Application of three-dimensional body scanner: observation of prevalence of metabolic syndrome

Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study

BACKGROUND

3D laser-based photonic scanners are increasingly used in health studies to estimate body composition. However, too little is known about whether various 3D body scan measures estimate body composition better than single standard anthropometric measures, and which body scans best estimate it. Furthermore, little is known about differences by sex and age.

METHODS

105 men and 96 women aged between 18 and 90 years were analysed. Bioelectrical Impedance Analysis was used to estimate whole relative fat mass (RFM), visceral adipose tissue (VAT) and skeletal muscle mass index (SMI). An Anthroscan VITUSbodyscan was used to obtain 3D body scans (e.g. volumes, circumferences, lengths). To reduce the number of possible predictors that could predict RFM, VAT and SMI backward elimination was performed. With these selected predictors linear regression on the respective body compositions was performed and the explained variations were compared with models using standard anthropometric measurements (Body Mass Index (BMI), waist circumference (WC) and waist-to-height-ratio (WHtR)).

RESULTS

Among the models based on standard anthropometric measures, WC performed better than BMI and WHtR in estimating body composition in men and women. The explained variations in models including body scan variables are consistently higher than those from standard anthropometrics models, with an increase in explained variations between 5% (RFM for men) and 10% (SMI for men). Furthermore, the explained variation of body composition was additionally increased when age and lifestyle variables were added. For each of the body composition variables, the number of predictors differed between men and women, but included mostly volumes and circumferences in the central waist/chest/hip area and the thighs.

CONCLUSIONS

3D scan models performed better than standard anthropometric measures models to predict body composition. Therefore, it is an advantage for larger health studies to look at body composition more holistically using 3D full body surface scans.

Laser-Based 3D Body Scanning Reveals a Higher Prevalence of Abdominal Obesity than Tape Measurements: Results from a Population-Based Sample

BACKGROUND

The global obesity epidemic is a major public health concern, and accurate diagnosis is essential for identifying at-risk individuals. Three-dimensional (3D) body scanning technology offers several advantages over the standard practice of tape measurements for diagnosing obesity. This study was conducted to validate body scan data from a German population-based cohort and explore clinical implications of this technology in the context of metabolic syndrome.

METHODS

We performed a cross-sectional analysis of 354 participants from the Study of Health in Pomerania that completed a 3D body scanning examination. The agreement of anthropometric data obtained from 3D body scanning with manual tape measurements was analyzed using correlation analysis and Bland-Altman plots. Classification agreement regarding abdominal obesity based on IDF guidelines was assessed using Cohen's kappa. The association of body scan measures with metabolic syndrome components was explored using correlation analysis.

RESULTS

Three-dimensional body scanning showed excellent validity with slightly larger values that presumably reflect the true circumferences more accurately. Metabolic syndrome was highly prevalent in the sample (31%) and showed strong associations with central obesity. Using body scan vs. tape measurements of waist circumference for classification resulted in a 16% relative increase in the prevalence of abdominal obesity (61.3% vs. 52.8%).

CONCLUSIONS

These results suggest that the prevalence of obesity may be underestimated using the standard method of tape measurements, highlighting the need for more accurate approaches.

System for Estimation of Human Anthropometric Parameters Based on Data from Kinect v2 Depth Camera

Anthropometric measurements of the human body are an important problem that affects many aspects of human life. However, anthropometric measurement often requires the application of an appropriate measurement procedure and the use of specialized, sometimes expensive measurement tools. Sometimes the measurement procedure is complicated, time-consuming, and requires properly trained personnel. This study aimed to develop a system for estimating human anthropometric parameters based on a three-dimensional scan of the complete body made with an inexpensive depth camera in the form of the Kinect v2 sensor. The research included 129 men aged 18 to 28. The developed system consists of a rotating platform, a depth sensor (Kinect v2), and a PC computer that was used to record 3D data, and to estimate individual anthropometric parameters. Experimental studies have shown that the precision of the proposed system for a significant part of the parameters is satisfactory. The largest error was found in the waist circumference parameter. The results obtained confirm that this method can be used in anthropometric measurements.

Association of Physical Fitness Performance Tests and Anthropometric Indices in Taiwanese Adults

Background

The association between physical fitness performance tests and anthropometric indices is not clear. The study aims to explore the association between physical fitness performance and anthropometric indices in Taiwanese community-dwelling adults. This may help in monitoring anthropometric indices to improve physical fitness.

