Traditional Anthropometric Measurements Research Articles

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.

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.

Relationship between the novel and traditional anthropometric indices and subclinical atherosclerosis evaluated by carotid intima-media thickness (c-IMT).

Over the last few years, novel anthropometric indices have been developed as an alternative to body mass index (BMI) and other traditional anthropometric measurements to enhance the estimate of fat proportion and its relationship to a future cardiovascular event. The purpose of this study was to investigate the association of carotid intima-media thickness (c-IMT) estimated by Doppler ultrasound with current anthropometric indices (traditional and novel). A cross-sectional study was conducted on a total of 789 Spanish patients. Traditional (BMI, WHR, and WHtR) and new (WWI, AVI, ABSI, BRI, BAI, CUN-BAE, and CI) anthropometric indices were determined, and carotid Doppler ultrasound was performed to evaluate c-IMT (≥0.90 mm). Most of the anthropometric indices analyzed were significantly higher among patients with pathological c-IMT, except for BMI, BAI, and CUN-BAE. In multiple linear regression analysis, c-IMT was positively related to ABSI, AVI, BRI, CI, and WWI but not to CUN-BAE, BAI, or traditional anthropometric indices. Similarly, in univariate analysis, all indices were associated with a c-IMT of ≥0.90 mm (p < 0.05), except BMI, BAI, and CUN-BAE; however, only ABSI (adjusted OR: 1.61; 95% CI: 1.08-2.40; p = 0.017), CI (adjusted OR: 1.73; 95% CI: 1.15-2.60; p = 0.008), and WWI (adjusted OR: 1.74; 95% CI: 1.14-2.64; p = 0.009) were significantly associated in multivariate analysis. Finally, CI, ABSI, and WWI provided the largest AUC, and BMI and CUN-BAE showed the lowest AUC. ABSI, CI, and WWI were positively associated with pathological c-IMT (≥0.90 mm), independent of other confounders.

Neck circumference is independently associated with metabolic syndrome in women with polycystic ovary syndrome.

Recent compelling evidence has shown that neck circumference (NC), as a reliable and convenient anthropometric index, has better predictive values of hyperuricemia and insulin resistance in women with polycystic ovary syndrome (PCOS) compared with traditional anthropometric measurements. Since both PCOS and metabolic syndrome (MetS) share similar characteristics and affect long-term health of women, we conducted this cross-sectional study to explore the correlation of NC with MetS and metabolic risk factors. Anthropometric parameters, blood pressure, glycemic and lipid profile of 633 PCOS and 2,172 non-PCOS women from January 2018 to June 2021 were analyzed. The results showed that the prevalence of MetS was 28.0% and 9.4% in PCOS and non-PCOS women, respectively. The prevalence of MetS, hypertention, obesity, central obesity, hyperglycemia and dyslipidaemia was also significantly higher in both PCOS and non-PCOS women with larger NC. Additionally, logistic regression analysis showed that PCOS women in the highest quartile of NC had the highest prevalence of MetS (RR = 9.94, 95%CI: 2.41-40.99) after adjusting for confounding factors, while the association between NC and MetS was much attenuated after adjusting for confounding factors in non-PCOS women. Furthermore, we also identified that the optimal NC cutoff value was 33 cm in PCOS women for the prediction of MetS. The potential mechanism could be attributed to the increased release of adipokines and excessive free fatty acids release from subcutaneous adipose tissue, which consequently precipitate the development of MetS. In conclusion, NC was found to be positively and independently correlated with the prevalence of MetS.

