Assessment of the appropriate cutoff points for anthropometric indices and their relationship with cardio-metabolic indices to predict the risk of metabolic associated fatty liver disease.

BACKGROUND: Research on Metabolic Associated Fatty Liver Disease (MAFLD) is still in its early stages, with few studies available to identify and predict effective indicators of this disease. On the other hand, early diagnosis and intervention are crucial to reduce the burden of MAFLD. Therefore, the aim of this research was to investigate the effectiveness of eleven anthropometric indices and their appropriate cut-off values as a non-invasive method to predict and diagnose MAFLD in the Iranian population. METHODS: In this cross-sectional study, we analyzed baseline data from the Hoveyzeh Cohort Study, a prospective population-based study conducted in Iran that enrolled a total of 7836 subjects aged 35 to 70 years from May 2016 through August 2018. RESULTS: The optimal cut-off values of anthropometric indices for predicting MAFLD risk were determined for waist circumference(WC) (102.25 cm for males and 101.45 cm for females), body mass index (BMI) (27.80 kg/m2 for males and 28.75 kg/m2 for females), waist-to-hip ratio (WHR) (0.96 for both males and females), waist-to-height ratio (WHtR) (0.56 for males and 0.63 for females), body adiposity index (BAI) (23.24 for males and 32.97 for females), visceral adiposity index (VAI) (1.64 for males and 1.88 for females), weight-adjusted waist index (WWI) (10.63 for males and 11.71 for females), conicity index (CI) (1.29 for males and 1.36 for females), body roundness index (BRI) (4.52 for males and 6.45 for females), relative fat mass (RFM) (28.18 for males and 44.91 for females) and abdominal volume index (AVI) (18.85 for males and for 21.37 females). VAI in males (sensitivity: 77%, specificity: 60%, Youden's Index: 0.37) and RFM in females (sensitivity: 76%, specificity: 59%, Youden's Index: 0.35) were found to have higher sensitivity and specificity compared to other anthropometric indices. Furthermore, anthropometric indices demonstrated statistically significant correlations with various hepatic and cardiometabolic indices. Among these, the strongest positive correlations were observed between WC, BMI, BAI, BRI, and AVI with the Hepatic Steatosis Index (HSI), TyG-BMI, and TyG-WC, as well as between VAI and the Atherogenic Index of Plasma (AIP), Lipid Accumulation Product (LAP), Cardiometabolic Index (CMI), and the Triglyceride and Glucose (TyG) Index. CONCLUSION: Anthropometric indices are effective in predicting MAFLD risk among Iranian adults, with WWI, VAI, and RFM identified as the strongest predictors. The proposed cutoff values could serve as a straightforward and non-invasive methods for the early diagnosis of MAFLD.

Correlation of anthropometric measurements with body mass index and estimation of the proportion of metabolic syndrome among overweight and obese children: a hospital-based cross-sectional study.

BACKGROUND: Early identification of overweight and obesity with the help of simple anthropometric tests can prevent from development of metabolic complications in these children. Body mass index (BMI) is the most commonly used parameter but, measurements such as waist circumference (WC), waist-to-height ratio (WHtR) and wrist circumference (WrC) have also been studied and found to have a better correlation with visceral fat. OBJECTIVE: To correlate WC, WHtR and WrC with BMI among overweight and obese children. The secondary objective was to estimate the proportion of metabolic syndrome among obese and overweight children. METHODS: A single-centre, cross-sectional study involving 80 overweight and obese children aged 3-15 years. Anthropometric measures such as WC, WHtR and WrC of the study subjects were correlated with BMI and investigated for metabolic syndrome. RESULTS: Statistically significant and moderate positive correlation was found between BMI and WC, r (80)=0.45 and p<0.001 with WC explaining 20% of the variation of BMI. There was a statistically significant, moderate positive correlation between WHtR and BMI r (80)=0.34 and p<0.001 with 11% of the variation in BMI. There was a statistically significant strong positive correlation between WC and WrC (80)=0.61 and p<0.001, and WrC explains 37.2% of the variation in WC. However, there was no statistically significant correlation between BMI and WrC. Metabolic syndrome was found in 13 (16.25%) children. CONCLUSION: Alternative anthropometric measurements such as WC and WHtR have a significant correlation with BMI and may be of help in defining overweight and obesity in children. There was a statistically significant strong positive correlation between WC and WrC among obese children. Metabolic syndrome is common in these children.

