Predictive regression modeling of body segment parameters using individual-based anthropometric measurements

Body segment parameters such as segment mass, center of mass, and radius of gyration are used as inputs in static and dynamic ergonomic and biomechanical models used to predict joint and muscle forces, and to assess risks of musculoskeletal injury. Previous work has predicted body segment parameters (BSPs) in the general population using age and obesity levels as statistical predictors (Merrill et al., 2017). Estimated errors in the prediction of BSPs can be as large as 40%, depending on age, and the prediction method employed (Durkin and Dowling, 2003). Thus, more accurate and representative segment parameter inputs are required for attempting to predict modeling outputs such as joint contact forces, muscle forces, and injury risk in individuals. This study aims to provide statistical models for predicting torso, thigh, shank, upper arm, and forearm segment parameters in working adults using whole body dual energy x-ray absorptiometry (DXA) scan data along with a set of anthropometric measurements. The statistical models were developed on a training data set, and independently validated on a separate test data set. The predicted BSPs in validation data were, on average, within 5% of the actual in vivo DXA-based BSPs, while previously developed predictions (de Leva, 1996) had average errors of up to 60%, indicating that the new models greatly increase the accuracy in predicting segment parameters. These final developed models can be used for calculating representative BSPs in individuals for use in modeling applications dependent on these parameters.     

Analysis of body segment parameter differences between four human populations and the estimation errors of four popular mathematical models

Calculating the kinetics of motion using inverse or forward dynamics methods requires the use of accurate body segment inertial parameters. The methods available for calculating these body segment parameters (BSPs) have several limitations and a main concern is the applicability of predictive equations to several different populations. This study examined the differences in BSPs between 4 human populations using dual energy x-ray absorptiometry (DEXA), developed linear regression equations to predict mass, center of mass location (CM) and radius of gyration (K) in the frontal plane on 5 body segments and examined the errors produced by using several BSP sources in the literature. Significant population differences were seen in all segments for all populations and all BSPs except hand mass, indicating that population specific BSP predictors are needed. The linear regression equations developed performed best overall when compared to the other sources, yet no one set of predictors performed best for all segments, populations or BSPs. Large errors were seen with all models which were attributed to large individual differences within groups. Equations which account for these differences, including measurements of limb circumferences and breadths may provide better estimations. Geometric models use these parameters, however the models examined in this study did not perform well, possibly due to the assumption of constant density or the use of an overly simple shape. Creating solids which account for density changes or which mimic the mass distribution characteristics of the segment may solve this problem. Otherwise, regression equations specific for populations according to age, gender, race, and morphology may be required to provide accurate estimations of BSPs for use in kinetic equations of motion.     

The measurement of body segment inertial parameters using dual energy X-ray absorptiometry

Accurate body segment parameter (BSP) information is required for dynamic analyses of motion and the current methods available for obtaining these BSPs have been criticized. The purpose of this study was to determine whether dual energy X-ray absorptiometry (DXA) could accurately measure the BSPs of scanned objects and thus be used as a tool for measuring the BSPs of human subjects. Whole body mass (WBM) of 11 males was measured from a DXA scan and the values were compared to criterion scale-measured values by calculating the mean percent error. Two objects (plastic cylinder, human cadaver leg) were also scanned and DXA measurements of mass, length, centre of mass location (CM) and moment of inertia about the centre of mass (I_CM) were made using custom software. Criterion BSP measurements were then made and compared to DXA BSP values by calculating the percent error. Criterion I_CM measurements of the two objects were made using a pendulum technique and a second criterion I_CM calculation was made for the cylinder using a geometric formula. A mean percent error of −1.05% ±1.32% was found for WBM measurements of the human subjects. Errors for the cylinder and cadaver leg were under 3.2% for all BSPs except for I_CM when DXA was compared to the pendulum method (14.3% and 8.2% for cylinder and leg, respectively). The errors between DXA and the pendulum method were attributed to uncertainty in the pendulum technique (J. Biomech. 2002, in Review). I_CM error of the cylinder when DXA was compared to the geometric calculation was 2.63%. This error, combined with the low errors for all other BSPs, indicated that DXA can be used as a simple and accurate means of obtaining direct BSP information on living humans.     