Methods

We recruited 2216 participants aged 23–64 years between 2014 and 2017. Physical fitness performance, including abdominal muscular endurance (60-s sit-up test), flexibility (sit-and-reach test), and cardiorespiratory endurance (3-min step test), was evaluated in all participants. The association of the physical fitness performance and anthropometric indices, including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR), was analyzed using linear regression, with adjustments for age and gender.

Results

Body mass index was negatively associated with abdominal muscular endurance (p < 0.001) and cardiorespiratory endurance (p < 0.001). Neither BMI, WC, WHR, nor WHtR were significantly associated with flexibility. Abdominal muscle endurance, flexibility, and cardiorespiratory endurance were significantly lower in obese participants when obesity was defined using a BMI of ≥27, 30, and 35 kg/m². Participants with central obesity that was defined as WC ≥ 90 cm in men and 80 cm in women and WHtR ≥ 0.6 had lower abdominal muscular endurance than those without central obesity.

Conclusion

Body mass index is associated with abdominal muscular endurance and cardiorespiratory endurance in a reverse J-shaped manner. None of the anthropometric indices are significantly associated with flexibility. Obesity defined by BMI is linked to worse physical fitness performance and obesity defined using WHtR is linked to lower abdominal muscular endurance in Taiwanese community-dwelling adults.

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men

INTRODUCTION

Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements.

METHODS

We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken.

RESULTS

Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements.

CONCLUSION

The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

The Impact of Education and Age on Metabolic Disorders

Metabolic disorders, such as obesity, elevated blood pressure, dyslipidemias, insulin resistance, hyperglycemia, and hyperuricemia have all been identified as risk factors for an epidemic of important and widespread chronic-degenerative diseases, such as type 2 diabetes and cardiovascular disease, that constitute some of the world's most important public health challenges. Their increasing prevalence can be associated with an aging population and to lifestyles within an obesogenic environment. Taking educational level as a proxy for lifestyle, and using both logistic and linear regressions, we study the relation between a wide set of metabolic biomarkers, and educational level, body mass index (BMI), age, and sex as correlates, in a population of 1,073 students, academic and non-academic staff at Mexico's largest university (UNAM). Controlling for BMI and sex, we consider educational level and age as complementary measures-degree and duration-of exposure to metabolic insults. Analyzing the role of education across a wide spectrum of educational levels (from primary school to doctoral degree), we show that higher education correlates to significantly better metabolic health when compared to lower levels, and is associated with significantly less risk for waist circumference, systolic blood pressure, glucose, glycosylated hemoglobin, triglycerides, high density lipoprotein and metabolic syndrome (all p < 0.05); but not for diastolic blood pressure, basal insulin, uric acid, low density lipoprotein, and total cholesterol. We classify each biomarker, and corresponding metabolic disorder, by its associated set of statistically significant correlates. Differences among the sets of significant correlates indicate various aetiologies and the need for targeted population-specific interventions. Thus, variables strongly linked to educational level are candidates for lifestyle change interventions. Hence, public policy efforts should be focused on those metabolic biomarkers strongly linked to education, while adopting a different approach for those biomarkers not linked as they may be poor targets for educational campaigns.

The aging human body shape

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40–80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications.

Body height and waist circumference of young Swiss men as assessed by 3D laser-based photonic scans and by manual anthropometric measurements

Overweight and obesity are considered among the major health concerns worldwide. The body mass index is a frequently used measure for overweight and obesity and is associated with common non-communicable diseases such as diabetes type II, cardiovascular diseases and certain cancers. However, the body mass index does not account for the distribution of body fat and relative fat to muscle mass. 3D laser-based photonic full body scans provide detailed information on various body circumferences, surfaces, and volumes as well as body height and weight (using an integrated scale). In the literature, body scans showed good feasibility, reliability, and validity, while also demonstrating a good correlation with health parameters linked to the metabolic syndrome. However, systematic differences between body scan derived measurements and manual measurements remain an issue. This study aimed to assess these systematic differences for body height, waist circumference, and body mass index using cross-sectional data from a homogenous sample of 52 young Swiss male volunteers. In addition to 3D laser-based photonic full body scans and correlative manual measurements, body fat distribution was assessed through bioelectrical impedance analysis. Overall, an excellent correlation was found between measurements of waist circumference and body mass index, and good correlation between body mass index and total fat mass, as well as between waist circumference and visceral fat mass as assessed by bioelectrical impedance analysis. Volunteers were shorter in height measured by body scan when compared to manual measurements. This systematic difference became smaller when volunteers stood in the scanner in a completely upright position with their feet together. Waist circumference was slightly smaller for manual measurements than for body scan derived values. This systematic difference was larger in overweight volunteers compared to leaner volunteers.