Multiple factor assessment for determining resting metabolic rate in young adults.

Existing formulas cannot fully explain the variation of resting metabolic rate (RMR). This study aims to examine potential influencing factors beyond anthropometric measurements and develop more accurate equations using accessible parameters. 324 healthy adults (230 females; 18-32 years old) participated in the study. Height, fat-free mass (FFM), fat mass (FM) and RMR were measured. Menstrual cycle, stress levels, living habits, and frequency of consuming caffeinated foods were collected. Measured RMR were compared with predictive values of the new equations and previous 11 equations. Mean RMR for men and women was 1825.2 ± 248.8 and 1345.1 ± 178.7 kcal/day, respectively. RMR adjusted for FFM0.66FM0.066 was positively correlated with BMI. The multiple regression model showed that RMR can be predicted in this population with model 1 (with FFM, FM, age, sex and daily sun exposure duration) or model 2 (with weight and height replacing FFM and FM). The accuracy was 75.31% in the population for predictive model 1 and 70.68% for predictive model 2. The new equations had overall improved performance when compared with existing equations. The predictive formula that consider daily sun exposure duration improve RMR prediction in young adults. Additional investigation is required among individuals in the middle-aged and elderly demographic.

Evaluation of the relationship between dietary energy and protein intakes and anthropometric measurements in hemodialysis patients.

This study evaluated the relationship between dietary energy, and protein (animal and plant based) intakes and anthropometric measurements in maintenance hemodialysis (MHD) patients. Individuals between the ages of 19 to 65 who received MHD treatment for more than 3 months from October 2021 to February 2022 in the state hospitals were included in the study. Body mass index (BMI) (kg/m2) was calculated for each patient, and anthropometric measurements including upper middle arm circumference, triceps skinfold thickness (TST) and hand grip strength (HGS) were carried out. 3-day food records and Subjective Global Assessment (SGA) were used to assess nutritional status of the patients. Of the 51 MHD patients included in the study, 33 (64.7%) were male and 18 (35.3%) were female. The mean age of the patients was 50.37 ±â€…11.55 years, and length of time on MHD was 39.49 ±â€…51.68 months. The mean energy intake of female and male MHD patients was 20.01 ±â€…6.94 and 17.26 ±â€…6.24 kcal/kg/d, respectively. The mean dietary protein intake of female and male MHD patients were 0.84 ±â€…0.35 and 0.78 ±â€…0.30 g/kg/d, respectively. Dry weight (P = .048), BMI (P = .020), TST (P = .013), and HGS (P = .026) of well-nourished and moderately malnourished female MHD patients according to SGA results were found to be lower than in male patients. While the majority of the patients receiving MHD treatment appeared to be well-nourished according to the SGA results, energy and protein intakes obtained from the food records were below the recommended daily dietary intake. These evaluations affected the anthropometric measurements including HGS, BMI, and TST. Therefore, there is a need for more comprehensive clinical studies in which anthropometric measurements, food consumption, biochemical findings and nutritional screening tools are used all together to evaluate nutritional status in MHD patients.

Anthrometric dimensions and their impact on cardiovascular risk factors.