Anthropometric and biomechanical characteristics of body segments in persons with spinal cord injury

People with spinal cord injury (SCI) experience bone and muscle loss in their paralyzed limbs that is most rapid and severe in the first 3 years after injury. Restoration of mechanical loading through therapeutic physical activity may potentially slow or reverse post-SCI bone loss, however, therapeutic targets cannot be developed without accurate biomechanical models. Obesity is prevalent among SCI population, and it alters body composition and further affects parameters of these models. Here, clinical whole body dual-energy X-ray absorptiometry data from people with acute (n = 39) and chronic (n = 61) SCI were analyzed to obtain anthropometric parameters including segment masses, center of mass location, and radius of gyration for both obese and non-obese individuals. Chronic SCI was associated with higher normalized trunk mass of 3.2%BW and smaller normalized leg mass of 1.8%BW in males, but no significant changes in segment centers of mass or radius of gyration. People with chronic SCI had 58.6% lean mass in the trunk, compared to 66.6% lean mass in those with acute SCI (p = 0.01), with significant changes in all segments. Obesity was associated with an increase in trunk mass proportion of 3.1%BW, proximal shifts in thigh and upper arm center of mass, and changes to thigh and shank radius of gyration. The data presented here can be used to accurately represent the anthropometrics of SCI population in biomechanical studies, considering obesity and injury duration.     

Changes in body segment inertial parameters of obese individuals with weight loss

Forward dynamic simulation of human movement has the potential to investigate the biomechanical effects of weight loss in obese individuals. However, guidelines for altering body segment inertial parameters (BSIPs) of a biomechanical model to approximate changes that occur with weight loss are currently unavailable. Therefore, the goal of this study was to quantify three-dimensional changes in BSIPs with weight loss. Nineteen Caucasian men of age 43.6+/-7.5 years (mean+/-standard deviation) were evaluated. Body mass and body mass index prior to weight loss were 102.7+/-3.6 kg and 32.6+/-3.2 kg/m2, respectively. Both before and after weight loss, magnetic resonance imaging scans were acquired along the length of the body to discriminate muscle, bone, organ, and adipose tissues. Segment masses, center of mass (COM) positions, and radii of gyration were determined from these scans using published tissue densities and established methods. A number of significant changes in BSIPs occurred with the 13.8+/-2.4% average weight loss. Mass decreased in all segments. COM position moved distally for the thigh and upper arm, superiorly for the trunk, and inferiorly for the whole body. Radius of gyration, in general, decreased in all segments. The changes in BSIPs with weight loss reported here could be used in forward dynamic simulations investigating the biomechanical implications of weight loss.     

A new geometric-based model to accurately estimate arm and leg inertial estimates

Segment estimates of mass, center of mass and moment of inertia are required input parameters to analyze the forces and moments acting across the joints. The objectives of this study were to propose a new geometric model for limb segments, to evaluate it against criterion values obtained from DXA, and to compare its performance to five other popular models. Twenty five female and 24 male college students participated in the study. For the criterion measures, the participants underwent a whole body DXA scan, and estimates for segment mass, center of mass location, and moment of inertia (frontal plane) were directly computed from the DXA mass units. For the new model, the volume was determined from two standing frontal and sagittal photographs. Each segment was modeled as a stack of slices, the sections of which were ellipses if they are not adjoining another segment and sectioned ellipses if they were adjoining another segment (e.g. upper arm and trunk). Length of axes of the ellipses was obtained from the photographs. In addition, a sex-specific, non-uniform density function was developed for each segment. A series of anthropometric measurements were also taken by directly following the definitions provided of the different body segment models tested, and the same parameters determined for each model. Comparison of models showed that estimates from the new model were consistently closer to the DXA criterion than those from the other models, with an error of less than 5% for mass and moment of inertia and less than about 6% for center of mass location.     