Perspective: Are We Ready to Measure Child Nutritional Status with Lasers?

The continued use of basic, manual anthropometric tools (e.g., boards and tapes) leaves anthropometry susceptible to human error. A potential solution, 3-dimensional (3D) imaging systems for anthropometry, has been around since the 1950s. In the 1980s, 3D imaging technology advanced from photographs to the use of lasers for body digitization; and by the 2000s, the falling price of 3D scanners made commercial application feasible. The garment sector quickly adopted imaging technology for surveys because of the need for numerous measurements and large sample sizes. In the health sector, 3D imaging for anthropometry was not widely adopted; its use was limited to research and specialized purposes. The different cost and logistical requirements for measurement in the garment and health sectors help to explain why the technology was adopted in one sector and not the other. Despite reductions, the price of 3D imaging systems remained a barrier to the use of 3D imaging for regular nutritional assessment in the health sector. Additional barriers in the health sector were that imaging systems required dedicated space and were not designed for capturing measurements in young children. In recent years, the development of light-coding technology may have removed these barriers, and a handheld imaging system was developed specifically for young children. There are not yet recommendations to replace manual equipment with 3D imaging for nutritional assessment, and there is a need for more research on low-cost, handheld imaging systems-particularly research that evaluates the ability of 3D imaging to improve the quality of anthropometric data and indicators.

A collaborative, mixed-methods evaluation of a low-cost, handheld 3D imaging system for child anthropometry

3D imaging for body measurements is regularly used for design of garments and ergonomic products. The development of low‐cost 3D scanners provided an opportunity to extend the use of 3D imaging to the health sector. We developed and tested the AutoAnthro System, the first mobile, low‐cost, full‐body, 3D imaging system designed specifically for child anthropometry. This study evaluated the efficiency, invasiveness, and user experience of the AutoAnthro System. We used a mixed‐methods, collaborative approach that included a quantitative time‐motion study and qualitative interviews of anthropometrists. For cooperative children, anthropometrists considered the use of 3D imaging an easy, “streamlined experience,” but with uncooperative children, anthropometrists reported that capturing a good quality scan was out of their control. The mean time to complete a full set of scans was 68 s (standard deviation [SD] 29), compared with 135 s (SD 22) for a set of manual measurements (stature, head circumference, and arm circumference). We observed that crying was more common during manual measurement, and anthropometrist interviews confirmed that 3D imaging was less stressful for children than manual measurement. In a previous publication, we showed the potential of 3D imaging to produce reliable and accurate measurements. In this study, we found that anthropometrists were not ready to abandon manual equipment for 3D scanners because of difficulty in measuring uncooperative children. Revising the AutoAnthro System to address anthropometrists' concerns on capturing good quality scans of uncooperative children should help to facilitate widespread use of 3D imaging for child anthropometry.

Comparison of 3D laser-based photonic scans and manual anthropometric measurements of body size and shape in a validation study of 123 young Swiss men

Background

Manual anthropometric measurements are time-consuming and challenging to perform within acceptable intra- and inter-individual error margins in large studies. Three-dimensional (3D) laser body scanners provide a fast and precise alternative: within a few seconds the system produces a 3D image of the body topography and calculates some 150 standardised body size measurements.

Objective

The aim was to enhance the small number of existing validation studies and compare scan and manual techniques based on five selected measurements. We assessed the agreement between two repeated measurements within the two methods, analysed the direct agreement between the two methods, and explored the differences between the techniques when used in regressions assessing the effect of health related determinants on body shape indices.

Methods

We performed two repeated body scans on 123 volunteering young men using a Vitus Smart XXL body scanner. We manually measured height, waist, hip, buttock, and chest circumferences twice for each participant according to the WHO guidelines. The participants also filled in a basic questionnaire.

Results

Mean differences between the two scan measurements were smaller than between the two manual measurements, and precision as well as intra-class correlation coefficients were higher. Both techniques were strongly correlated. When comparing means between both techniques we found significant differences: Height was systematically shorter by 2.1 cm, whereas waist, hip and bust circumference measurements were larger in the scans by 1.17–4.37 cm. In consequence, body shape indices also became larger and the prevalence of overweight was greater when calculated from the scans. Between 4.1% and 7.3% of the probands changed risk category from normal to overweight when classified based on the scans. However, when employing regression analyses the two measurement techniques resulted in very similar coefficients, confidence intervals, and p-values.

