 0.001), TBS T-score (mean -1.82 versus -0.52; p < 0.001) and TBS Z-score (mean -0.35 versus 0.75; p = 0.002). Moreover, a close association was present between the VAT index and TBS lumbar spine L1-L4 (r2 linear 0.573; p < 0.001), and altered values of the TBS Z-score were associated with the severity of vertebral fractures. Finally, in a linear regression-adjusted model, the VAT index predicted TBS lumbar spine L1-L4 (β -0.323; p < 0.001). In patients with OSA VAT impacts bone quality. In these patients, the role of VAT as a metabolically active tissue should be considered.

Metabolic age is defined as an estimation of a person's age based on their basal metabolic rate (BMR) and other physiological health indicators. Unlike chronological age, which simply measures the number of years lived since birth, metabolic age is based on various health and fitness markers that estimate the body's "true" biological age and can be assessed using various methodologies, including bioimpedance. The aim of this study was to evaluate how age, sex, social class, smoking habits, physical activity, and adherence to the Mediterranean diet influence metabolic age.

A cross-sectional, descriptive study was conducted on 8590 Spanish workers in the Balearic Islands. A series of sociodemographic variables and health-related habits were assessed, while metabolic age was measured using bioimpedance. A metabolic age exceeding chronological age by 12 years or more was considered high. A descriptive analysis of categorical variables was performed by calculating their frequency and distribution. By applying multivariate models, specifically multinomial logistic regression, we observe that all independent variables (sex, age, social class, physical activity, mediterranean diet, and smoking) show varying levels of association with the occurrence of high metabolic age values. Among these independent variables, those showing the highest degree of association, represented by odds ratios, are physical activity, adherence to the Mediterranean diet, and social class. In all cases, the observed differences demonstrate a high level of statistical significance (p < 0.001).

The factors with the greatest influence were physical inactivity, with an OR of 5.07; and low adherence to the Mediterranean diet, with an OR of 2.8; followed by social class, with an OR of 2.51. Metabolic age increased with chronological age and was higher in males, with an OR of 1.38. Smoking also had a negative impact on metabolic age, with an OR of 1.19.

Mediterranean diet is associated with a higher metabolic age. The most influential factors on metabolic age are physical activity and adherence to the Mediterranean diet, followed by the individual's socioeconomic class. Smoking also contributes to increased metabolic age, albeit to a lesser extent.

Whether excess visceral fat tissue increases the risk of death in older individuals remains controversial.

To investigate the association between the Chinese Visceral Adiposity Index (CVAI) and all-cause mortality risk in older Chinese individuals.

This cohort study utilized data of individuals aged ≥ 65 years in 2014 to 2018 wave from the Chinese Longitudinal Healthy Longevity Survey database. Older individuals in the 2014 wave were included and followed up in 2018. CVAI was calculated based on age, body size, and blood lipid parameters, with higher values indicating increased visceral fat. Survival status was determined from official death certificates, local primary healthcare providers, or the family members of participants. Kaplan-Meier survival curve and log-rank test were employed to analyze cumulative mortality risk through CVAI tertiles (tertile 1: CVAI index < 97.34; tertile 2: 97.43 ≤ CVAI index < 132.21; and tertile 3: CVAI index ≥ 132.21). A Cox proportional hazards regression model was used to assess the relationship between the CVAI groups and all-cause mortality risk. Additionally, a sensitivity analysis was performed by excluding participants who died within the first year of follow-up. A subgroup analysis was performed based on age and sex, and a restricted cubic spline plot was created to analyze the dose-response relationship between CVAI and mortality risk.

A total of 1414 individuals were included, and the mean age of the participants was 84.6 (standard deviation: 10.9) years, of which 46.4% were women and 32.8% were died during a median follow-up time of 36.4 months. In the multivariable adjusted Cox regression model, we observed a significantly lower risk of mortality in the CVAI tertile 2 and 3 groups than in the tertile 1 group. The hazard ratios (HR) of the tertile 2 and 3 groups were 0.68 (95% CI, approximately 0.52-0.89) and 0.63 (95% CI, approximately 0.48-0.82), respectively. Subgroup analysis revealed that the protective effect of higher CVAI levels on mortality was more pronounced in participants aged 65-79 years and in women.

