Traditional Anthropometric Research Articles

Raw bioelectrical impedance parameters and vector analysis in the screening of low muscle mass and low muscle mass associated with obesity in adult healthy subjects.

The aim was to estimate the prevalence of low muscle mass (LMM) and low muscle mass associated with obesity (LMM-O) in healthy adult, and to verify the performance of raw bioelectrical impedance parameters (BIA) and vector analysis (BIVA) in the screening of this tow conditions. This is a cross-sectional study including 1025 healthy adults. Body composition was assessed by the BIA technique. The appendicular skeletal muscle mass index (ASMMI) and body fat percentage (BF%) were used for the screening of LMM and LMM-O. The raw BIA parameters were: resistance (R), reactance (Xc), phase angle (PhA), and impedance (Z). The vectors, R and Xc, were adjusted for height and projected on the RXc graph. Associations were checked by the correlation test, binary logistic regression, adjusted for age and body water, and ROC curve. LMM was found in 30.8% of the subjects, and 20.9 and 21.4% of the men and women were with LMM-O. PhA and R/H were the most powerful discriminators of LMM with a sensitivity of 62-100% and a specificity of 71-90%. Cutoff values of PhA ranged between 4.95° and 5.75° for women and men. The RXc graph was able to identify LMM subjects, with clustering on the right side: area of low cellularity, high R/H and low-phase angle. Traditional anthropometric indices were the least effective in identifying LMM-O. The BIVA approach, PhA, R and R/H are effective in the screening of LMM and LMM-O, irrespective of age, gender, intra- and extracellular hydration status.

Association between adipose deposition and mortality among adults without major cardiovascular risk factors

AimTo examine the association between adiposity and mortality in U.S. adults without major cardiovascular risk factors. MethodsWe analyzed 7,948 adults (4,123 women, 3,825 men) aged > 20 years from the National Health and Nutrition Examination Survey (2003-2004, 2011-2016). Participants with cardiovascular disease, estimated glomerular filtration rate < 60 ml/min/1.73m², diabetes, hypertension, or pregnancy were excluded. Adiposity measures, assessed by dual-energy x-ray absorptiometry or anthropometrics, included android and gynoid fat mass index (FMI), android-to-gynoid ratio, subcutaneous, abdominal, and visceral FMI, BMI, and waist circumference. We employed multivariable-adjusted Cox regression and restricted cubic spline models to assess sex-specific associations between adiposity measures and all-cause mortality. ResultsOver a median follow-up of 7.8 years, there were 83 deaths among women and 119 among men. In women, BMI, waist circumference, and gynoid FMI showed non-linear associations with all-cause mortality, while in men, BMI, waist circumference, and android-to-gynoid ratio demonstrated similar non-linear associations. In final adjusted models, a 1-SD increase in visceral, subcutaneous, and abdominal FMI among women was associated with 61% (HR 1.61, 95% CI 1.17-2.21), 87% (HR 1.87, 95% CI 1.13-3.08), and 89% (HR 1.89, 95% CI 1.19-2.99) higher mortality risk, respectively. Women in the lowest tertile of gynoid FMI had an 82% (HR 1.82, 95% CI 1.01-3.29) higher mortality risk compared to those in the middle tertile. In final adjusted models, a 1-SD increase in gynoid, android, visceral, subcutaneous, and abdominal FMI among men was associated with 30% (HR 1.30, 95% CI 1.02-1.65), 41% (HR 1.41, 95% CI 1.09-1.83), 54% (HR 1.54, 95% CI 1.04-2.28), 69% (HR 1.69, 95% CI 1.25-2.29), and 76% (HR 1.76, 95% CI 1.25-2.48) higher mortality risk, respectively. Additionally, men in the middle tertile of android-to-gynoid ratio had a 2.68-fold higher mortality risk compared to the lowest tertile, while men in the highest BMI tertile had an 83% higher mortality risk compared to the lowest tertile. Sex modified the association between gynoid FMI and mortality (P-interaction = 0.008). ConclusionImaging-based adiposity measures have distinct prognostic value for mortality beyond traditional anthropometrics in adults without cardiovascular risk factors.