Central obesity is an important risk factor for cardiovascular disease. The abdominal subcutaneous adipose tissue thickness (ASATT) can be used to evaluate central obesity. The objective of this study was to compare ASATT with cardiovascular risk factors and other anthropometric parameters to show that ASATT can be a useful tool for the early assessment of heart disease risk. In this observational cross-sectional study, anthropometric measurements of 100 autopsied decedents, including waist circumference, hip circumference, waist/height and waist/hip ratio, aortic outlet and coronary artery atheroma plaque densities, heart weight, ventricular wall thickness, and ASATT, were assessed. The research data were evaluated using the Statistical Package for the Social Sciences for Windows 25.0. The average ASATT of the male group was 40.36 mm (SD: 11.00), and the average of female cases was 46.34 mm (SD: 18.12). There was no statistically significant difference between the sexes and both age groups in terms of the ASATT score (P > .05). There was a positive correlation between ASATT and waist circumference, hip circumference, and waist/height ratio in both sexes (P < .05). While ASATT was not related to atheroma density in the coronary arteries of men (P > .05), it was correlated with atheroma density in all 3 coronary arteries of women (P < .05). In the male group, the aortic inner surface atheroma density was positively correlated with ASATT (P < .05). In both sexes, there was a positive correlation (P < .05) between ASATT and heart weight; however, no such correlation was observed with right and left ventricular wall thickness (P > .05). ASATT is related to other anthropometric measurements, atherosclerosis of critical vessels, and heart weight, and can be used to scan the patient population for heart disease risk assessment with noninvasive methods.

Can thoraco-abdominal organ boundaries be accurately determined from X-ray and anthropometric surface scans? Implications for body armour system coverage and design.

To optimise soldier protection within body armour systems, knowledge of the boundaries of essential thoraco-abdominal organs is necessary to inform coverage requirements. However, existing methods of organ boundary identification are costly and time consuming, limiting widespread adoption for use on soldier populations. The aim of this study was to evaluate a novel method of using 3D organ models to identify essential organ boundaries from low dose planar X-rays and 3D external surface scans of the human torso. The results revealed that, while possible to reconstruct 3D organs using template 3D organ models placed over X-ray images, the boundary data (relating to the size and position of each organ) obtained from the reconstructed organs differed significantly from MRI organ data. The magnitude of difference varied between organs. The most accurate anatomical boundaries were the left, right, and inferior boundaries of the heart, and lateral boundaries for the liver and spleen. Visual inspection of the data demonstrated that 11 of 18 organ models were successfully integrated within the 3D space of the participant's surface scan. These results suggest that, if this method is further refined and evaluated, it has potential to be used as a tool for estimating body armour coverage requirements.

Facial modeling and measurement based upon homologous topographical features.

Measurement of human faces is fundamental to many applications from recognition to genetic phenotyping. While anthropometric landmarks provide a conventional set of homologous measurement points, digital scans are increasingly used for facial measurement, despite the difficulties in establishing their homology. We introduce an alternative basis for facial measurement, which 1) provides a richer information density than discrete point measurements, 2) derives its homology from shared facial topography (ridges, folds, etc.), and 3) quantifies local morphological variation following the conventions and practices of anatomical description. A parametric model that permits matching a broad range of facial variation by the adjustment of 71 parameters is demonstrated by modeling a sample of 80 adult human faces. The surface of the parametric model can be adjusted to match each photogrammetric surface mesh generally to within 1 mm, demonstrating a novel and efficient means for facial shape encoding. We examine how well this scheme quantifies facial shape and variation with respect to geographic ancestry and sex. We compare this analysis with a more conventional, landmark-based geometric morphometric (GMM) study with 43 landmarks placed on the same set of scans. Our multivariate statistical analysis using the 71 attribute values separates geographic ancestry groups and sexes with a high degree of reliability, and these results are broadly similar to those from GMM, but with some key differences that we discuss. This approach is compared with conventional, non-parametric methods for the quantification of facial shape, including generality, information density, and the separation of size and shape. Potential uses for phenotypic and dysmorphology studies are also discussed.

Ethnic variation in lower face anthropometry on facial computed tomography scans for patients seeking facial feminization surgery.