The New Anthropometric Measures in Patients With Hypothyroidism

Backgrounds: We aimed to compare the new anthropometric measurements and traditional anthropometric measurements as body mass index which are used to display visceral adipose distribution in patients with hypothyroidism. We also aimed to investigate the new anthropometric measurements and Carotid intima media thickness as predictors of cardiovascular risk. Methods: We include patients with hypothyroidism and healthy controls. The patients were divided into 3 groups as overt hypothyroidism, subclinical hypothyroidism and control groups. Demographic data, anthropometric measurements, laboratory findings and CIMT of the patients and control group were also evaluated. Results: The mean ages of the patients in groups were 37.46 ± 8.89, 35.03 ± 13.06 and 38.79 ± 10.46 years respectively (p=0.876). The average of waist circumference in overt hypothyroidism group was statistically higher than control (p&amp;lt;0.01). The averages of waist circumference/height circumference in the hypothyroidism groups were statistically higher than the control. There was a strong correlation according to body adiposity index, abdominal volume index, and body roundness index as new anthropometric measurements and body mass index, waist circumference, hip circumference and waist/height ratio (r&amp;gt;0.750 p&amp;lt;0.001 for all values). The mean value of carotid intima media thickness of the overt hypothyroidism group was significantly higher (p&amp;lt;0.01). Conclusions: We found strong correlations between new anthropometric and traditional anthropometric measurements in patient with hypothyroidism. Cardiometabolic risk has increased in patients with hypothyroidism, and routine use of new anthropometric measurements displaying body fat distribution and central obesity will be useful for early detection and treatment of cardiovascular complications.

Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data

This study aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs. In the study, 66 male and 54 female participants were scanned by MRI and a stereovision body imaging (SBI) to measure participants’ abdominal VAT and SAT volumes and the BSDs. A fuzzy c-means algorithm was used to form the inherent grouping clusters of abdominal fat distributions. A support-vector-machine (SVM) classifier, with an embedded feature selection scheme, was employed to determine an optimal subset of the BSDs for predicting internal fat distributions. A five-fold cross-validation procedure was used to prevent over-fitting in the classification. The classification results of the BSDs were compared with those of the traditional anthropometric measurements and the Dual Energy X-Ray Absorptiometry (DXA) measurements. Four clusters were identified for abdominal fat distributions: (1) low VAT and SAT, (2) elevated VAT and SAT, (3) higher SAT, and (4) higher VAT. The cross-validation accuracies of the traditional anthropometric, DXA and BSD measurements were 85.0%, 87.5% and 90%, respectively. Compared to the traditional anthropometric and DXA measurements, the BSDs appeared to be effective and efficient in predicting abdominal fat distributions.

Relationship of neck circumference to some cardiometabolic risk parameters

Background Neck circumference (NC) is an easy and reliable anthropometric measurement. The use of NC as an indicator of obesity among Egyptians was previously established. However, the relationship between NC and different cardiometabolic risk (CMR) parameters was not previously studied in the Egyptian population. Objective The aim of this work was to study the relationship between NC and some CMR parameters in obese adult Egyptian individuals. Participants and methods This cross-sectional study was carried out on 100 apparently healthy obese adult Egyptian participants (BMI ≥30 kg/m2), above the age of 18 years, 50% of them were males and the other 50% were females. NC and other traditional anthropometric measurements were evaluated. Blood samples were assayed for glycosylated hemoglobin, total cholesterol, high-density lipoprotein cholesterol (HDL-C), non-HDL-C, and high-sensitivity C-reactive protein. Results There were significant positive correlations between NC and each of systolic and diastolic blood pressure [(r=0.527, P&lt;0.001), (r=0.430, P&lt;0.001), respectively], waist circumference (r=0.538, P&lt;0.001), BMI (r=0.403, P&lt;0.001), and high-sensitivity C-reactive protein (r=0.304, P=0.002). While a significant negative correlation was found between NC and HDL-C. Multivariate regression analysis revealed an independent association of NC with waist circumference in males and with systolic blood pressure in females. Conclusion This study does not only confirm the association of NC with anthropometric measurements in the Egyptian population, but it also establishes the NC association with CMR factors that support the possibility of using NC as a CMR marker among Egyptians.

Predictive performance of traditional and novel lipid combined anthropometric indices to identify prediabetes