Association of “a body shape index” with the risk of developing colorectal cancer in U.S. patients with metabolic syndrome: evidence from the NHANES 1999–2018

BackgroundColorectal cancer (CRC) is the third most common cancer worldwide and presents a significant challenge to public health. Metabolic syndrome (MetS) is a condition that is predominantly characterized by abdominal obesity and metabolic abnormalities such as hypertension, hyperglycemia, and hyperlipidemia, and it is one of the critical risk factors for CRC. Traditional anthropometric measures have limitations in accurately assessing the risk associated with abdominal obesity. This study aimed to investigate the association between “A Body Shape Index” (ABSI) and the risk of developing CRC among individuals with MetS utilizing data from the National Health and Nutrition Examination Survey (NHANES).MethodsThis cross-sectional study conducted a statistical analysis of all adult participants who met the diagnostic criteria for MetS in the NHANES data from 1999 to 2018. The ABSI was calculated to quantify abdominal obesity. ABSI is derived from a formula that incorporates waist circumference (WC), body mass index (BMI), and height, and is calculated as ABSI = WC / (BMI^(2/3) × Height^(1/2)). Multivariate logistic regression modeling was used to examine the independent association between ABSI and CRC incidence. Receiver Operating Characteristic (ROC) curves were employed to analyze the ability of ABSI compared to traditional metrics in identifying CRC risk.ResultsThis study involved 16,018 MetS patients with a mean age of 51.8 years, of whom 50.3% were male and 49.7% were female. Logistic regression adjusted for confounders revealed a significant association between an elevated ABSI and an increased risk of developing CRC (odds ratio (OR): 1.433, 95% confidence interval (CI): 1.116 to 1.841; P = 0.005). ROC analyses confirmed that the predictive accuracy of the ABSI for the risk of developing CRC area under the curve (AUC): (0.668, 95% CI: 0.624 to 0.713) surpassed that of traditional measurement methods.ConclusionAmong individuals with MetS, the ABSI is linked to an elevated risk of developing CRC. Compared with traditional anthropometric indices, the ABSI is a superior predictive marker for the risk of developing CRC.

Body shapes of multiple anthropometric traits and all-cause and cause-specific mortality in the UK Biobank

Background: Individual traditional anthropometric measures like body mass index (BMI) and waist circumference may not fully capture the relation of adiposity to mortality. Investigating multi-trait body shapes could overcome this limitation, deepening insights into adiposity and mortality. Methods: Using UK Biobank data from 462,301 adults (40-69 years at baseline: 2006-2010), we derived four body shapes from principal component analysis on BMI, height, weight, waist and hip circumference, and waist-to-hip ratio. We then used multivariable-adjusted Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between body shapes and mortality for principal component scores of +1 and -1. Results: During 6,114,399 person-years of follow-up, 28,807 deaths occurred. A generally obese body shape exhibited a U-shaped mortality association. A tall and centrally obese body shape showed increased mortality risk in a dose-response manner (comparing a score of +1 and 0: HR=1.16; 95% CI=1.14-1.18). Conversely, tall and lean or athletic body shapes displayed no increased mortality risks when comparing a score of +1 and 0, with positive relations for the comparison between a score of -1 and 0 in these shapes (short and stout shape: HR=1.12, 95% CI=1.10-1.14; non-athletic shape: HR=1.15, 95% CI=1.13-1.17). Conclusions: Four distinct body shapes, reflecting heterogeneous expressions of obesity, were differentially associated with all-cause and cause-specific mortality. Multi-trait body shapes may refine our insights into the associations between different adiposity subtypes and mortality.

Body composition trajectories before the diagnosis of type 2 diabetes mellitus in Whitehall II study

Abstract Background The trajectories of anthropometric and body composition measures (important predictors of diabetes) are rarely explored before diabetes diagnosis. Our study aimed to compare trajectories of fat mass (FM), fat-free mass (FFM), body mass index (BMI), and waist circumference (WC) preceding type 2 diabetes mellitus (T2DM) to aging trajectories of individuals without diabetes during follow-up. Methods We used data from the Whitehall II study, a prospective cohort of British civil servants. 5-yearly BMI and WC were available for up to 20 years, while 5-yearly FM and FFM measures were available for up to 10 years. Linear mixed models with a backward timescale (from diabetes diagnosis or end of follow-up) were performed stratified by sex and adjusted for age, occupational grade, ethnicity, and lifestyle factors. Results A total of 1674/990 (anthropometric/body composition analysis) women (233/81 incident diabetes) and 3917/2710 men (479/217 incident diabetes) 49.81 [0.08]/60.91 [0.9] (mean [SE]) years of age at baseline were included. All outcomes were higher in cases compared to controls. Women’s FM, BMI, and WC followed a quadratic increase in both groups with a faster increase among incident diabetes cases (dBMI 0.04 [0.01] kg/m2/year, dFM 0.19 [0.09] kg/year, dWC 0.2 cm/year [0.05]). FFM decreased linearly with similar slopes in cases and controls. Men’s FM, BMI, and WC also showed a quadratic increase with faster increase in incident cases compared to controls (dBMI 0.03 [0.01] kg/m2/year, dFM 0.23 [0.04] kg/year, dWC 0.08 [0.02] cm/year). FFM followed a quadratic decrease in both groups with a slower rate (0.06 [0.03] kg/year) in incident cases. Conclusions Incident diabetes cases have higher anthropometric and body composition measures 10-20 years before diabetes diagnosis compared to controls. Furthermore, incident cases showed faster increases in these measures except for FFM that decreased during follow-up with similar or lower speeds in cases than controls. Key messages • Traditional anthropometric measures do not capture the underlying changes in body composition. • The inclusion of body composition in risk calculators may result in more precise diabetes prediction.