BACKGROUND: Facial feminization surgery (FFS) is the most common form of facial gender-affirming surgery. One of the current knowledge gaps is the understanding of differences among racial groups in baseline craniofacial norms for transgender and nonbinary patients. METHODS: All patients who sought consultation for FFS and underwent craniofacial computed tomography (CT) scans at a single institution between 2018 and 2023 were included. Patients who underwent previous facial surgeries were excluded. Chart reviews were conducted for patient characteristics, including race, age, hormone therapy duration, and prior gender-affirming surgeries. Racial categorizations included White, Latinx, African American, or Asian. Patients with other or multiracial identities were excluded. Lower face measurements were derived from preoperative facial CT scans. Comparative analyses were performed on all measurements among the racial groups. RESULTS: In this study, 204 patients were included with an average age of 32.0 ± 10.2 years and a median hormone therapy duration of 2.0 years. The notable differences among the racial groups were: 1. Zygomatic width was the largest in Asian patients (13.5 ± 0.6 cm) compared to all other racial groups (p = 0.03), 2. Nasolabial angle was the smallest in African American patients (82.5 ± 13.1 degrees, p < 0.001), 3. Lower face height was the largest in African American patients (6.9 ± 0.7 cm, p < 0.001), and 4. Lateral mandibular flare was the largest in African American patients (0.4 ± 0.1 cm) and the smallest in Latinx patients (0.2 ± 0.1 cm, p < 0.001). CONCLUSIONS: Specific target areas of FFS should be carefully considered to account for possible baseline ethnic differences. Relative facial proportions may also be a more salient surgical planning tool in transgender and gender nonbinary patients rather than absolute measurements alone.

A deep learning-based pipeline for developing multi-rib shape generative model with populational percentiles or anthropometrics as predictors.

Rib cross-sectional shapes (characterized by the outer contour and cortical bone thickness) affect the rib mechanical response under impact loading, thereby influence the rib injury pattern and risk. A statistical description of the rib shapes or their correlations to anthropometrics is a prerequisite to the development of numerical human body models representing target demographics. Variational autoencoders (VAE) as anatomical shape generators remain to be explored in terms of utilizing the latent vectors to control or interpret the representativeness of the generated results. In this paper, we propose a pipeline for developing a multi-rib cross-sectional shape generative model from CT images, which consists of the achievement of rib cross-sectional shape data from CT images using an anatomical indexing system and regular grids, and a unified framework to fit shape distributions and associate shapes to anthropometrics for different rib categories. Specifically, we collected CT images including 3193 ribs, surface regular grid is generated for each rib based on anatomical coordinates, the rib cross-sectional shapes are characterized by nodal coordinates and cortical bone thickness. The tensor structure of shape data based on regular grids enable the implementation of CNNs in the conditional variational autoencoder (CVAE). The CVAE is trained against an auxiliary classifier to decouple the low-dimensional representations of the inter- and intra- variations and fit each intra-variation by a Gaussian distribution simultaneously. Random tree regressors are further leveraged to associate each continuous intra-class space with the corresponding anthropometrics of the subjects, i.e., age, height and weight. As a result, with the rib class labels and the latent vectors sampled from Gaussian distributions or predicted from anthropometrics as the inputs, the decoder can generate valid rib cross-sectional shapes of given class labels (male/female, 2nd to 11th ribs) for arbitrary populational percentiles or specific age, height and weight, which paves the road for future biomedical and biomechanical studies considering the diversity of rib shapes across the population.

Combining conventional and smartphone technologies to evaluate the psychomotor status in chronic malnutrition: A cross-sectional pilot study in sub-Saharan Africa.

Malnutrition remains a pressing health concern in developing nations, contributing to growth delay (stunting) and psychomotor impairments among the youth. Tanzania has the highest prevalence of stunting, yet the psychomotor status of its population has not been previously studied. To address this gap, we gathered anthropometric, nutritional, and psychomotor data from 211 children with the aim of assessing the reliability of digital tools as indicators of psychomotor performance in relation to the nutritional status. Collected anthropometric measures included middle-upper arm circumference (MUAC), triceps skinfold thickness (TST), and handgrip strength, while psychomotor variables were assessed using digital finger tapping test (DFTT), eye-tracking test (ETT), and nine-hole peg test (9HPT). Statistical analysis revealed significant associations between age and both MUAC and handgrip strength (R = 0.5, p < 0.001). Moreover, DFTT and 9HPT demonstrated a correlation with each other (p = 0.026) and with MUAC, handgrip strength, and age (p < 0.001). Notably, lower stature was independently linked to slower horizontal eye movements (p < 0.001). Findings underscores the crucial link between nutrition and psychomotor skills in Tanzanian children. Digital tests like DFTT, ETT, and the 9HPT show promise for assessing psychomotor performance. Addressing malnutrition requires comprehensive interventions. Future research should explore long-term effects of interventions in resource-limited settings.