Differences in geriatric anthropometric data between DXA-based subject-specific estimates and non-age-specific traditional regression models

Age, obesity, and gender can have a significant impact on the anthropometrics of adults aged 65 and older. The aim of this study was to investigate differences in body segment parameters derived using two methods: (1) a dual-energy x-ray absorptiometry (DXA) subject-specific method (Chambers et al., 2010) and (2) traditional regression models (de Leva, 1996). The impact of aging, gender, and obesity on the potential differences between these methods was examined. Eighty-three healthy older adults were recruited for participation. Participants underwent a whole-body DXA scan (Hologic QDR 1000/W). Mass, length, center of mass, and radius of gyration were determined for each segment. In addition, traditional regressions were used to estimate these parameters (de Leva, 1996). A mixed linear regression model was performed (α = 0.05). Method type was significant in every variable of interest except forearm segment mass. The obesity and gender differences that we observed translate into differences associated with using traditional regressions to predict anthropometric variables in an aging population. Our data point to a need to consider age, obesity, and gender when utilizing anthropometric data sets and to develop regression models that accurately predict body segment parameters in the geriatric population, considering gender and obesity.     

MRI-derived body segment parameters of children differ from age-based estimates derived using photogrammetry

Body segment parameters are required when researching joint kinetics using inverse dynamics models. However, the only regression equations for estimating pediatric body segment parameters across a wide age range were developed, using photogrammetry, based on 12 boys and have not been validated to date (Jensen, R.K., 1986. Body segment mass, radius and radius of gyration proportions of children. Journal of Biomechanics 19, 359–368). To assess whether these equations could validly be applied to girls, we asked whether body segment parameters estimated by the equations differ from parameters measured using a validated magnetic resonance imaging (MRI) method. If so, do the differences cause significant differences in joint kinetics during normal gait? Body segment parameters were estimated from axial MRIs of the left thigh and shank of 10 healthy girls (9.6±0.9 years) and compared to those from Jensen's equations. Kinematics and kinetics were collected for 10 walking trials. Extrema in hip and knee moments and powers were compared between the two sets of body segment parameters. With the exception of the shank mass center and radius of gyration, body segment parameters measured using MRI were significantly different from those estimated using regression equations. These systematic differences in body segment parameters resulted in significant differences in sagittal-plane joint moments and powers during gait. Nevertheless, it is doubtful that even the greatest differences in kinetics are practically meaningful (0.3%BW×HT and 0.7%BW×HT/s for moments and power at the hip, respectively). Therefore, body segment parameters estimated using Jensen's regression equations are a suitable substitute for more detailed anatomical imaging of 8–10-year-old girls when quantifying joint kinetics during gait.     

DXA‐derived Abdominal Fat Mass,Waist Circumference,and Blood Lipids in Postmenopausal Women

The purpose of this study was to determine the utility of dual‐energy X‐ray absorptiometry (DXA)‐derived fat mass indices for predicting blood lipid profile in postmenopausal women. A secondary purpose was to determine whether waist circumference is comparable with DXA‐derived measurements in predicting blood lipid profile. Subjects were 423 postmenopausal women (age 58.1 ± 6.3 years). Fat mass was assessed at abdomen, trunk, and total body using DXA. Anthropometric measurements included BMI and waist circumference. Blood samples were analyzed for total cholesterol (TC), triglyceride (TAG), high‐density lipoprotein (HDL), low‐density lipoprotein (LDL), and cholesterol/HDL ratio. Of the DXA‐derived measures, abdominal‐fat mass was the best predictor of blood lipid profiles. DXA‐derived abdominal fat mass and waist girth explained 20 and 16.5% of variation in TC/HDL ratio, respectively, in univariate analysis, with no difference between the slopes of the regression coefficients. Eighty‐four percent of subjects were common to the top quartiles of waist circumference and abdominal fat mass, and blood lipid profiles generally worsened across increasing quartiles. DXA‐derived abdominal fat mass and waist circumference are of equivalent utility for predicting alterations in blood lipids. Waist circumference is, therefore, ideal as an inexpensive means in primary health‐care services for predicting risk of cardiovascular diseases in postmenopausal women.     

Using mass distribution information to model the human thigh for body segment parameter estimation

Accurate estimations of body segment inertial parameters (BSPs) are required to calculate the kinetics of motion. The purpose of this study was to develop a geometric model of the human thigh segment based on mass distribution properties determined from dual energy x ray absorptiometry (DEXA). One hundred subjects from four populations underwent a DEXA scan and anthropometric measurements were taken. The mass distribution properties of the thigh segment were determined for 20 subjects, a geometric model was developed, and the model was applied to the remaining 80 subjects. The model was validated by comparing to benchmark DEXA measurements. Four other popular models in the literature were also evaluated in the same manner No one set of predictors performed best for a particular group or BSP, however modeling the mass distribution properties of the segment allows the assumption of constant density while still accurately representing the inertial properties of the segment and provides promise for future development of BSP models.     