The serotonin 1A receptor promoter polymorphism, rs6295, is associated with morphofunctional features

Introduction. The tendency to weight gain is influenced by many genetic and environmental factors (nutrition, level of physical activity, social well-being, etc.), as well as complex interactions of these factors. Studying the genetic factors of obesity can help in developing individual strategies for the prevention and treatment of this common disease. One of the most important hereditary factors is the neurotransmitter systems gene polymorphism, (including the serotonin system gene polymorphism). The aim of the investigation is to study the associations of single nucleotide polymorphism of the rs6295 locus of the serotonin receptor gene 1A HTR1A with morphofunctional features and body weight gain. Material and methods. The study used the materials of a comprehensive anthropogenetic examination of 386 men and 418 women aged 17 to 30 years. More than 20 morphofunctional indicators were measured using the traditional anthropometric method. The material for genetic analysis was genomic DNA isolated from buccal epithelium. The reliability of intergroup differences was assessed using the Mann-Whitney criterion, while canonical discriminant analysis was used to study intergroup variability. Results. For the first time, a significant correlation was shown between the polymorphism of the serotonin receptor type 1 gene HTR1A and morphofunctional features: individuals with the G/G genotype with greater body weight have lower (compared to carriers of the C/C and C/G genotypes) values of the indicators of the level of metabolic processes and specific metabolism. Conclusion. The statistically significant obtained results may be used in the development of individual strategies for the prevention and treatment of obesity, and also allow us to supplement the information on the association of serotonin system gene polymorphism with morphofunctional features and contribute to expanding our understanding of the human physique features formation and their relationships with hereditary predisposition.

Utility of mid-upper arm circumference in pediatric malnutrition: An Australasian Society of Parenteral and Enteral Nutrition consensus statement using the Delphi method.

Mid-upper arm circumference (MUAC) is a simple anthropometric tool used to screen for childhood undernutrition in humanitarian settings or low-income and middle-income countries. However, there is conflicting evidence and a lack of consensus with regard to its diagnostic use in clinical settings or population groups beyond this context. In 2023, a project officer was appointed by the Australasian Society of Parenteral and Enteral Nutrition (AuSPEN) to lead the development of a consensus review into the use of MUAC in the pediatric clinical setting. An AuSPEN appointed multidisciplinary group of informed clinicians used the Delphi method to critically appraise the evidence and develop a series of consensus statements. Delphi surveys were anonymous and distributed electronically. Members were asked to rate their level of agreement with each consensus statement using a 5-point Likert scale. A priori definition of consensus was established as ≥80% responses "agree" or "strongly agree." Three Delphi rounds were required to reach consensus. A total of 18 consensus statements, including rationale, were developed across the topics 'assessment and diagnosis', 'screening and monitoring' and 'clinical settings'. An evidence-based, region-specific consensus approach to the use of MUAC in pediatric malnutrition is a valuable tool for clinicians. MUAC is a straightforward, non-invasive and cost-effective tool, and may provide an advantage over traditional anthropometric tools in some clinical settings. There are limitations to the utility of MUAC and this consensus paper provides an empirical summary of advantages and limitations as they apply to the screening, assessment, diagnosis, and monitoring of pediatric malnutrition.

Investigating the efficiency of novel indicators in predicting risk of metabolic syndrome in the Iranian adult population.