Conclusion

For performing a large number of measurements in a large group of probands in a short time, body scans generally showed good feasibility, reliability, and validity in comparison to manual measurements. The systematic differences between the methods may result from their technical nature (contact vs. non-contact).

Clinical anthropometrics and body composition from 3D whole-body surface scans

BACKGROUND/OBJECTIVES

Obesity is a significant worldwide epidemic that necessitates accessible tools for robust body composition analysis. We investigated whether widely available 3D body surface scanners can provide clinically relevant direct anthropometrics (circumferences, areas and volumes) and body composition estimates (regional fat/lean masses).

SUBJECTS/METHODS

Thirty-nine healthy adults stratified by age, sex and body mass index (BMI) underwent whole-body 3D scans, dual energy X-ray absorptiometry (DXA), air displacement plethysmography and tape measurements. Linear regressions were performed to assess agreement between 3D measurements and criterion methods. Linear models were derived to predict DXA body composition from 3D scan measurements. Thirty-seven external fitness center users underwent 3D scans and bioelectrical impedance analysis for model validation.

RESULTS

3D body scan measurements correlated strongly to criterion methods: waist circumference R2=0.95, hip circumference R2=0.92, surface area R2=0.97 and volume R2=0.99. However, systematic differences were observed for each measure due to discrepancies in landmark positioning. Predictive body composition equations showed strong agreement for whole body (fat mass R2=0.95, root mean square error (RMSE)=2.4 kg; fat-free mass R2=0.96, RMSE=2.2 kg) and arms, legs and trunk (R2=0.79-0.94, RMSE=0.5-1.7 kg). Visceral fat prediction showed moderate agreement (R2=0.75, RMSE=0.11 kg).

CONCLUSIONS

3D surface scanners offer precise and stable automated measurements of body shape and composition. Software updates may be needed to resolve measurement biases resulting from landmark positioning discrepancies. Further studies are justified to elucidate relationships between body shape, composition and metabolic health across sex, age, BMI and ethnicity groups, as well as in those with metabolic disorders.

Novel Anthropometry Based on 3D-Bodyscans Applied to a Large Population Based Cohort

Three-dimensional (3D) whole body scanners are increasingly used as precise measuring tools for the rapid quantification of anthropometric measures in epidemiological studies. We analyzed 3D whole body scanning data of nearly 10,000 participants of a cohort collected from the adult population of Leipzig, one of the largest cities in Eastern Germany. We present a novel approach for the systematic analysis of this data which aims at identifying distinguishable clusters of body shapes called body types. In the first step, our method aggregates body measures provided by the scanner into meta-measures, each representing one relevant dimension of the body shape. In a next step, we stratified the cohort into body types and assessed their stability and dependence on the size of the underlying cohort. Using self-organizing maps (SOM) we identified thirteen robust meta-measures and fifteen body types comprising between 1 and 18 percent of the total cohort size. Thirteen of them are virtually gender specific (six for women and seven for men) and thus reflect most abundant body shapes of women and men. Two body types include both women and men, and describe androgynous body shapes that lack typical gender specific features. The body types disentangle a large variability of body shapes enabling distinctions which go beyond the traditional indices such as body mass index, the waist-to-height ratio, the waist-to-hip ratio and the mortality-hazard ABSI-index. In a next step, we will link the identified body types with disease predispositions to study how size and shape of the human body impact health and disease.

Efficacy of thigh volume ratios assessed via stereovision body imaging as a predictor of visceral adipose tissue measured by magnetic resonance imaging

OBJECTIVES

The research examined the efficacy of regional volumes of thigh ratios assessed by stereovision body imaging (SBI) as a predictor of visceral adipose tissue measured by magnetic resonance imaging (MRI). Body measurements obtained via SBI also were utilized to explore disparities of body size and shape in men and women.

METHOD

One hundred twenty-one participants were measured for total/regional body volumes and ratios via SBI and abdominal subcutaneous and visceral adipose tissue areas by MRI.

RESULTS

Thigh to torso and thigh to abdomen-hip volume ratios were the most reliable parameters to predict the accumulation of visceral adipose tissue depots compared to other body measurements. Thigh volume in relation to torso [odds ratios (OR) 0.44] and abdomen-hip (OR 0.41) volumes were negatively associated with increased risks of greater visceral adipose tissue depots, even after controlling for age, gender, and body mass index (BMI). Irrespective of BMI classification, men exhibited greater total body (80.95L vs. 72.41L), torso (39.26L vs. 34.13L), and abdomen-hip (29.01L vs. 25.85L) volumes than women. Women had higher thigh volumes (4.93L vs. 3.99L) and lower-body volume ratios [thigh to total body (0.07 vs. 0.05), thigh to torso (0.15 vs. 0.11), and thigh to abdomen-hip (0.20 vs. 0.15); P < 0.05].