Predictive ability of novel and traditional anthropometric measurement indices for kidney stone disease: a cross-sectional study.

BACKGROUND: The aim of our research was to examine the association of novel anthropometric indices (a body shape index (ABSI), waist-to-height ratio (WtHR), conicity index (CI) and body roundness index (BRI)) and traditional anthropometric indices (body mass index (BMI), and waist (WC)) with prevalence of kidney stone disease (KSD) in the general population of United States (U.S.). METHODS: In this study, we conducted a cross-sectional analysis among the participants in the National Health and Nutrition Examination Survey between the years 2007 and 2020. Weighted multivariable logistic regression analysis, restricted cubic spline (RCS), receiver operating characteristic (ROC) curves, and subgroup analysis were performed to analyze the association of ABSI, BRI, WtHR, CI, BMI and WC with prevalence of KSD. RESULTS: In total, 11,891 individuals were included in our study. The RCS plot shown that the linear positive association was found between ABSI, BRI, WtHR, CI, BMI and WC and KSD risk. Additionally, the ROC curve demonstrated that the area under the curve of ABSI, BRI, WtHR, and CI was significantly higher than traditional anthropometric indices, including BMI and WC. CONCLUSIONS: Our study found that the discriminant ability of ABSI, BRI, WtHR, and CI for KSD was higher than BMI and WC. Consequently, ABSI, BRI, WtHR, and CI have the potential to become new indicators for the detection of KSD risk in clinical practice.

Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis.

BACKGROUND: Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP. METHOD: The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test. RESULTS: Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678-0.784. CONCLUSIONS: This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.

Advancing athlete development: How Percentile Comparison Methods (PCMs) can identify youth developmental profiles.

OBJECTIVES: Inter-individual developmental differences confound the capability to accurately evaluate youth athletic performance, highlighting the need for considerate methodology and analytical approaches. The present study demonstrated how Percentile Comparison Methods (PCMs) were developed, tested, and applied to identify athlete developmental profiles in Australian youth swimming. DESIGN: Cross-sectional. METHODS: Participants were N = 866 female 100-metre (m) Front-Crawl swimmers, aged 9-15 years, competing at 36 Australian regional-national level long course events. At respective events, swim performance time was collated alongside, age, date of birth, and anthropometric measures to identify age group, relative age, and maturity status. Quadratic relative age and maturity status with 100-m performance regression trendlines were generated. Then, individual swim performances at a given relative age or maturity status were converted into percentile rank distributions and compared with raw (unadjusted) annual age-group performance percentile ranks. RESULTS: At a cohort level, initial testing confirmed relative age and maturity-adjusted percentile rankings were associated with general rank improvements for relatively younger and later maturing swimmers compared to raw ranks (and vice versa). When assessing individual swimmer plots, where three percentile rank scores were compared and rank change threshold criteria applied, five Percentile Comparison Method profile types were identified, namely: 'Early Developing' (19 %); 'Later Developing' (18 %); 'Consistent' (15 %); 'Mixed' (38 %) and 'Counteracting' (10 %). Percentile Comparison Method plots helped identify developmentally (dis-)advantaged swimmers; specific factors leading to (dis-)advantage, and likely onward development trajectories. CONCLUSIONS: Overall and with practical considerations, Percentile Comparison Methods can improve the validity of youth athletic performance evaluation as well as inform athlete development programming.

Adult obesity diagnostic tool: A narrative review.

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.

Feeding practices and anthropometric classification of nutritional status in low-birth-weight infants at term. A prospective cohort study.