Whether new anthropometric indicators are superior to conventional anthropometric indicators and whether they can better identify MetS in apparently healthy people needs further research. Thus, this study aimed to estimate the efficiency of novel indicators in predicting the risk of metabolic syndrome (MetS) in the Iranian adult population. In this cross-sectional study, 800 subjects were selected by clustered random sampling. The metabolic factors, traditional and novel anthropometric indices, the triglyceride and glucose index (TyG index) and modified TyG indices (TyG-BMI, TyG-WC, TyG-WHR, and TyG-WHtR), and metabolic score for insulin resistance (METS-IR) were evaluated. The MetS was calculated according to the IDF criteria. To investigate the risk of MetS, logistic regression was used along with modeling. In all three models, all traditional anthropometric indices were associated with MetS (P < 0.001). Regarding novel anthropometric indices, all indices (except for ABSI) significantly predicted the risk of MetS in all participants before and after adjustment (P < 0.001). WTI index presented the highest Odds ratios for MetS (29.50, 95% CI: 15.53-56.03). A positive association was found in all models between TyG and modified TyG indices and METS-IR with MetS (P for all < 0.001). TyG-WHtR index presented the highest Odds ratios for MetS (70.07, 95% CI: 32.42-151.43). A combination of the TyG index and WHtR (TyG-WHtR index) was better than the TyG index alone, with a higher odds ratio in predicting MetS. Due to the simplicity of these indices, cost-effectiveness, and facility at small-scale labs and being predictive of MetS risk it is suggested to include these markers in clinical practice.

Clinical utility of novel anthropometric indices in identifying type 2 diabetes mellitus among South African adult females.

To assess the clinical utility of novel anthropometric indices and other traditional anthropometric indices in identifying the risk of type 2 diabetes mellitus (T2D) among South African adult females. In the first South African National Health and Nutrition Examination Survey (SANHANES-1), traditional [body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)] and novel [a-body shape index (ABSI), abdominal volume index (AVI), body adiposity index (BAI), body roundness index (BRI), conicity index (CI), and Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE)] anthropometric indices were assessed. T2D was diagnosed using glycated haemoglobin (HbA1c) ≥ 6.5% among participants without known T2D. Basic statistics and multiple regression analyses were explored the association between anthropometric indices and newly diagnosed T2D. Receiver operating characteristic (ROC) curve analysis was used to measure the predictive ability of both traditional and novel indices. Among 2 623 participants, 384 (14.6%) had newly diagnosed T2D. All anthropometric indices mean values were significantly higher among participants with T2D (most p < 0.001). Higher mean values increased T2D odds e.g., in the model adjusted for age, employment, residence, and population group, odds ratio (OR) and 95% confidence interval (CI) for T2D with some of anthropometric indices were: 1.86 (1.60-2.15) for WC, 1.84 (1.59-2.13) for WHtR, 1.73 (1.51-1.99) for AVI, 1.71 (1.49-1.96) for BRI and 1.86 (1.57-2.20) for CUN-BAE. The top quartile for all indices had the highest T2D odds (p < 0.05). These outcomes were the highest for WC, AVI, and CUN-BAE and remained so even after removing the confounding effects of age, employment, population group, and residence. Based on the ROC analysis, none of the anthropometrical indices performed excellently (i.e., had an area under the curve [AUC] > 0.80). The WC, WHtR, AVI, BRI, and CUN-BAE, however, performed acceptably (AUCs 0.70-0.79), while also exhibiting corresponding cutoff values of 86.65cm, 0.57, 15.52, 3.83, and 38.35, respectively. The data shows that traditional and novel anthropometric indices similarly identifying newly diagnosed T2D among adult South African females. We recommend the continuing the use of traditional indices, as they are affordable and easy to use in our setting.

Robust identification key predictors of short- and long-term weight status in children and adolescents by machine learning.

Early identification of high-risk individuals for weight problems in children and adolescents is crucial for implementing timely preventive measures. While machine learning (ML) techniques have shown promise in addressing this complex challenge with high-dimensional data, feature selection is vital for identifying the key predictors that can facilitate effective and targeted interventions. This study aims to utilize feature selection process to identify a robust and minimal set of predictors that can aid in the early prediction of short- and long-term weight problems in children and adolescents. We utilized demographic, physical, and psychological wellbeing predictors to model weight status (normal, underweight, overweight, and obese) for 1-, 3-, and 5-year periods. To select the most influential features, we employed four feature selection methods: (1) Chi-Square test; (2) Information Gain; (3) Random Forest; (4) eXtreme Gradient Boosting (XGBoost) with six ML approaches. The stability of the feature selection methods was assessed by Jaccard's index, Spearman's rank correlation and Pearson's correlation. Model evaluation was performed by various accuracy metrics. With 3,862,820 million student-visits were included in this population-based study, the mean age of 11.6 (SD = 3.64) for the training set and 10.8 years (SD = 3.50) for the temporal test set. From the initial set of 38 predictors, we identified 6, 9, and 13 features for 1-, 3-, and 5-year predictions, respectively, by the best performed feature selection method of Chi-Square test in XGBoost models. These feature sets demonstrated excellent stability and achieved prediction accuracies of 0.82, 0.73, and 0.70; macro-AUCs of 0.94, 0.86, and 0.83; micro-AUCs of 0.96, 0.93, and 0.92 for different prediction windows, respectively. Weight, height, sex, total score of self-esteem, and age were consistently the most influential predictors across all prediction windows. Additionally, several psychological and social wellbeing predictors showed relatively high importance in long-term weight status prediction. We demonstrate the potential of ML in identifying key predictors of weight status in children and adolescents. While traditional anthropometric measures remain important, psychological and social wellbeing factors also emerge as crucial predictors, potentially informing targeted interventions to address childhood and adolescence weight problems.