Our study established a linear relationship between CVAI and mortality risk among community-dwelling older adults, with higher CVAI levels associated with a lower risk of all-cause mortality. These findings highlight the potential importance of visceral adiposity in predicting mortality risk in community-dwelling older adults.

Traditional metrics such as body mass index (BMI) and waist circumference (WC) fail to accurately assess the health outcomes associated with abdominal adiposity, because they neglect the intricacies of adipose tissue distribution. Notably, the variability in body composition scaled to height remains underexplored in Chinese demographics. This study introduces height-normalised indices of abdominal adiposity using computed tomography (CT) scans and further assesses their associations with various health outcomes.

In a large, diverse Chinese population (n = 1054 healthy individuals; n = 1159 with dyslipidemia; n = 803 with diabetes; n = 1289 with cardio-cerebrovascular diseases; n = 1108 with cancers; and n = 509 with abnormal bone mas), abdominal CT scans were performed and allometric growth model analyses were used to derive height-normalised indices (body composition/heightβ). Logistic regression models assessed the associations between these indices and health outcomes.

Distinct scaling powers were observed for visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and total abdominal adipose tissue (TAT), as well as for sagittal diameter (SAD), with marked sex differences. Powers for VAT were 1.786 ± 1.270 for males and 1.274 ± 0.692 for females. Powers for SAT were 2.266 ± 0.856 for males and 1.656 ± 0.497 for females. Powers for TAT were 2.141 ± 0.967 for males and 1.438 ± 0.489 for females. Powers for SAD were 0.646 ± 0.217 for males and 0.678 ± 0.141 for females. After controlling for age, BMI and WC, VAT/heightβ, TAT/heightβ and SAD/heightβ retained their significantly positive associations with the odds of health outcomes, whereas SAT/heightβ did not.

Our findings endorse the clinical utility of height-normalised indices, particularly VAT/heightβ, TAT/heightβ and SAD/heightβ, in health outcomes assessment. These indices, grounded in robust empirical data, underscore the necessity of a nuanced approach in obesity-related health evaluations, advocating for a departure from conventional methods like BMI.

Cushing's syndrome (CS) is associated with increased risk for heart failure, which often initially manifests as left ventricular diastolic dysfunction (LVDD). In this study, we aimed to explore the potential risk factors of LVDD in CS by incorporating body composition parameters.

A retrospective study was conducted on patients diagnosed with endogenous CS no less than 18 years old. The control group consisted of healthy individuals who were matched to CS patients in terms of gender, age, and BMI. LIFEx software (version 7.3) was applied to measure epicardial adipose tissue volume (EATV) on non-contrast chest CT, as well as abdominal adipose tissue and skeletal muscle mass at the first lumbar vertebral level. Echocardiography was used to evaluate left ventricular (LV) diastolic function. Body compositions and clinical data were examined in relation to early LVDD.

A total of 86 CS patients and 86 healthy controls were enrolled. EATV was significantly higher in CS patients compared to control subjects (150.33 cm3 [125.67, 189.41] vs 90.55 cm3 [66.80, 119.84], p < 0.001). CS patients had noticeably increased visceral fat but decreased skeletal muscle in comparison to their healthy counterparts. Higher prevalence of LVDD was found in CS patients based on LV diastolic function evaluated by E/A ratio (p < 0.001). EATV was proved to be an independent risk factor for LVDD in CS patients (OR = 1.015, 95%CI 1.003-1.026, p = 0.011). If the cut-point of EATV was set as 139.252 cm3 in CS patients, the diagnostic sensitivity and specificity of LVDD were 84.00% and 55.60%, respectively.

CS was associated with marked accumulation of EAT and visceral fat, reduced skeletal muscle mass, and increased prevalence of LVDD. EATV was an independent risk factor for LVDD, suggesting the potential role of EAT in the development of LVDD in CS.