Patterns of subcutaneous fat deposition and the relationship between body mass index and waist-to-hip ratio: Implications for models of physical attractiveness

Body mass index (BMI) and waist-to-hip ratio (WHR) are two widely used anthropometric indices of body shape argued to convey different information about health and fertility. Both indices have also been shown to affect attractiveness ratings of female bodies. However, BMI and WHR are naturally positively correlated, complicating studies designed to identify their relative importance in predicting health and attractiveness outcomes. We show that the correlation between BMI and WHR depends on the assumed model of subcutaneous fat deposition. An additive model, whereby fat is added to the waist and hips at a constant rate, predicts a correlation between BMI and WHR because with increasing fat, the difference between the waist and hips becomes smaller relative to total width. This model is supported by longitudinal and cross-sectional data. We parameterised the function relating WHR to BMI for white UK females of reproductive age, and used this function to statistically decompose body shape into two independent components. We show that judgements of the attractiveness of female bodies are well explained by the component of curvaceousness related to BMI but not by residual curvaceousness. Our findings resolve a long-standing dispute in the attractiveness literature by confirming that although WHR appears to be an important predictor of attractiveness, this is largely explained by the direct effect of total body fat on WHR, thus reinforcing the conclusion that total body fat is the primary determinant of female body shape attractiveness.     

Food prices and body fatness among youths

We examine the effect of food prices on clinical measures of obesity, including body mass index (BMI) and percentage body fat (PBF) measures derived from bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA), among youths ages 12 through 18 in the National Health and Nutrition Examination Survey. This is the first study to consider clinically measured levels of body composition rather than BMI to investigate the effects of food prices on obesity outcomes among youths classified by gender and race/ethnicity. Our findings suggest that increases in the real price per calorie of food for home consumption and the real price of fast-food restaurant food lead to improvements in obesity outcomes among youths. We also find that a rise in the real price of fruits and vegetables leads to increased obesity. Finally, our results indicate that measures of PBF derived from BIA and DXA are no less sensitive and in some cases more sensitive to the prices just mentioned than BMI, and serve an important role in demonstrating that rising food prices (except fruit and vegetable prices) are indeed associated with reductions in obesity rather than with reductions in body size proportions alone.     

Estimating subject-specific body segment parameters using a 3-dimensional modeller program

The estimation of body segment properties is important in the biomechanical analysis of movement. Current subject-specific estimation methods however can be expensive and time-consuming, while other methods do not adequately take into account individual or group variability. We describe a simple procedure for estimating subject-specific geometric properties, independent of joint centres. The method requires only a small number of anthropometric measurements and digital images of the segment or subject, a 3-dimensional modeller program and simple mathematical calculations to estimate segment volumes and centroids. Assuming that the segment is of uniform density, it's mass and moment of inertia can also be derived. Future work should include generating segment density profiles for particular populations, to increase the accuracy of the method, and comparing the accuracy of the results obtained with those produced by other techniques.     

Non-invasive measure of body composition of snakes using dual-energy X-ray absorptiometry

Non-invasive techniques to measure body composition are critical for longitudinal studies of energetics and life histories and for investigating the link between body condition and physiology. Previous attempts to determine, non-invasively, the body composition of snakes have proven problematic. Therefore, we explored whether dual-energy X-ray absorptiometry (DXA) could be used to determine the body composition of snakes. We analyzed 20 adult diamondback water snakes (Nerodia rhombifer) with a DXA instrument and subsequently quantified their body composition by gravimetric and chemical extraction methods. Body composition components scaled with body mass with mass exponents between 0.88 and 1.53. DXA values for lean tissue mass, fat mass and total-body bone mineral mass were significantly correlated with observed masses of lean tissue, fat and ash from chemical analysis. Using regression models incorporating DXA values we predicted the fat-free tissue mass, lean tissue mass, fat mass, ash mass and total body water content for this sample of water snakes. A cross-validation procedure demonstrated that these models estimated fat-free tissue mass, lean tissue mass, fat mass, ash mass and total-body water content with respective errors of 2.2%, 2.3%, 16.0%, 6.6% and 3.5%. Compared to other non-invasive techniques, include body condition indices, total body electrical conductivity (TOBEC) and cyclopropane absorption, DXA can more easily and accurately be used to determine the body composition of snakes.     