BACKGROUND: About 50 % of LBW occurs in term newborns, which is associated with higher infant mortality rates compared to infants of average birth weight. Analysis of feeding practices in at-risk groups is essential to address malnutrition and stunting in infancy. AIM: To identify feeding practices and anthropometric classification of nutritional status in a cohort of low-birth-weight term infants. METHODS: Methods: Cohort study. A prospective follow-up of 73 term newborns with low birth weight up to six months of age was performed. Feeding practices and anthropometric classification of nutritional were analysed. Data were processed by univariate analysis and multivariate linear regression. RESULTS: The most common feeding practice was exclusive breastfeeding. Breast milk substitutes are frequent in this population group. The risk of undernutrition ranged from 2.7 % to 19.2 % and of overweight from 4.1 % to 11.0 % during the first six months of life. Low height-for-age risk was the most frequent anthropometric classification during the follow-up period. Average head circumference was consistent in infants with low birth weight. Gestational risk classification, breastfeeding during the first hour of life, and sex of the newborn were predictors of variations in anthropometric indicators. CONCLUSIONS: Exclusive breastfeeding is the most common feeding practice in the population group studied, but using breast milk substitutes is also prevalent. Low height-for-age is the most frequent anthropometric classification. The weight growth rate seems reasonable, but further studies are needed based on gender differences, analysis of the composition of breast milk, and socio-environmental factors involved in growth.

An improvement of body surface area formulas using the 3D scanning technique.

OBJECTIVES: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. MATERIAL AND METHODS: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the majority of known BSA formulas. Furthermore, it was supplement with a comparison with the authors' propositions of enhanced formulas coefficients for known formulas models as well as with new power models based on an increased number of anthropometric data. RESULTS: Introduction of the enhanced formulas coefficients cause a reduction of at least 30.5% in mean absolute error and 21.1% in maximum error in comparison with their known counterparts. CONCLUSIONS: In the context of the analysis presented it can be stated that the development of a single universal body surface area formula, based on a small number of state variables, is not possible. Therefore, it is necessary and justified to search for new estimation models that allow for quick and accurate calculation of body surface area for the entire population, regardless of individual body variations. The new formulas presented are such an alternative, which achieves better results than the previously known methods. Int J Occup Med Environ Health. 2024;37(2):205-19.

Association of novel anthropometric indices with prevalence of kidney stone disease: a population-based cross-sectional study.

BACKGROUND: The purpose of this study was to investigate the correlation between novel anthropometric indices, specifically the body shape index (ABSI) and body roundness index (BRI), and the prevalence of kidney stone disease (KSD) within the general population of the United States (U.S.). METHODS: This study employed a cross-sectional analysis of participants in the National Health and Nutrition Examination Survey from 2007 to 2020. Various statistical methods, including multivariable logistic regression analysis, restricted cubic spline (RCS) plot curve, receiver operating characteristic (ROC) curves, and subgroup analysis, were utilized to examine the association between ABSI and BRI and the risk of KSD. RESULTS: A total of 39,251 individuals were included in the study. First, the RCS plot presented that a linear positive association was found between ABSI and BRI and KSD risk. Second, the results of the multivariable logistic regression analysis revealed that, compared to the lowest quartile, the adjusted odds ratios (with 95% confidence intervals) for the prevalence of KSD across the quartiles of ASBI and BRI were 0.94 (0.67, 1.30), 1.55 (1.15, 2.10), and 1.74 (1.28, 2.35), respectively, in the fully adjusted model. Third, the ROC curve demonstrated that the area under the curve of ABSI, and BRI was significantly higher than traditional anthropometry or body composition measures, including BMI and waist circumference. CONCLUSIONS: The findings of our study indicate that the discriminant ability of ABSI and BRI for KSD is significantly superior to that of BMI and waist circumference. Consequently, ABSI and BRI have the potential to more accurately identify an individual's risk of developing KSD in a clinical setting.

Short-term chemotherapy-related complications and undernutrition in children diagnosed with cancer at Korle Bu Teaching Hospital, Accra, Ghana: A prospective cohort study.