Background and aimsDiabetes mellitus is one of the critical public health challenges in the Indian healthcare scenario. Novel anthropometric indices are promising surrogate markers to detect prediabetes compared to the traditional anthropometric indices that only reflect gross obesity. Thus, the authors aim to analyse the potential of three novel lipid combined anthropometric indices in predicting prediabetes in the Asian Indian population. MethodsWe conducted an age and gender-matched case-control study to identify the predictors of prediabetes. Prediabetes was diagnosed as per the American Diabetes Association (ADA) guidelines 2010. The traditional anthropometric measurements including waist circumference (WC), waist to hip ratio (WHR) and body mass index (BMI) were executed using standardised methods. Fasting lipid profile was obtained and using standardised formulas, the novel lipid combined anthropometric indices such as lipid accumulation product (LAP), visceral adiposity index (VAI) and triglyceride glucose index (TyG index) were derived. TyG related indices such as triglyceride glucose-waist circumference (TyG-WC) and triglyceride glucose-body mass index (TyG-BMI) were also calculated. ResultsThe novel lipid combined anthropometric indices LAP, VAI, TyG index, TyG-WC and TyG-BMI were significantly higher in subjects with prediabetes of both the genders (p < 0.05). During receiver operating characteristic (ROC) curve evaluation, TyG index (AUC = 0.802) was the superior predictive measure in males, while in females, TyG-WC (AUC = 0.767) was the best among all the markers. ConclusionTyG index and TyG-WC seem to be a superior indicator of prediabetes in the Asian Indian population in comparison with other anthropometric indices to screen prediabetes.

Novel anthropometric parameters to define obesity and obesity-related disease in adults: a systematic review.

Obesity is defined as an abnormal or excessive accumulation of body fat. Traditionally, it has been assessed using a wide range of anthropometric, biochemical, and radiological measurements, with each having its advantages and disadvantages. A systematic review of the literature was conducted to identify novel anthropometric measurements of obesity in adults. Using a combination of MeSH terms, the PubMed database was searched. The current systematic review was conducted in accordance with the PRISMA guidelines. The data extracted from each study were (1) details of the study, (2) anthropometric parameter(s) evaluated, (3) study methods, (4) objectives of the study and/or comparisons, and (5) main findings/conclusions of the study. The search yielded 2472 articles, of which 66 studies were deemed eligible to be included. The literature search identified 25 novel anthropometric parameters. Data on novel anthropometric parameters were derived from 26 countries. Majority were descriptive cross-sectional studies (n = 43), while 22 were cohort studies. Age range of the study populations was 17-103 years, while sample size varied from 45 to 384612. The novel anthropometric parameters identified in the present study showed variable correlation with obesity and/or related metabolic risk factors. Some parameters involved complex calculations, while others were derived from traditional anthropometric measurements. Further research is required in order to determine the accuracy and precision.

Lipid accumulation product index as visceral obesity indicator in psoriasis: A Case–control Study

Background:Psoriasis has well-known associations with individual components of metabolic syndrome such as hypertension, dyslipidemia, insulin resistance, and obesity. Traditional anthropometric measurements of obesity such as waist circumference (WC) and body mass index (BMI) do not differentiate between subcutaneous fat and visceral fat, the latter being associated with cardiovascular risk factors. Lipid accumulation product (LAP) index is a measure of visceral fat and has been found to be a better predictor of cardiovascular risk. However, LAP index has not been well-studied in psoriasis patients.Aims and Objectives:Our objective was to find out if LAP index differs significantly between psoriasis patients and controls and whether LAP index shows a correlation with duration and severity of psoriasis.Materials and Methods:A case–control study was undertaken with 40 chronic plaque psoriasis patients and 42 controls. BMI and LAP index were calculated for all the patients and controls. Psoriasis area severity index (PASI) was calculated for all the psoriasis patients. Mann–Whitney U-test was done for comparing the age, BMI, WC, serum triglyceride, and LAP index between the cases and controls and to compare the LAP index between mild psoriasis and moderate-to-severe psoriasis groups. Spearman's correlation coefficient was used to assess the correlation of LAP index with duration of psoriasis and with PASI. Logistic regression models were done to assess the risk factors in psoriasis.Results:A statistically significant difference was observed between the LAP index of controls (23.79 ± 13.02) and that of psoriasis patients (46.42 ± 27.2). LAP index was significantly higher in the moderate-to-severe psoriasis group as compared to the mild psoriasis group. LAP index was a significant risk factor associated with psoriasis (OR = 1.07; 95% CI: 1.03 – 1.11).Conclusion:Calculation of LAP index in psoriasis patients helps in identification of more individuals at high risk of cardiovascular morbidity than traditional anthropometric measurements of obesity.

A Study of Correlation of Neck Circumference with Framingham Risk Score as a Predictor of Coronary Artery Disease.