Comparative analysis of methods for estimating arm segment parameters and joint torques from inverse dynamics

A common problem in the analyses of upper limb unfettered reaching movements is the estimation of joint torques using inverse dynamics. The inaccuracy in the estimation of joint torques can be caused by the inaccuracy in the acquisition of kinematic variables, body segment parameters (BSPs), and approximation in the biomechanical models. The effect of uncertainty in the estimation of body segment parameters can be especially important in the analysis of movements with high acceleration. A sensitivity analysis was performed to assess the relevance of different sources of inaccuracy in inverse dynamics analysis of a planar arm movement. Eight regression models and one water immersion method for the estimation of BSPs were used to quantify the influence of inertial models on the calculation of joint torques during numerical analysis of unfettered forward arm reaching movements. Thirteen subjects performed 72 forward planar reaches between two targets located on the horizontal plane and aligned with the median plane. Using a planar, double link model for the arm with a floating shoulder, we calculated the normalized joint torque peak and a normalized root mean square (rms) of torque at the shoulder and elbow joints. Statistical analyses quantified the influence of different BSP models on the kinetic variable variance for given uncertainty on the estimation of joint kinematics and biomechanical modeling errors. Our analysis revealed that the choice of BSP estimation method had a particular influence on the normalized rms of joint torques. Moreover, the normalization of kinetic variables to BSPs for a comparison among subjects showed that the interaction between the BSP estimation method and the subject specific somatotype and movement kinematics was a significant source of variance in the kinetic variables. The normalized joint torque peak and the normalized root mean square of joint torque represented valuable parameters to compare the effect of BSP estimation methods on the variance in the population of kinetic variables calculated across a group of subjects with different body types. We found that the variance of the arm segment parameter estimation had more influence on the calculated joint torques than the variance of the kinematics variables. This is due to the low moments of inertia of the upper limb, especially when compared with the leg. Therefore, the results of the inverse dynamics of arm movements are influenced by the choice of BSP estimation method to a greater extent than the results of gait analysis.     

Age variations in the relation of body mass indices to estimates of body fat and muscle mass

In some chronic disease studies, distinctions have been made regarding the importance of body mass index (BMI) as a risk factor in younger versus older men and women. In order to determine the significance of these differences in BMI-disease associations, we determined the extent of age-dependent variations in the relation of BMIs to body composition in large probability samples of U.S. men and women from the First and Second U.S. National Health and Nutrition Examination Surveys (NHANES I and II). BMIs are more highly correlated with estimates of body fat in younger than in older men and women, and with muscle mass in older than in younger adults. Caution should be exercised in interpreting the significance of BMI as a risk factor for chronic disease, particularly in comparison of age groups.     

Time discounting and the body mass index: Evidence from the Netherlands

In many Western countries, the relative weight of people -- measured by the body mass index (BMI) -- has increased substantially in recent years, leading to an increasing incidence of overweight and related health problems. As with many forms of risky behavior, it is plausible that overweight is related to the individual discount rate. Increases in credit card debts, the rise in gambling and the development of a more hedonic life style, suggest that the average discount rate has increased over time. An increase in time discounting may be a contributing factor in the rise in BMI. Applying a large set of indicators for the individual discount rate from a Dutch survey, this paper analyzes whether changes in time discounting can account for differences in body mass between individuals at a given point in time and whether changes in the average individual discount rate can explain the remarkable increase in BMI experienced in recent years in the Netherlands. We find some evidence for a link between time discounting and differences in BMI between people, but this relationship depends strongly on the choice of the proxy for the discount rate. Giving our hypothesis the best chance, we analyze the development of the time discounting proxies that are most strongly related to BMI. We find no evidence for a change of these proxies over time. Our main conclusion therefore is that overweight might be related to the way people discount future health benefits, but the increase in BMI is more likely explained by shifts in other parameters that determine the intertemporal decisions regarding the trade-off of current and future health and satisfaction.     