Background: Diabetic peripheral neuropathy (DPN) impacts approximately 50% of individuals with Type 2 diabetes mellitus (T2DM), leading to severe complications such as foot ulcers and amputations. Notably, visceral adiposity is increasingly recognized as a pivotal factor in augmenting the risk of DPN. We aim to evaluate the correlation between obesity-related body composition, particularly visceral fat, and DPN to facilitate early identification of high-risk patients with T2DM. Methods: This cross-sectional analysis encompassed 113 T2DM patients from the Department of Endocrinology and Metabolism at the Second Affiliated Hospital of Fujian Medical University, conducted between September 2020 and January 2021. Patients were categorized into two cohorts: those with DPN (DPN group) and those without (NDPN group). We utilized bioelectrical impedance analysis (BIA) to determine body measurements, such as weight and visceral fat area, in addition to collecting clinical and biochemical data. Logistic regression was employed to analyze the data. Results: The study uncovered a statistically significant difference in the visceral fat area between the DPN and NDPN groups (p = 0.048). Through multivariate logistic regression analysis, the visceral fat area was identified as an independent risk factor for DPN among T2DM patients (OR 1.027; 95% CI 1.004-1.051, p = 0.022). Other significant risk factors included the duration of diabetes and the presence of diabetic retinopathy. Conclusion: The visceral fat area serves as an independent risk factor for DPN in individuals with T2DM. Implementing measures to assess and manage visceral obesity could be vital in the prevention and management of DPN. This underscores the value of technologies such as BIA in clinical and community settings for early intervention.

This study aims to investigate the association of Chinese visceral adiposity index (CVAI) with incident hyperuricemia (HUA).

We included 5186 adults aged ≥45 years from China Health and Retirement Longitudinal Study. Modified Poisson regression model was used to estimate the relative risks (RRs) of incident HUA associated with baseline CVAI, and logistic model was used to estimate the odds ratios (ORs) of HUA for CVAI change. Restricted cubic splines analysis was adopted to model the dose-response associations. The area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the predictive value of CVAI. During 4-year follow-up, a total of 510 (9.8%) HUA cases were identified. The RRs (95%CIs) of incident HUA were 3.75 (2.85-4.93) for quartile 4 versus quartile 1 and 1.56 (1.45-1.69) for per-standard deviation increase in baseline CVAI. For the analyses of CVAI change, compared with stable group, participants in decreased group had 34% lower risk (OR 0.66, 95%CI 0.49-0.87) and those in increased group had 35% (1.35, 1.03-1.78) higher risk of HUA. Linear associations of baseline CVAI and its change with HUA were observed (Pnonlinear >0.05). Besides, the AUC value for HUA was 0.654 (0.629-0.679), which was higher than other five obesity indices.

Our study found linear associations between baseline CVAI and its change and risk of HUA. CVAI had the best predictive performance in predicting incident HUA. These findings suggest CVAI as a reliable obesity index to identify individuals with higher HUA risk.

Metabolic Score for Visceral Fat (METS-VF) is a novel indicator for estimating intra-abdominal fat, yet its connection with coronary artery calcification (CAC) remains uncharted. Our research aims to explore the novel METS-VF indicator's link to CAC while comparing its performance against relevant anthropometric indices.

This study enrolled participants who underwent health checkups and computed tomography scans for categorizing severity of CAC using the coronary artery calcium score. The METS-VF was calculated and compared with anthropometric indices in estimating the presence of CAC and different CAC severity using receiver operating characteristic curves.

Overall, 1217 participants (mean age 50.7 ± 9.9, 53.8% male) were included. METS-VF (odds ratio [OR], 1.506; 95% confidence interval [CI], 1.181-1.921; p = 0.001) was positively associated with the presence of CAC, even after accounting for cardiometabolic factors. Notably, METS-VF was positively associated with mild (OR, 1.450; 95% CI, 1.115-1.886; p = 0.006), moderate (OR, 1.865; 95% CI, 1.137-3.062; p = 0.014), and severe (OR, 2.316; 95% CI, 1.090-4.923; p = 0.029) CAC. Moreover, METS-VF yielded the highest area under curve (AUC) value in the estimation of the CAC presence (AUC = 0.710), mild (AUC = 0.682), moderate (AUC = 0.757), and severe (AUC = 0.807) CAC when compared with body mass index, waist circumference, visceral adiposity index, triglyceride-glucose index, and metabolic score for insulin resistance. The optimal METS-VF cut-off value was 6.4 for predicting CAC.

METS-VF emerged as a strong independent marker for detecting CAC presence across mild, moderate, and severe CAC categories, outperforming major anthropometric indices in accurately estimating the presence of CAC and different severity of CAC.