Undernutrition in children with cancer is associated with complications during cancer therapy. The study objective was to determine the association between specific anthropometric parameters and short-term chemotherapy-related complications and mortality. This was a hospital-based, prospective cohort study of children, age ≤12 years, with a new cancer diagnosis at the Paediatric Oncology Unit, Korle Bu Teaching Hospital, Ghana. Socio-demographic information, cancer characteristics and anthropometric measurements were obtained at enrolment. Participants were followed up for twelve weeks from commencement of chemotherapy and selected treatment-related complications such as anaemia and thrombocytopenia requiring transfusions, prolonged neutropenia resulting in treatment delays, febrile neutropenia, mucositis and death were recorded. A total of 133 participants were recruited with a median age of 4.5 years. Eighty-one (60.9%) were diagnosed with solid tumours, 31 (23.3%) had leukaemias and 21 (15.8%) had lymphomas. Of the anthropometric parameters assessed, only arm anthropometry using upper arm muscle area (UAMA) and mid-upper arm circumference (MUAC) were associated with complications. Participants with wasting were more likely to develop anaemia and mucositis. However, the incidence of prolonged neutropenia was significantly higher among participants with average UAMA (p = 0.043) and low average UAMA (p = 0.049) compared to those with low UAMA. Risk of neutropenia was also significantly less among those with wasting by MUAC compared to those well-nourished (p = 0.045). Twenty-three participants (17.3%) died with a greater proportion (11/44; 25%) occurring in those who were wasted using MUAC. These findings underscore the need for nutritional surveillance at diagnosis and during chemotherapy, particularly where co-morbid disease is prevalent.

The influence of seated postures and anthropometry on lap belt fit in vehicle occupants: A 3D computed tomography study.

OBJECTIVE: In vehicle frontal collisions, it is crucial that the lap belt is designed to engage with the anterior superior iliac spine (ASIS) of occupants for a reliable restraint. This study aims to understand the influence of different seated postures on the geometrical relationship of the seat belt and the pelvis for various occupants using 3D upright and supine computed tomography (CT) systems. METHODS: The 3D shapes of bones and soft tissues around the pelvis were acquired through a CT scan for 30 participants. They were seated in a rigid seat equipped with a lap belt simulating the front seat of a small car, and wore a lap belt in three seated postures: upright, slouched and reclined. Parameters related to the likelihood of submarining occurrences, such as belt-ASIS overlap (an index for assessing the potential engagement of the lap belt with the ASIS) and the belt-pelvis angle (the difference between the belt angle and the normal direction of the anterior edge of the ilium) were compared. RESULTS: It was observed that the pelvis angle tilted rearward as the hip point was positioned forward and seatback angle increased. This can be seen in the slouched and reclined posture. The belt-pelvis angle was comparable between the slouched and the reclined postures, and was closer to zero (indicating that the lap belt path is closer to perpendicular to the anterior edge of the ilium) compared to the upright posture. In contrast, the belt-ASIS overlap increased with an increasing flesh margin of the ASIS and shallower belt angle. This suggests that the belt-pelvis angle is influenced by the seated posture whereas the belt-ASIS overlap is dependent more on an individual's anthropometry. The plot of belt-pelvis angle and belt-ASIS overlap exhibited significant variability among participants. CONCLUSIONS: The belt-pelvis angle and the belt-ASIS overlap of individuals will provide valuable information for understanding the current belt-fit location and predicting submarining occurrences for individuals in various postures when designing restraint systems.

Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors.

Measuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensional (3D) whole-body scanning can be much faster, but 3D scanning typically requires subjects to change into tight-fitting clothing, which increases time and cost and introduces privacy concerns. To address these and other issues in current anthropometry techniques, a measurement system was developed based on portable, low-cost depth cameras. Point-cloud data from the sensors are fit using a model-based method, Inscribed Fitting, which finds the most likely body shape in the statistical body shape space and providing accurate estimates of body characteristics. To evaluate the system, 144 young adults were measured manually and with two levels of military ensembles using the system. The results showed that the prediction accuracy for the clothed scans remained at a similar level to the accuracy for the minimally clad scans. This approach will enable rapid measurement of clothed populations with reduced time compared to manual and typical scan-based methods.