Anthropometric measures, body composition, body fat distribution, and knee osteoarthritis in women

Objective: Increased BMI is a well‐recognized risk factor for radiographic knee osteoarthritis (rKOA); however, the contributions of the components of body composition, body fat distribution, and height to this association are not clear. Research Methods and Procedures: We examined 779 women ≥45 years of age from the Johnston County Osteoarthritis Project. Body composition was assessed using DXA, and rKOA was defined as Kellgren‐Lawrence grade ≥2. Logistic regression models examined the association between rKOA and the fourth compared with the first quartiles of anthropometric, body composition, and fat distribution measures adjusting for age, ethnicity, and prior knee injury. Results: The adjusted odds ratios and 95% confidence interval of BMI and weight were 5.27 (3.05, 9.13) and 5.28 (3.05, 9.16), respectively. In separate models, higher odds of rKOA were also found for fat mass [4.54 (2.68, 7.69)], percent fat mass [3.84 (2.26, 6.54)], lean mass [3.94 (2.22, 6.97)], and waist circumference [4.15 (2.45, 7.02)]. Waist‐to‐hip ratio was not associated with rKOA [1.45 (0.86, 2.43)], and percent lean mass was associated with lower odds [0.20 (0.11, 0.35)]. Taller women had higher odds of rKOA after adjustment for BMI [1.77 (1.05, 3.00)]. Discussion: This study confirms that BMI and weight are strongly associated with rKOA in women and suggests that precise measurements of body composition and measures of fat distribution may offer no advantage over the more simple measures of BMI or weight in assessment of risk of rKOA.     

Joint axes of rotation and body segment parameters of pig limbs

To enable a quantification of net joint moments and joint reaction forces, indicators of joint loading, this study aimed to locate the mediolateral joint axes of rotation and establish the body segment parameters of the limbs of pigs (Sus scrofa). To locate the joint axes of rotation the scapulohumeral, humeroradial, carpal complex, metacarpophalangeal, coxofemoral, femorotibial, tarsal, and metatarsophalangeal joints from 12 carcasses were studied. The joints were photographed in three positions, bisecting lines drawn at fixed landmarks with their intersection marking the joint axes of rotation. The body segment parameters, i.e. the segment mass, center of mass and moment of inertia were measured on the humerus, radius/ulna, metacarpus, forepastern, foretoe, femur, tibia, metatarsus, hindpastern, and hindtoe segments from five carcasses. The segments were weighed, and their center of mass was found by balancing them. The moments of inertia of the humerus, radius/ulna, femur and tibia were found by rotating the segments. The moments of inertia of the remaining segments were calculated. Generally, the joint axes of rotation were near the attachment site of the lateral collateral ligaments. The forelimb, with segments taken as one, was significantly lighter and shorter than the hindlimb (P < 0.001). In all segments the center of mass was located 31 to 50% distal to the proximal segment end. The segment mass decreased with distance from the trunk, as did the segment moment of inertia. The results may serve as reference on the location of the joint axes of rotation and on the body segment parameters for inverse dynamic modeling of pigs.     

BMI, body composition, and physical functioning in older adults

Objective: Recent studies have emphasized the importance of muscle and fat mass in relation to age‐related decline in physical function. Our objective was to determine whether BMI, as a surrogate measurement of fat mass, may be used as a measure of risk factor for physical functioning in older adults and whether body composition measurements confer any advantage over BMI. Research Methods and Procedures: Four thousand men and women ≥65 years of age living in the community, stratified by age and sex, underwent the following measurements: body composition by DXA; grip strength; and timed 6‐m walk. Subjects were grouped into five categories of BMI using Asian criteria for health‐related risks, and between‐group differences in physical performance measures and body composition were analyzed using analysis of covariance adjusting for age, physical activity level, and presence of chronic disease. Results: Subjects in the two obese categories had a significantly greater number of instrumental activities of daily living (IADL) impairments compared with the underweight and normal‐weight groups. Those with BMI ≥30 kg/m² had the worst walking performance, and the groups with BMI in the normal and overweight range had optimal performance. Fat mass, but not appendicular muscle mass, was associated with walking speed after adjusting for BMI. Discussion: Fat mass seems to be a more important factor than appendicular muscle mass in determining walking speed in community‐living older adults, even after adjusting for BMI.