CONCLUSIONS

The unique parameters of the volumes of thigh in relation to torso and abdomen-hip, by SBI were highly effective in predicting visceral adipose tissue deposition. The SBI provided an efficient method for determining body size and shape in men and women via total and regional body volumes and ratios. Am. J. Hum. Biol. 27:445-457, 2015. © 2015 Wiley Periodicals, Inc.

Measurement of waist and hip circumference with a body surface scanner: feasibility, validity, reliability, and correlations with markers of the metabolic syndrome

Objective

Body surface scanners (BS), which visualize a 3D image of the human body, facilitate the computation of numerous body measures, including height, waist circumference (WC) and hip circumference (HC). However, limited information is available regarding validity and reliability of these automated measurements (AM) and their correlation with parameters of the Metabolic Syndrome (MetS) compared to traditional manual measurements (MM).

Methods

As part of a cross-sectional feasibility study, AM of WC, HC and height were assessed twice in 60 participants using a 3D BS (Vitus^smartXXL). Additionally, MM were taken by trained personnel according to WHO guidelines. Participants underwent an interview, bioelectrical impedance analysis, and blood pressure measurement. Blood samples were taken to determine HbA1c, HDL-cholesterol, triglycerides, and uric acid. Validity was assessed based on the agreement between AM and MM, using Bland-Altman-plots, correlation analysis, and paired t-tests. Reliability was assessed using intraclass correlation coefficients (ICC) based on two repeated AM. Further, we calculated age-adjusted Pearson correlation for AM and MM with fat mass, systolic blood pressure, HbA1c, HDL-cholesterol, triglycerides, and uric acid.

Results

Body measures were higher in AM compared to MM but both measurements were strongly correlated (WC, men, difference = 1.5cm, r = 0.97; women, d = 4.7cm, r = 0.96; HC, men, d = 2.3cm, r = 0.97; women, d = 3.0cm; r = 0.98). Reliability was high for all AM (nearly all ICC>0.98). Correlations of WC, HC, and the waist-to-hip ratio (WHR) with parameters of MetS were similar between AM and MM; for example the correlation of WC assessed by AM with HDL-cholesterol was r = 0.35 in men, and r = -0.48 in women, respectively whereas correlation of WC measured manually with HDL cholesterol was r = -0.41 in men, and r = -0.49 in women, respectively.

Conclusions

Although AM of WC, HC, and WHR are higher when compared to MM based on WHO guidelines, our data indicate good validity, excellent reliability, and similar correlations to parameters of the MetS.

Waist-to-height ratio is the best indicator for undiagnosed type 2 diabetes

AIMS

Early detection of diabetes is important for the prevention of diabetic complications. The best adiposity index for indicating Type 2 diabetes mellitus remains unclear. We aimed to identify the optimal adiposity measure among BMI, waist circumference, waist-hip ratio and waist-to-height ratio to indicate undiagnosed Type 2 diabetes and impaired fasting glucose in Chinese adults.

METHODS

A total of 7567 participants aged 20-79 years were included in this study. Impaired fasting glucose was defined as a fasting plasma glucose level of 6.1-6.9 mmol/l in participants without diabetes. Undiagnosed Type 2 diabetes was identified as fasting plasma glucose ≥ 7.0 mmol/l when neither a history of diabetes nor use of hypoglycaemic drugs was present. Body weight, height, waist and hip circumferences were measured following standard procedures. Data were analysed using logistic regression and areas under the receiver operating characteristic curves.

RESULTS

Of the 7567 participants, 536 were defined as having impaired fasting glucose and 690 were patients with Type 2 diabetes, including 290 (3.8%) persons with undiagnosed diabetes. In multivariate logistic regression, the odds ratios of waist-to-height ratio (≥ 0.5) were stronger than BMI (≥ 24 kg/m²), waist circumference (≥ 85 cm in men and ≥ 80 cm in women) and waist-hip ratio (≥ 0.85) for undiagnosed Type 2 diabetes and impaired fasting glucose. Among the four indices, waist-to-height ratio ≥ 0.5 showed the largest area under the receiver operating characteristic curve for diagnosing undiagnosed Type 2 diabetes (0.725, 95% CI 0.693-0.756) and impaired fasting glucose (0.662, 95% CI 0.638-0.687).