Not all type 2 diabetes mellitus (T2DM) patients exhibit insulin resistance (IR). Our objective is to identify the most effective sex-specific index for predicting IR in T2DM. This will be achieved through a comparative analysis of the sex-specific attributes of waist to hip circumference ratio (WHR), visceral fat area to hip circumference ratio (VHR), and visceral fat area to subcutaneous fat area ratio (VSR).

Receiver operating characteristic curve analysis was conducted to estimate the area under the curve for WHR, VHR, and VSR. Subsequently, logistic regression was employed to analyze the relationship between VHR and IR.

There were significant differences between males and females in anthropometric measurements, biochemical data, and obesity prevalence. ROC analysis revealed that the area under the curve (AUC) for predicting male IR was 0.67, 0.71, and 0.62 for WHR, VHR, and VSR, respectively. For females, the AUC values were 0.63, 0.69, and 0.60, respectively. In multivariate logistic regression analysis, adjusting for confounding factors, compared to the lowest tertile of VHR, the odds ratio (OR) of the highest tertile was 2.2 (95% CI: 1.47-3.3, P<0.001) for males and 2.1 (95% CI: 1.24-3.57, P=0.005) for females.

VHR emerges as the most reliable predictor of IR risk in individuals with T2DM.

Body measurements are primarily made with a tape measure. In measurements taken with a tape measure, the inability to take measurements from the same part of the body each time, incorrect positioning of the tape measure, the occurrence of incorrect measurements, and the need for a person to take the measurements are significant problems in the traditional measurement method. Due to the social distancing rule that must be followed during the Covid-19 pandemic, the close contact between the person to be measured and the person taking the measurement became the starting point of this study. This study focuses on the detecting body shape changes using image processing techniques with 2D imaging. The novelty of the work is that non-contact body measurements are taken more accurately and reliably using the cosine theorem. Regular monitoring of obese patients is important in combating obesity, which is also the source of many health problems. In the monitoring of obese patients, it is necessary to determine the rate of slimming in areas where fat accumulation is intense. The error margin between the real measurements of human models and the calculated measurements was calculated as an average of ± 5.16% for waistline and an average of ± 4.58% for hip size. The cosine theorem was used instead of the ellipse formula used in the literature, and it was observed that the cosine theorem obtained results closer to reality. It is also thought that the developed system will be beneficial not only for extracting body measurements but also for extracting body measurements contactless in the textile sector. The study demonstrates the feasibility of image processing for non-contact body anthropometry and shape tracking.

We aim to investigate the association between body roundness index (BRI) and abdominal aortic calcification (AAC) among middle aged and elderly US residents.

This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 cycle, including 3,079 middle-aged and elderly participants aged 40 and above. AAC scores for these participants were assessed using dual-energy x-ray absorptiometry (DXA). BRI was calculated from participants' height and waist circumference, with all measurements conducted by trained surveyors using standardized methods. The relationship between BRI and AAC was analyzed using weighted multivariate logistic regression, adjusting for confounding variable. Additionally, restricted cubic splines (RCS) analysis was also employed.

We found that those with AAC were significantly older and had a higher prevalence of smoking and chronic kidney disease (CKD) prevalence compared to those without AAC. Using weighted multivariable logistic regression, we determined that an increase of one unit in BRI was associated with a 22% higher risk of AAC. Additionally, higher BRI quartiles (Q2, Q3, Q4) showed significantly increased risks of AAC compared to the lowest quartile. Visualization using RCS indicated a gradual increase in AAC risk with higher BRI, which plateaued beyond a BRI of 7.2. This relationship was significant across different age and gender group.

There is a positive association between abdominal obesity (as measured by BRI) and AAC in the middle-aged and elderly population. This suggests the impact of abdominal obesity on vascular health and that this factor should be considered in public health strategies.