Association of body shape phenotypes and body fat distribution indexes with inflammatory biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank

BackgroundThe allometric body shape index (ABSI) and hip index (HI), as well as multi-trait body shape phenotypes, have not yet been compared in their associations with inflammatory markers. The aim of this study was to examine the relationship between novel and traditional anthropometric indexes with inflammation using data from the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts.MethodsParticipants from EPIC (n = 17,943, 69.1% women) and UK Biobank (n = 426,223, 53.2% women) with data on anthropometric indexes and C-reactive protein (CRP) were included in this cross-sectional analysis. A subset of women in EPIC also had at least one measurement for interleukins, tumour necrosis factor alpha, interferon gamma, leptin, and adiponectin. Four distinct body shape phenotypes were derived by a principal component (PC) analysis on height, weight, body mass index (BMI), waist (WC) and hip circumferences (HC), and waist-to-hip ratio (WHR). PC1 described overall adiposity, PC2 tall with low WHR, PC3 tall and centrally obese, and PC4 high BMI and weight with low WC and HC, suggesting an athletic phenotype. ABSI, HI, waist-to-height ratio and waist-to-hip index (WHI) were also calculated. Linear regression models were carried out separately in EPIC and UK Biobank stratified by sex and adjusted for age, smoking status, education, and physical activity. Results were additionally combined in a random-effects meta-analysis.ResultsTraditional anthropometric indexes, particularly BMI, WC, and weight were positively associated with CRP levels, in men and women. Body shape phenotypes also showed distinct associations with CRP. Specifically, PC2 showed inverse associations with CRP in EPIC and UK Biobank in both sexes, similarly to height. PC3 was inversely associated with CRP among women, whereas positive associations were observed among men.ConclusionsSpecific indexes of body size and body fat distribution showed differential associations with inflammation in adults. Notably, our results suggest that in women, height may mitigate the impact of a higher WC and HC on inflammation. This suggests that subtypes of adiposity exhibit substantial variation in their inflammatory potential, which may have implications for inflammation-related chronic diseases.

Comparison of novel and traditional anthropometric indices in Eastern-China adults: which is the best indicator of the metabolically obese normal weight phenotype?

BackgroundPeople with the metabolically obese normal weight (MONW) phenotype have been confirmed to significantly increase the risk of unfavorable health consequences. This study aimed to investigate the relationships between traditional and novel anthropometric indices with the MONW phenotype and compare the predictive ability of different anthropometric indices in identifying individuals with the MONW phenotype.MethodsThis cross-sectional study involved a total of 26,332 participants aged 18 years or older with a normal weight from Nanjing, China. Sociodemographic information, biochemical measurements, and anthropometric indices were collected. The novel body fat anthropometric indices included body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), weight-adjusted-waist index (WWI), body adiposity index (BAI), conicity index (CI), waist-hip-height ratio (WHHR), as well as traditional indices such as waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR).The prevalence ratio (PR) from modified poisson regression and area under the receiver-operating characteristic curve (AUC) were conducted to compare the association and predictive capacity of different obesity indicators for the MONW phenotype. All analyses were stratified by sex.ResultsModified poisson regression analyses revealed that weight, WC, HC, BMI, WHR, WHtR, ABSI, BRI, AVI, WWI, BAI, CI, and WHHR were independently associated with higher risk of the MONW phenotype, regardless of whether they were treated as a continuous or categorical variable (P < 0.05). Notably, BRI demonstrated the strongest association in both men (highest quartile VS lowest quartile; PR = 3.14, 95%CI, 2.49, 3.96; P < 0.001) and women (PR = 4.63, 95%CI, 3.81, 5.62; P < 0.001). Receiver operating characteristic analysis indicated that AUC for the different anthropometric indices ranged from 0.50 to 0.80. BRI and WHtR had the largest AUC in both males (both AUC = 0.733; 95% CI, 0.717, 0.750) and females (both AUC = 0.773; 95% CI, 0.761, 0.786). The optimal cut-off points for BRI, determined by maximizing the Youden’s index, were 3.102 (sensitivity: 63.2%, specificity: 36.2%) in males and 3.136 (sensitivity: 68.9%, specificity: 44.2%) in females. Moreover, BRI and WHtR exhibited the highest diagnostic accuracy in younger age groups, specifically those aged 18–34 in both sexes.ConclusionsBRI emerged as the optimal predictor and independent determinant of the MONW phenotype, regardless of gender. This association was particularly pronounced in young individuals.