CONCLUSIONS

By comparison with BMI, waist circumference and waist-hip ratio, waist-to-height ratio ≥ 0.5 may be the best indicator for undiagnosed Type 2 diabetes and impaired fasting glucose.

Evaluation of a rotary laser body scanner for body volume and fat assessment

This paper reports the evaluation tests on the reliability and validity of a 3-dimensional (3D) laser body scanner for estimation of body volume and % fat. Repeated measures of body imaging were performed for reproducibility analysis. Validity of the instrument was assessed by comparison of measures of body volume by imaging to hydrodensitometry, and body fat was compared to hydrodensitometry and dual energy X-ray absorptiometry. Reproducibility analysis showed little difference between within-subjects measurements of volume (ICC ≥ 0.99, p < 0.01). Body volume estimations by laser body scanner and hydrodensitometry were strongly related (r = 0.99, p < 0.01), and agreement was high (ICC = 0.99, p < 0.01). Measurements of % body fat also agreed strongly with each other between methods (ICC = 0.86, p < 0.01), and mean % fat estimates by body imaging did not differ from criterion methods (p > 0.05). These findings indicate that the 3D laser body scanner is a reliable and valid technique for the estimation of body volume. Furthermore, body imaging is an accurate measure of body fat, as compared to dual energy X-ray absorptiometry. This new instrument is promising as a quick, simple to use, and inexpensive method of body composition analysis.

Validation of the body scanner as a measuring tool for a rapid quantification of body shape

BACKGROUND

Currently, the body scanner, using laser-triangulation, is one of the most precise measuring tools for the rapid quantification of body shape. The VITUS body scanner is a laser-based system based on a principle called triangulation and the scan produced describes the distance to a surface at each point in the picture. The body scanner has multiple applications such as determining body measurements for tailoring, anthropometric investigations and cosmetic surgery. There are also intensive investigations into the effect of weight gain and thus body shape on health risks. In order to be of value, the body scanner needs to generate precise, accurate and reproducible data.

AIMS

To determine the precision and reproducibility of the VITUS XXL 3D body scanner.

METHODS

The measurements of geometric shapes (cones, columns) and human body parts (mid-thigh) were compared using a measuring tape and the body scanner.

RESULTS

The precision of the measurements of the circumferences of a truncated cone and a column was within 1 mm of the actual values (0.29%). The reproducibility of the measurements was very good. The standard deviation in the measurement of a truncated cone was only 0.13% of the actual value. Likewise, the standard deviation of the thigh measurement of 12 human subjects was <1%.

CONCLUSION

These results show that the body scanner can accurately, precisely and reproducibly measure the circumference of objects and human body parts.

Association Between Elevated Liver Enzymes and Metabolic Syndrome Among Thai Adults

BACKGROUND

To examine the relation between elevated liver marker concentrations (alanine aminotransferase [ALT], aspartate aminotransferase [AST], and alkaline phosphatase [ALP]) and risk of metabolic syndrome (MetS).

METHODS

This cross-sectional study was comprised of 1,391 Thai participants (451 men and 940 women) receiving annual health check-ups. Multivariable logistic regression procedures were used to estimate odds ratios (OR) and 95% confidence intervals (95%CI) of MetS risk according to quartiles of each liver marker concentration with the lowest quartile specified as the referent group.

RESULTS

Overall, mean concentrations of AST, ALT and ALP increased and mean AST:ALT ratio decreased with increasing presence of metabolic abnormalities (p-value=0.059 for AST in men, all other p-values <0.001). After adjusting for confounders, men with ALT concentrations in the extreme quartiles (>40 units/L), had a 2.77-fold increased risk of MetS (95%CI: 1.18-6.53), as compared with men who had values in the lowest quartile (≤21 units/L). The OR for extreme quartiles of ALP concentrations was 3.72 (95%CI: 1.49-9.29). In women, elevated ALT concentrations were also associated with MetS risk. Those with the highest ALT concentrations (>23 units/L) had a 2.55-fold increased risk of MetS (95%CI: 1.22-5.35) compared to women with concentrations ≤13 units/L.

CONCLUSIONS

These findings add to an emerging body of literature that suggests elevated liver enzymes may be related with MetS risk. However, prospective studies are needed to more fully determine the practical value of elevated liver enzymes as a clinical risk predictor of MetS and related disorders among Thai adults.