It has been observed that metabolic syndrome is risk factor for Coronary Artery Disease (CAD) and exerts its effects through fat deposition and vascular aging. CAD has been acknowledged as a leading cause of death. In earlier studies, the metabolic risk has been estimated by Framingham risk score. Recent studies have shown that Neck Circumference (NC) has a good correlation with other traditional anthropometric measurements and can be used as marker of obesity. It also correlates with Framingham risk score, which is slightly more sophisticated measure of CAD risk. To assess the risk of CAD in a subject based on NC and to correlate the NC to Framingham risk score. The present cross-sectional study, done at Karnataka Institute of Medical Sciences, Hubli, Karnataka, India, includes 100 subjects. The study duration was of one year from 1st January 2015 to 31st December 2015. Anthropometric indices Body Mass Index (BMI) and NC were correlated with 10 year CAD risk as calculated by Framingham risk score. The correlation between BMI, NC, vascular age and Framingham risk score was calculated using Karl Pearson's correlation method. NC has a strong correlation with 10 year CAD risk (p≤0.001). NC was significantly greater in males as compared to females (p≤0.001). Males had greater risk of cardiovascular disease as reflected by higher 10 year Framingham risk score (p≤0.0035). NC gives simple and easy prediction of CAD risk and is more reliable than traditional risk markers like BMI. NC correlates positively with 10 year Framingham risk score.

Association of Anthropometric Measurement Methods with Cardiovascular Disease Risk in Turkey

Objective: The aim of this study is to compare the predictive power of anthropometric indices for risk of developing Coronary Heart Disease (CHD) or CHD death. Methods: We used cross-sectional data from nationally representative Chronic Diseases and Risk Factors Survey conducted by the Ministry of Health in 2011. Body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist to height ratio (WHtR), body adiposity index (BAI) and A Body Shape Index (ABSI) formed the anthropometric measures. For each participant risk of developing CHD or dying from CVDs were calculated based on Framingham and SCORE risk equations. Predictive ability of anthropometric measurements was assessed by receiver operating characteristic (ROC) curves. Results: Anthropometric measurements of central obesity recorded higher area under the ROC curve (AUC) values than BMI in both men and women. While ABSI had the highest AUC values for Framingham 10-year predicted risk (FRS) for CHD death (AUC = 0.613), SCORE 10-year risk for CVD death (AUC = 0.633), in women AUC for ABSI was the highest for only SCORE risk threshold (AUC = 0.705). Among women, WHtR was found to be the best indicator for estimating CHD incidence (AUC = 0.706) and death from CVD (AUC = 0.696). Conclusion: Compared to traditional anthropometric measurements such as BMI, ABSI was a better indicator for given thresholds for estimating the risk of developing CHD and CVD death in men. Among women WHtR made better predictions for FRS thresholds, however, ABSI was better for predicting 10-year risk of CVD death calculated by SCORE risk equation. Key words: Obesity, Framingham risk score, coronary heart disease

Shape analysis of female torsos based on discrete cosine transform

Purpose – The purpose of this paper is to present results of shape analysis of female torso shape using the discrete cosine transform (DCT) from a three-dimensional (3D) whole body scan database. Design/methodology/approach – Torso shape is a central part of body shape and difficult to describe by linear measurements. In order to analyze body shape variation within a population the authors employed a DCT-based shape description method to compresses a dense 3D body scan surface into a small vector that preserves shape and removes size. The DCT-based shape descriptors of torso surfaces are further fed to principal component analysis (PCA) that decompose shape variation into constituent shape components. A visualization program was developed to observe principal components of torso shape and interpret their meanings. Findings – Extreme shapes of the first ten principal components summarize major shape variations and identify shapes that are difficult to capture with traditional anthropometric measurements. PCA results also help to find and retrieve similar shapes from a population-level database. Originality/value – Using the DCT for PCA of torso shape is a unique and original approach. It provides a basis for the description and classification of torso shape in 3D and the results from the shape analysis are potentially useful for designers of clothing and personal protective equipment.

Data Processing and Analysis for the 2012 Canadian Forces 3D Anthropometric Survey

The 2012 Canadian Forces Anthropometric Survey (CFAS 2012) is the first major 3D anthropometric survey of Canadian Forces personnel. 2200 full-body scans were conducted, together with traditional anthropometric measurements. This survey aims at providing accurate, detailed, and up-to-date body shape information for equipment design and procurement. In this paper, we describe the data processing and analysis of this dataset. This includes de-noising, template fitting, landmark identification, and statistical shape analysis. We also compare the military personnel with the general North American population using the CAESAR dataset.