Comparisons of Various Anthropometric Indices for Incident Hypertension in Military Young Adults: The CHIEF Cohort Study.

The study aimed to compare the predictive capabilities of the traditional anthropometric indices with the novel anthropometric indices for incident hypertension. Some novel anthropometric indices, e.g., the Body Roundness Index (BRI) and A Body Shape Index (ABSI) have been associated with prevalent hypertension. There are a few cohort studies that have examined the association of the novel anthropometric indices with newonset hypertension in young adults. This study included 2,448 military male and female young adults, aged 18-39 years, free of hypertension at baseline in Taiwan; they were followed for incidence of hypertension from 2014 till the end of 2020. Blood Pressure (BP) in mmHg was measured twice and averaged to verify hypertension, which was defined as systolic BP ≥130 and/or diastolic BP ≥80 or on antihypertensive medication therapy in each annual health examination. Anthropometric indices included the Body Mass Index (BMI) defined as the weight (kg)/height squared (m2), Waist Girth (WC) in cm, the Waist-to-height Ratio (WHtR), the BRI defined as 364.2 - 365.5 × {1 - [(WC/2π)/(0.5 × height)]2}0.5, as well as ABSI defined as WC/(BMI2/3 × height1/2). Multiple Cox regression analysis and Area Under the Curve (AUC) of the Receiver of Operating Characteristics (ROC) were utilized with adjustments for the baseline potential covariates to determine the association and compare the performance of various indices for incident hypertension. During a median follow-up period of 6.0 years, 920 new-onset hypertension cases (37.6%) developed. Higher BMI, WC, BRI (per each 1-unit increase) and WHtR (per each 0.1- unit increase) were associated with a greater risk of new-onset hypertension [Hazard Ratios (HRs) and 95% confidence intervals: 1.060 (1.035-1.085), 1.021 (1.011-1.030), and 1.178 (1.077-1.288), respectively], whereas there was no association between ABSI and new-onset hypertension. For the ROC, WC was observed with the greatest AUC for incident new-onset hypertension [0.661 (0.638-0.683)], followed by BMI [0.650 (0.628-0.673)], while the ABSI was found with the lowest AUC [0.544 (0.521-0.568)]. Most of the anthropometric indices were associated with a higher risk of new-onset hypertension among young adults, except for ABSI. In addition, this study has suggested the traditional indices, such as WC and BMI, to be superior to the latest ones, e.g., BRI and ABSI, for the prediction of new-onset hypertension.

Associations between novel anthropometric indices and the prevalence of gallstones among 6,848 adults: a cross-sectional study.

Traditional anthropometric measures, including body mass index (BMI), are insufficient for evaluating gallstone risk. This study investigated the association between novel anthropometric indices and gallstone risk among 6,848 participants from the National Health and Nutrition Examination Survey in the United States. Measures calculated included weight (WT), BMI, waist circumference (WC), waist-to-height ratio (WtHR), conicity index (CI), A Body Shape Index (ABSI), Body Roundness Index (BRI), Abdominal Volume Index (AVI), and Weight-adjusted Waist Index (WWI). Logistic regression and smooth curve fitting assessed the relationships between these indices and gallstones, complemented by receiver operating characteristic (ROC) curve analysis to evaluate their discriminative power. The results indicated significant differences between study groups, with a positive and independent correlation identified between gallstones and all measures except ABSI. Specifically, per 1 SD increase in WC, WT, BMI, WtHR, and AVI was associated with a 57%, 59%, 52%, 53%, and 53% increased risk of gallstones, respectively. Dose-response analysis confirmed a positive correlation between these indices and gallstone risk. ROC analysis highlighted WtHR and BRI as having superior discriminative abilities (AUC = 0.6703). Further, among participants with a BMI < 30 kg/m2, elevated levels of WT, WtHR, CI, BRI, and WWI significantly increased the risk of gallstones (P < 0.001). Likewise, elevated BMI heightened the risk at low levels of WT, WC, WtHR, BRI, AVI, and CI (P < 0.001). This study supports the positive association between various anthropometric indicators and gallstones, recommending that newer anthropometric indices be considered more extensively to enhance gallstone prevention and treatment strategies.

Anthropometric Profile, Overweight/Obesity Prevalence, and Socioeconomic Impact in Moroccan Children Aged 6-12 Years Old with Autism Spectrum Disorder.