Background/Objectives: The prevalence of metabolic syndrome (MetS) is increasing worldwide, and an increasing number of cases are diagnosed in younger age groups. This study aimed to propose predictive models based on demographic, anthropometric, and non-invasive clinical variables to predict MetS in adolescents. Methods: A total of 2064 adolescents aged 18-19 from São Luís-Maranhão, Brazil were enrolled. Demographic, anthropometric, and clinical variables were considered, and three criteria for diagnosing MetS were employed: Cook et al., De Ferranti et al. and the International Diabetes Federation (IDF). A feed-forward artificial neural network (ANN) was trained to predict MetS. Accuracy, sensitivity, and specificity were calculated to assess the ANN's performance. The ROC curve was constructed, and the area under the curve was analyzed to assess the discriminatory power of the networks. Results: The prevalence of MetS in adolescents ranged from 5.7% to 12.3%. The ANN that used the Cook et al. criterion performed best in predicting MetS. ANN 5, which included age, sex, waist circumference, weight, and systolic and diastolic blood pressure, showed the best performance and discriminatory power (sensitivity, 89.8%; accuracy, 86.8%). ANN 3 considered the same variables, except for weight, and exhibited good sensitivity (89.0%) and accuracy (87.0%). Conclusions: Using non-invasive measures allows for predicting MetS in adolescents, thereby guiding the flow of care in primary healthcare and optimizing the management of public resources.

Morbid obesity, as characterized by BMI, is often utilized as an exclusion criterion for VV-ECMO because of presumed poor prognosis and technically complex cannulation. However, the "obesity paradox" suggests obesity may be protective during critical illness, and BMI does not capture variations in body type, adiposity, or fluid balance. This study examines relationships between BMI and patient outcomes. Adult VV-ECMO patients with BMI ≥ 35 kg/m2 admitted January 2012 to June 2021 were identified from an institutional registry. BMI and outcomes were analyzed with Mann-Whitney U tests and Pearson correlations with Bayesian post-hoc analyses. 116 of 960 ECMO patients met inclusion criteria. Median (Q1, Q3) BMI was 42.3 (37.3, 50.8) and min, max of 35.0, 87.8 with 9.0 (5.0, 15.5) ECMO days. BMI was not significantly correlated with ECMO days (r = -0.102; p = .279). Bayesian analyses showed moderate evidence against BMI correlating with ECMO days. In-hospital mortality (27%) was significantly associated with ECMO days (p = .014) but not BMI (p = .485). In this cohort of high-BMI patients, BMI was not associated with survival or time on ECMO. BMI itself should not be used as an exclusion criterion for VV-ECMO.

(1) Background: This study aims to assess visceral fat values, waist circumference (WC), body mass index (BMI), and body fat percentage for their ability to predict poor outcomes during COVID-19 patients' hospitalization; (2) Methods: This study was a prospective cohort of mild-moderate COVID-19 patients hospitalized at Dr. Cipto Mangunkusumo National General Hospital from December 2020 to March 2021. This study includes hospitalized patients over 18 diagnosed with COVID-19 using RT-PCR. Patients who do not have chest radiography, waist circumference, a bioimpedance analyzer (BIA) error, or are unable to stand or mobilize during the examination are excluded from this study. Cox regression was used for multivariate analysis; (3) Results: The study included two hundred sixty-one patients. The median visceral fat value was 10 (equivalent to 100 cm2), the WC was 93.4 cm, the BMI was 26.1 kg/m2, and the body fat percentage was 31.5%. Based on multivariate Cox regression, WC was statistically significant as an independent factor influencing poor outcomes in COVID-19 patients (RR 1.037 [95% CI 1.011-1.064]) along with COVID-19 degree of severity (RR 3.063 [95% CI 1.537-6.104]) and comorbidities (RR 2.123 [95% CI 1.017-4.435]); (4) Conclusions: Waist circumference can influence poor outcomes in confirmed COVID-19 patients during hospitalization.

This study aimed to evaluate the relationship between the weight-adjusted waist circumference index (WWI) and the frailty in American adults aged over 60 years.

We utilized data from the National Health and Nutrition Examination Surveys (NHANES) spanning from 2007 to 2018. WWI was calculated using the square root of waist circumference (cm) divided by body weight (kg). The frailty index ≥ 0.25 was employed to assess frailty. Weighted multivariate logistic regression was conducted to explore the association between WWI and frailty. Generalized Additive Modeling (GAM) was used to explore potential non-linear relationships. Receiver operating characteristic curve (ROC) analysis was used to assess the predictive ability of WWI for frailty.

The study encompassed 7765 participants. Higher WWI was significantly associated with higher odds of frailty. In the fully adjusted model, each unit increase of WWI was associated with an 82% increased odds of frailty (OR: 1.82, 95% CI: 1.61 - 2.06; P < 0.001). GAM found significant nonlinear relationships and threshold effects.