Assessment of Nutritional Status by Dual-Energy X-Ray Absorptiometry in Chronic Kidney Disease Patients without Dialysis

Objective: The objective was to evaluate the assessment of nutritional status by dual-energy X-ray absorptiometry (DEXA) in chronic kidney disease (CKD) patients not receiving dialysis. Patients and Methods: A total of 143 patients in stage 4-5 without receiving dialysis were enrolled and classified into well-nourished and malnourished groups by subjective global assessment. Biochemical and anthropometric measurements were performed. Simultaneously, body composition including lean body mass (LBM) and fat mass (FM) was evaluated by DEXA. Results: Compared with well-nourished patients, malnourished patients showed lower pre-albumin (ALB) levels, but higher C-reactive protein (CRP) levels. There was no significant difference in serum ALB between both groups. For either men or women, body weight, body mass index, and glomerular filtration rate (GFR) were lower in the malnourished group. For the men, triceps skin-fold thickness (TSFT), mid-arm circumference (AC), mid-arm muscle circumference (AMC), LBM-DEXA and FM-DEXA were significantly lower in the malnourished patients. For the women, TSFT, mid-AC and FM-DEXA, but mid-AMC and LBM-DEX, were not significantly lower in the malnourished patients. There was a significant correlation between LBM-DEXA and mid-AMC. A significant correlation also existed between FM-DEXA and TSFT. Multiple logistic regressions showed that low percentage of FM, high serum CRP level and low GFR were independent risk factors for malnutrition. Conclusions: Low percentage of FM, high serum CRP and low GFR are independent risk factors for malnutrition. Estimation of LBM and FM by dual X-ray absorptiometry is in consistent with traditional anthropometric measurements. It's noteworthy that DEXA, a reliable and easy-to-perform assessment method, can sensitively detect early malnutrition and may be useful in monitoring nutrition changes in CKD patients.

Estimating 3D human shapes from measurements

The recent advances in 3-D imaging technologies give rise to databases of human shapes, from which statistical shape models can be built. These statistical models represent prior knowledge of the human shape and enable us to solve shape reconstruction problems from partial information. Generating human shape from traditional anthropometric measurements is such a problem, since these 1-D measurements encode 3-D shape information. Combined with a statistical shape model, these easy-to-obtain measurements can be leveraged to create 3D human shapes. However, existing methods limit the creation of the shapes to the space spanned by the database and thus require a large amount of training data. In this paper, we introduce a technique that extrapolates the statistically inferred shape to fit the measurement data using nonlinear optimization. This method ensures that the generated shape is both human-like and satisfies the measurement conditions. We demonstrate the effectiveness of the method and compare it to existing approaches through extensive experiments, using both synthetic data and real human measurements.

Anthropometric indexes outperform bioelectrical impedance analysis-derived estimates of body composition in identification of metabolic abnormalities in morbid obesity

BackgroundThe validity of anthropometric indexes in ascertaining the body composition (BC) in morbidly obese (MO) subjects has been questioned. Our objective was to evaluate, in MO subjects, whether bioelectrical impedance analysis (BIA) of BC is more closely associated with the metabolic syndrome (MS) and insulin resistance (IR) than are classic anthropometric measurements. The setting was a university hospital. MethodsThe association between anthropometric (body mass index, waist circumference [WC]) and BIA (total fat mass [FM] [percentage of FM], truncal FM, android FM) estimates of BC, MS, and IR was evaluated in 784 white MO subjects (212 men and 572 women). BIA estimates were calculated using equations specific for MO subjects developed by our own group and validated against dual energy x-ray absorptiometry. ResultsThe prevalence of the MS and IR was 78.6% and 88.6%, respectively. The body mass index was greater in women with the MS (P <.001) or IR (P <.001), and the WC was larger in subjects of both genders with the MS or IR (P <.001). Moreover, the WC correlated significantly with all the MS components (P <.05). In contrast, the percentage of FM, truncal FM, and android FM were significantly associated with the MS only in women. Stepwise logistic regression analysis demonstrated the WC as the only significant predictor of the MS or IR (both P <.001). Furthermore, receiver operating curve analysis showed WC was the most accurate BC parameter for the identification of subjects with the MS (area under the curve, WC = .681, P <.001) or IR (area under the curve, WC = .753, P <.001). ConclusionIn MO subjects, the BIA-derived indexes of total and central adiposity were not better predictors of the MS or IR than were traditional anthropometric measurements.