In addition to the inherent challenges of their condition, children with autism spectrum disorder (ASD) are also susceptible to the global obesity epidemic. However, concerning the prevalence of obesity within the Moroccan ASD pediatric population, data remain scarce. A total of 258 children (boys = 195) aged 6 to 12 years old (mean = 9.4 ± 1.4) diagnosed with ASD participated in this study. Besides the body mass and height, four significant anthropometric markers for assessing obesity were examined: body mass index (BMI), body surface area (BSA), waist circumference (WC), and waist-to-height ratio (WHtR). Each anthropometric marker was categorized into one of three cardiometabolic risk levels based on the Z-scores and their corresponding percentiles. The distribution was as follows: low risk (≤84th percentile), high risk (85th-94th percentile), and very high risk (≥95th percentile). Subsequently, a multiple regression analysis was employed to develop an algorithm that generates a composite risk score. This score incorporates all the anthropometric variables simultaneously, while also weighting their individual contributions to the cardiometabolic risk. Children with ASD exhibit an anthropometric profile that markedly increases their susceptibility to cardiometabolic issues. While roughly 11% of the general Moroccan child population is overweight or obese, this figure soars to nearly 60% among children with ASD when considering the central adiposity markers. Furthermore, children from middle-class socioeconomic backgrounds display a more than threefold greater risk of developing overweight or obesity compared to their counterparts from lower socioeconomic backgrounds. This study has, for the first time, provided an up-to-date overview of the cardiometabolic risk in Moroccan children with ASD using traditional anthropometric measurements. The primary risk factor is clearly linked to central (abdominal) adiposity, which is recognized as the most deleterious. This study highlights the need to include general and central obesity markers. This study underscores the importance of incorporating both general and central adiposity markers for a more comprehensive assessment, and it emphasizes the need for closer monitoring within this high-risk population.

Consumers' interaction with online fashion retailers' body measurement guidance

PurposeOnline fashion retailers offer body measurement guidance, alongside their target consumer body size charts and fit information, to help consumers select the right size garment as the garment cannot be tried on. Its use by retailers suggests it can act as a means of mitigating garment returns as there has been a noted increase in returns due to incorrect size selection even though body measurement instructions are provided online. The purpose of this research is to determine how consumers interact with body measurement guidance, how they interpret it and use it, thereby interrogating its efficacy.Design/methodology/approachAn exploratory investigation was undertaken. Thirty participants were recruited and given a choice of fashion retailers' body measurement guidance and a tape measure. They took their body measurements over their clothes. A technician repeated the task, thereby providing two sets of body measurements. A paired t-test determined if there was a significant difference in both values in terms of their mean. Technicians also documented their observations of how the participants interacted with the task. The content of the fashion retailer measurement guidance was then compared to that of published anthropometric guidance for surveys.FindingsParticipants were familiar with the guidance and tape-measure; they were able to self-measure. The fashion retailer measurement guidance, however, lacked detail/clarity in visuals and written content when compared to anthropometric guidance. Interpretation of the guidance differed between participant and technician. This resulted in a significant difference in circumference measurements for the bust/chest and hips, yet no significant difference in waist and inside-leg measurements. For measurements that were difficult to take unaided, participants devised novel practices which resulted in little divergence from the technician taken body measurements. The results question the guidance efficacy in its current form.Originality/valueThere has been no study which addresses how consumers interpret and interact with fashion retailers' online measurement guidance. This is important as this can mitigate garment returns. This research provides insight to influence fashion retailers' measurement guidance policy. It also adds to the existing body of knowledge surrounding anthropometric practice for clothing.Research limitations/implicationsThe findings indicated that fashion retailers need to revise their body measurement guidance content. The content needs to be more comprehensive but still use accessible language and visuals. The broader implications of this study highlight that traditional anthropometrics for self-taken body measurement needs developing as an emerging concept through clothing-related academic study.Practical implicationsFashion retailers' measurement guidance needs to be more comprehensive but still use accessible language and visuals. The broader implications of this study highlight that traditional anthropometrics for self-taken body measurement needs further investigation and documentation as an emerging concept through clothing-related academic study.

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

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.). 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. 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. 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.

Face anthropometry for filtering facepiece respirators: analysis of the association between facial dimensions and respirator fit.