The study presented a robust correlation between elevated WWI and increased odds of frailty among American older adults. However, these findings require further validation in large-scale, prospective studies.

To evaluate if ileo-psoas muscle size and visceral adipose tissue (VAT) can predict long-term survival after endovascular aneurysm repair (EVAR).

Patients who underwent EVAR between 2004 and 2012 in a single centre were included. Total psoas muscle area (TPA), abdominal VAT area, subcutaneous adipose tissue (SAT), and total adipose tissue were measured on the preoperative CT. Primary endpoint was all-cause mortality. Values are presented as median and interquartile range or absolute number and percentage. Cox regression analyses were performed to assess the associations with mortality.

Two hundred and eighty-four patients could be included in the study. During a median follow-up of 8 (4-11) years, 223 (79.9%) patients died. Age (P ≤ .001), cardiovascular (P = .041), cerebrovascular (P = .009), renal diseases (P = .002), and chronic obstructive pulmonary disease (P ≤ .001) were independently associated with mortality. TPA was associated with mortality in a univariate (P = .040), but not in a multivariate regression model (P = .764). No significant association was found between mortality and TPA index (P = .103) or any of the adiposity measurements with the exception of SAT (P = .040). However, SAT area loss in a multivariate analysis (P = .875).

Assessment of core muscle size and VAT did not contribute to improving the prediction of long-term survival after EVAR.

The finding of this study contradicts the previously claimed utility of core muscle size and VAT in predicting long-term survival after EVAR.

The weight-adjusted waist index (WWI) is a quantitative anthropometric index that can be applied to evaluate obesity. This study examined the relationship between adult United States (US) residents' risk of diabetes mellitus type 2 (T2DM) and WWI.

The NHANES (National Health and Nutrition Examination Survey) 2001-2018 provided the data for this investigation. This study used multifactorial logistic regression analysis, smoothed curve fitting, subgroup analysis, and interaction tests to assess the association between WWI and T2DM. Additionally, threshold effects were calculated using a two-stage linear regression model. The receiver operating characteristic(ROC) curves evaluated the diagnostic ability of the WWI and commonly used obesity indicators.

20,477 participants were enrolled in the analysis, and patients with greater levels of WWI had a higher prevalence of T2DM. WWI and T2DM have a non-linear relationship, with a positive association found on the left side of the breakpoint (WWI = 12.35) (OR = 1.82, 95%CI:1.64-2.02), whereas, on the right side, no such relationship was found (OR = 0.9, 95%CI:0.61-1.34). For every unit rise in WWI, the probability of having T2DM increased by 67% after controlling for all other variables (OR:1.67,95%CI:1.53-1.83). Based on subgroup analyses, individuals under 40 had a higher correlation between WWI and T2DM (P < 0.001).ROC analyses showed that WWI had the best discrimination and accuracy in predicting T2DM compared to other obesity indicators (WC, BMI, and Weight).

Higher WWI values had a higher prevalence of T2DM in US individuals, especially in adults under 40. WWI has the strongest ability to predict T2DM. Therefore, the importance of WWI in the early identification of T2DM in US adults should be emphasized.

Current research offers limited clarity on the correlation between waist circumference and chronic pain prevalence.

This investigation seeks to elucidate the potential relationship between waist circumference and chronic pain and their causal association.

An observational study was conducted, leveraging data from the National Health and Nutrition Examination Survey (NHANES) collected between 2001 and 2004. The multivariable logistic regression was used to assess the relationship between waist circumference and chronic pain. Furthermore, a meta-analysis of Mendelian Randomization (MR) was applied to explore a causal relationship between waist circumference and pain.

The observational study, post multivariable adjustment, indicated that an increase in waist circumference by 1 dm (decimeter) correlates with a 14% elevation in chronic pain risk (Odds Ratio [OR] = 1.14, 95% Confidence Interval [CI]: 1.04-1.24, p = 0.01). Moreover, the meta-analysis of MR demonstrated that an increased waist circumference was associated with a genetic predisposition to pain risk (OR = 1.14, 95%CI: 1.06-1.23, p = 0.0007).

Observational analysis confirmed a significant relationship between increased waist circumference and the incidence of chronic pain, and results based on MR Study identified increased waist circumference as potentially causal for pain.