Diazoxide prevents abdominal adiposity and fatty liver in obese OLETF rats at prediabetic stage

Epidemiological studies in both humans and experimental animals have shown an association between visceral obesity and cardiovascular risk factors such as dyslipidemia, hyperinsulinemia, and type 2 diabetes mellitus. The objective of this study was to evaluate the effects of diazoxide, an inhibitor of glucose-stimulated insulin secretion, on the prevention of fat deposition in the liver and in the abdominal cavity of prediabetic rats. Otsuka Long-Evans Tokushima Fatty (OLETF) rats, which are a well-established animal model of human obesity, were used. Diazoxide (25 mg/kg/day) was administered from 8 to 30 weeks of age. Various fat distribution parameters, including computerized tomography imaging, histopathological examination, lipid metabolism, and insulin resistance, were determined in prediabetic OLETF rats. Occurrences of abdominal adiposity and fatty liver were markedly reduced by diazoxide treatment. Diazoxide significantly lowered hyperinsulinemia, triglycerides, free fatty acid levels, insulin resistance, weight gain, and food intake. In addition, it inhibited the development of diabetes in these animals. Linear regression assay demonstrated a close correlation between decreasing hyperinsulinemia and the protective effects of diazoxide. The present study demonstrates that diazoxide treatment in obese OLETF rats at prediabetic stage prevents abdominal obesity and fat deposition in the liver. These metabolic changes may occur through a direct effect on beta-cells through reduction of their workload and suppression of insulin secretion.

Serum uric acid and leptin levels in metabolic syndrome: a quandary over the role of uric acid

This study investigates the impact of uric acid (UA) on the risk factors associated with metabolic syndrome. In addition, this study explores the relationship between UA and insulin resistance and serum leptin levels in metabolic syndrome. A total of 470 subjects (252 women and 218 men) were recruited from the Department of Health Management at Chang Gung Medical Center (Linkou, Taiwan). Metabolic syndrome was defined using a modified Adult Treatment Panel III (ATP III) definition. The formula for the homeostasis model assessment of insulin resistance (HOMA-IR) is as follows: fasting serum insulin (microU/mL) x fasting plasma glucose (mmol/L)/22.5. Diabetes mellitus was diagnosed in 45 subjects (9.6%); 82 subjects (17.4%) had hypertension. Hyperuricemia was diagnosed in 144 subjects (30.6%). Of these subjects, 115 (63 females and 52 males) (24.5%) were diagnosed as having metabolic syndrome. Patients with hyperuricemia had increased body mass index, waist-to-hip ratio, and triglyceride (Tg) level. The subjects also had lower high-density lipoprotein and greater hypertension. Hormone assays showed an elevation of leptin, immunoreactive insulin (IRI), and HOMA-IR in the hyperuricemia group. Uric acid appeared to be better correlated with Tg, blood pressure (both systolic and diastolic), obesity, immunoreactive insulin, and HOMA-IR. Uric acid did not correlate with leptin or blood glucose levels. Metabolic syndrome and Tg/high-density lipoprotein ratio showed a statistically significant difference in HOMA-IR using 3.8 as a cutoff value. Otherwise, there was no difference in leptin value. In conclusion, serum UA is significantly related to risk factors of metabolic syndrome except for blood glucose. Waist-to-hip ratio and HOMA-IR were statistically different in subjects with and without metabolic syndrome.

[Blood uric acid levels in patients with sleep-disordered breathing]

OBJECTIVE

Recurrent hypoxia associated with sleep apnea-hypopnea syndrome (SAHS) leads to an increase in the degradation of adenosine triphosphatase to xanthine and, secondarily, to an increase in uric acid concentrations. The aim of the present study was to determine whether there is a correlation between uric acid levels in peripheral blood and sleep-disordered breathing, independently of known confounding factors.

PATIENTS AND METHODS

We carried out a retrospective cross-sectional study of 1135 patients evaluated for suspected SAHS. For all patients, a medical history was taken using a standardized protocol. In addition, biochemical analysis of venous blood and an overnight sleep study (with either conventional polysomnography or home monitoring) were carried out.

RESULTS

The mean (SD) concentration of uric acid was 6.31 (1.5) mg/dL, and 36% of patients had concentrations above established normal values for their sex. We found a significant correlation between uric acid levels and some sleep study parameters (number of respiratory events, number of desaturations, or the cumulative percentage of time with oxygen saturation less than 90%). Those patients with more respiratory events (apnea-hypopnea index or respiratory event index >or= 30) had higher uric acid levels than those with mild or no SAHS. However, this difference was not apparent in the univariate analysis of variance, in which body mass index and cholesterol and triglyceride levels were considered confounding factors.