Ensuring proper respirator fit for individuals remains a persistent challenge in occupational environments, yet there is limited knowledge about how respirators interact with the face to "'fit." Previous studies have attempted to understand the association between face dimensions and respirator fit using traditional head/face anthropometry not specifically tailored for respirators. The purpose of this study was to assess and compare the ability of filtering facepiece respirator (FFR)-specific face anthropometry with traditional head/face anthropometry in exploring the relationship between facial dimensions and the fit of FFR. The study utilized 3D face scans and quantitative fit factor scores from 56 participants to investigate the relationship between face anthropometry and FFR fit. Both FFR-specific and traditional anthropometric measurements were obtained through 3D anthropometric software. Intra-correlation of anthropometry was analyzed to evaluate the efficiency and effectiveness of FFR-specific and traditional anthropometry respectively. Principal component analysis (PCA) was conducted to test the usefulness of the PCA method for investigating various facial features. Logistic regression was used to develop fit association models by estimating the relationship between each face measurement set and the binary outcome of the fit test result. The prediction accuracy of the developed regression models was tested. FFR-specific face anthropometry consists of a set of measurements that can inform the detailed facial shape associated with the FFRs more effectively than traditional head/face anthropometry. While PCA may have been effective in reducing the variable dimensions for the relatively large parts of the human body such as upper and lower bodies in previous literature, PCA results of FFR-specific and traditional anthropometry were inconsistent and insufficient to describe face dimensions with complex anatomy in a small-detailed area, suggesting that facial shape should be understood through a variety of approaches including statistical methods. Logistic regression analysis results confirmed that the association models of FFR-specific face anthropometry were significant with higher prediction accuracy and had a better model's goodness of fit than those of traditional head/face anthropometry in 3 conditions inputting all measurements, all PC scores, or top 5 measurements from PCA. The findings showed that the FFR fit association model enables an understanding of the detailed association between face and respirator fit and allows for the development of a system to predict respirator fit success or failure based on facial dimensions. Future research would include testing the validity of the model and FFR-specific measurement set on different respirator types, expanding the population set, and developing an integrated approach using automated and machine learning technologies to inform FFR selection for occupation workers and the general population.

Advanced Body Measurement Techniques Can Complement Current Methods of Cytotoxic Chemotherapy Dose Prescription

Within chemotherapy, estimates of a patient’s body surface area (BSA) are used to calculate drug dosages. However, the use of BSA for calculating chemotherapy dosage has been heavily criticised in previous literature, with potentially significant implications for the effectiveness and toxicity of treatment. BSA has been found to be a poor indicator of optimal drug exposure that does not account for the complex processes of cytotoxic drug distribution and elimination. In addition, differences in BSA estimates between existing formulae have been shown to be so large that they can affect patients’ mortality, particularly in patients with atypical body types. This uncertainty associated with BSA prediction may decrease the confidence of practitioners when determining chemotherapy dosages, particularly with regards to the risk of excess toxicity from over-dosing, or a reduced anti-cancer effect due to under-dosing. The use of national dose-banding in the UK may in some cases account for possible inaccuracies, but the threshold of variance in this case is small (+/−6%). Advanced body measurement techniques, utilising digital tools such as three-dimensional (3D) surface imaging, capture accurate external dimensions and detailed shape characteristics of the human body. Measures of body shape describe morphological variations that cannot be identified by traditional anthropometric techniques and improve the prediction of total body fat and distribution. It is our view that the use of advanced body measurement techniques can provide practitioners with tools for prescribing chemotherapy dosages that are valid for individuals, regardless of their body type.

Effect of Weight Loss on the Apnea Hypopnea Index is Related to Waist Circumference in Chinese Adults with Overweight and Obesity.

The present study aimed to evaluate the efficiency of traditional anthropometric and body composition parameters in predicting apnea hypopnea index (AHI) change after weight loss. Chinese adults with overweight and obesity were included into this study containing two parts. A cross-sectional study was conducted in 137 individuals using the baseline data from two weight loss intervention trials. The second part was the weight-loss intervention study conducted in 60 overweight and obese patients with obstructive sleep apnea (OSA). All participants underwent physical examination, bioelectrical impedance analysis and overnight polysomnography. Multivariate linear regression models were used to identify the most accurate parameters to predict AHI and the mediation analysis to evaluate the mediators between weight loss and AHI reduction. Waist circumference (WC), body mass index and fat mass were positively associated with AHI after adjusting multiple collinearities in the cross-sectional study. After weight-loss intervention, body weight decreased from 94.6 ± 15.3 to 88.0 ± 13.9 kg, and AHI decreased from 41.9 (13.0,66.9) to 20.7 (8.7,51.2) events/h. Among these parameters, only percentage changes in WC and AHI across the intervention were positively intercorrelated after controlling for covariates (adjusted r = 0.271, P = 0.041). The mediation analysis supported WC as a mediator between weight loss and AHI reduction (standardized indirect effect [95% CI] = 4.272[0.936,7.999]). Both general and abdominal obesity are of high prognostic value for OSA. WC as an easily accessible parameter mediates the effects of weight loss in decreasing OSA severity.