Validation of Stereophotogrammetry of the Human Torso

The objective of this study was to determine if measurements of breast morphology computed from three-dimensional (3D) stereophotogrammetry are equivalent to traditional anthropometric measurements obtained directly on a subject using a tape measure. 3D torso images of 23 women ranged in age from 36 to 63 who underwent or were scheduled for breast reconstruction surgery were obtained using a 3dMD torso system (3Q Technologies Inc., Atlanta, GA). Two different types (contoured and line-of-sight distances) of a total of nine distances were computed from 3D images of each participant. Each participant was photographed twice, first without fiducial points marked (referred to as unmarked image) and second with fiducial points marked prior to imaging (referred to as marked image). Stereophotogrammetry was compared to traditional direct anthropometry, in which measurements were taken with a tape measure on participants. Three statistical analyses were used to evaluate the agreement between stereophotogrammetry and direct anthropometry. Seven out of nine distances showed excellent agreement between stereophotogrammetry and direct anthropometry (both marked and unmarked images). In addition, stereophotogrammetry from the unmarked image was equivalent to that of the marked image (both line-of-sight and contoured distances). A lower level of agreement was observed for some measures because of difficulty in localizing more vaguely defined fiducial points, such as lowest visible point of breast mound, and inability of the imaging system in capturing areas obscured by the breast, such as the inframammary fold. Stereophotogrammetry from 3D images obtained from the 3dMD torso system is effective for quantifying breast morphology. Tools for surgical planning and evaluation based on stereophotogrammetry have the potential to improve breast surgery outcomes.

Sex Differences in the Association of Regional Fat Distribution with the Severity of Obstructive Sleep Apnea

To describe sex differences in the associations between severity of obstructive sleep apnea (OSA) and measures of obesity in body regions defined using both dual-energy absorptiometry and traditional anthropometric measures in a sleep-clinic sample. A prospective case-series observational study. The Western Australian Sleep Health Study operating out of the Sir Charles Gairdner Hospital Sleep Clinic, Perth, Western Australia. Newly referred clinic patients (60 men, 36 women) suspected of having OSA. N/A. Obstructive sleep apnea severity was defined by apnea-hypopnoea index from laboratory-based overnight polysomnography. Body mass index, neck, waist and hip circumference, neck-to-waist ratio, and waist-to-hip ratio were measured. Dual energy absorptiometry measurements included percentage fat and lean tissue. Multivariate regression models for each sex were developed. In women, percentage of fat in the neck region and body mass index together explained 33% of the variance in apnea-hypopnea index. In men, percentage of fat in the abdominal region and neck-to-waist ratio together accounted for 37% of the variance in apnea-hypopnea index. Regional obesity is associated with obstructive sleep apnea severity, although differently in men and women. In women, a direct influence of neck fat on the upper airway patency is implicated. In men, abdominal obesity appears to be the predominant influence. The apnea-hypopnea index was best predicted by a combination of Dual Energy Absorptiometry-measured mass and traditional anthropometric measurements.

Trends in Anthropometric Measures in U.S. Air Force Aircrew Survey Data

In 2008 a USAF Aircrew Sizing Survey project was launched. This survey is the first 3D whole body anthropometric survey of USAF aircrew. The primary purpose of this survey is to collect traditional anthropometric measurements, demographic information, and 3D data for body shape information on current aircrew personnel for use in crew station and protective equipment design. The specific aim for this paper is to compare the data collected to date with other available USAF aircrew anthropometric data as well as two extracted data sets, called JPATS (Joint Primary Air Training System) and JSF (Joint Strike Fighter) CAESAR (Civilian American European Surface Anthropometry Resource) which are currently being used as USAF design guidelines. The results from the comparisons between these survey data and available Air Force Survey data represent chronological trends in body dimensions for male and female aircrew. In addition, the noted anthropometric differences between the 2008–2009 survey data and the two extracted data subsamples (JPATS and JSF CAESAR) will help to determine the appropriateness of these subsets as substitute aircrew databases.