CONCLUSIONS

Uric acid levels are positively correlated with the number of obstructive respiratory episodes and oxygen desaturations during sleep, but this correlation seems to be influenced by other factors, such as obesity.

Association of hematological factors with components of the metabolic syndrome in older and younger adults

BACKGROUND AND AIMS

This study retrospectively examined the characteristics of metabolic syndrome in an aged population and assessed the risk factors for these subjects.

METHODS

A total of 1332 aged subjects (> or =65 years; mean age 71.0+/-5.0 years) were enrolled from 6903 subjects recruited from the Department of Health Management at Chang Gung Medical Center. Of these 6903 subjects, 1665 (814 females and 851 males) were diagnosed with metabolic syndrome. Whole body three-dimensional (3- D) laser scanning was employed for anthropometric measurements. Furthermore, health index (HI) was derived by the following equation: HI = (body weight x 2 x waist area) / [body height2 x (breast area + hip area)].

RESULTS

Among the 6903 subjects, no significant difference in gender was noted between groups with and without metabolic syndrome (p=0.142). For subjects >64 years, the incidence of metabolic syndrome in females is higher than in males. Subjects are categorized into four groups based on age and whether they had metabolic syndrome. Group A (4402 cases) consists of subjects <65 years old without metabolic syndrome. Group B (836 cases) comprises subjects >64 years old and without metabolic syndrome. Group C (1169 cases) contains subjects <65 years old with metabolic syndrome and group D (496 cases) is composed of subjects >64 years old with metabolic syndrome. Of the aged 1332 subjects, 595 were females (mean age, 70.6+/-4.6 years) and 737 were males (mean age, 71.3+/-5.3years), 37.2% (496/1332) had metabolic syndrome, 19.9% had DM and 21.8% had hypertension. These subjects had decreased BMI with age. Additionally, WHR peaked at an age range of 75-79 years. Of the aged subjects, also overweight, 42.8% and 33.6% were diagnosed with hypertension and DM, respectively; both ratios higher than those for non-overweight subjects (25.3% and 26.2%, respectively). Of the four groups in this study, the ratios for DM, hypertension, and WHR, HI, and LDL levels progressively increased through groups A to D. WBC count differs statistically significantly between these groups. Statistical analysis of WBC count, RBC and hemoglobin (Hb) with different parameters demonstrates significant elevation of WBC counts with the components of metabolic syndrome in aged subjects.

CONCLUSIONS

WBC count, RBC count and Hb are associated with metabolic syndrome components in younger and old adults of both genders. The incidence of metabolic syndrome marker increased after menopause onset in the female population in this study.

Influence of body fat content and distribution on variation in metabolic risk

OBJECTIVES

Several reports indicate that the body fat compartments, especially ip fat, predict metabolic risk better than total body fat. The objective of the study was to determine whether this can be confirmed and generalized throughout the population.

PARTICIPANTS

A representative sample of 1934 Black and White women and men of the Dallas Heart Study participated in the study.

DESIGN

We measured the fat in total body, trunk, and lower body with dual-energy x-ray absorptiometry and in abdominal compartments (sc, ip, and retroperitoneal) with magnetic resonance imaging. Other measurements included body mass index (BMI), waist circumference, blood pressure, plasma lipids, glucose, insulin (including homeostasis model), and C-reactive protein.

RESULTS

In all groups, total body fat correlated positively with key metabolic risk factors, i.e. homeostasis model, triglyceride/high-density lipoprotein-cholesterol ratios, C-reactive protein, and blood pressure; however, it explained less than one third of the variability of all the risk factors. After adjustment for total body fat, truncal fat conferred additional positive correlation with risk factors. Furthermore, with multivariable regression analysis, ip fat conferred independent correlation with plasma lipids beyond a combination of other compartments including truncal fat. Still, except for insulin levels, all combinations including ip fat still explained less than one third of the variability in risk-factor levels. Conversely, lower body fat correlated negatively with risk factors; i.e. lower body fat appeared to offer some protection against risk factors.

CONCLUSIONS

Body fat distribution has some influence on risk factors beyond total body fat content. Both waist circumference and BMI significantly predicted risk factors after adjustment for total body fat, and for clinical purposes, most of the predictive power for men was contained in waist circumference, whereas for women, BMI and waist circumference were similarly predictive. Finally, even though the correlations between combined body fat parameters and risk factors explained only a portion of the variation in the latter, the average number of categorical metabolic risk factors increased progressively with increasing obesity. Hence, obesity seemingly has more clinical impact than revealed in these correlative studies.