Improved Prediction of Body Fat by Measuring Skinfold Thickness, Circumferences, and Bone Breadths

Submandibular Skinfold Thickness Cut-off Values in Relation to Body Mass Index and Percentage Body Fat Among Chilean Adolescents

The present study evaluates submandibular skinfold (SMS) cutoff values to estimate excess weight for BMI and percentage body fat (%BF) among Chilean adolescents. The results show an optimal area under the cutoff curve value of 83% among girls and 91% in boys to estimate SMS concerning %BF and BMI. The SMS cutoff value estimating obesity by %BF was 10 mm among girls and 9 mm among boys, 10 mm among girls, and 7 mm among boys by BMI. Our results showed that SMS is significantly associated with anthropometric parameters for obesity.

Criterion-Related Validity of Field-Based Methods and Equations for Body Composition Estimation in Adults: A Systematic Review

PURPOSE OF REVIEW

Overweight and obesity are associated to health prognosis. Therefore, body composition assessment is an important health outcome, especially in adult population. We analyzed the criterion-related validity of existing field-based methods and equations for body composition estimation in adults aged 19-64 years.

RECENT FINDINGS

One hundred studies met inclusion criteria. The field-based methods, waist circumference (WC), body adiposity index (BAI), and body mass index (BMI) are valid to indicate body adiposity. Likewise, several equations, including the classical Durnin/Womersley equation, Jackson/Pollock equation (males), and Jackson, Pollock, and Ward equation (females), are valid to estimate total body fat mass or body fat percentage. Anthropometric field methods can provide a simple, quick, and easy informative indicators of adiposity in adults. Classical equations, such as Durnin/Womersley equation, Jackson/Pollock equation, and Jackson, Pollock, and Ward equation, are still valid to estimate total body fat mass or body fat percentage in adult population. When choosing estimation equations, specific population characteristics, such as age, weight status, or race ethnicity, should be taken into account. (Trial Registration: Registered on PROSPERO (CRD42020194272)).

Italian Ketogenic Mediterranean Diet in Overweight and Obese Patients with Prediabetes or Type 2 Diabetes

Obesity is a multifactorial disease strongly associated with insulin resistance and/or type 2 diabetes mellitus. Correct nutrition represents a valid strategy to fight these dysmetabolic pathologies responsible for numerous diseases, including inflammatory and cardiovascular ones. Medical nutrition therapy, including a Mediterranean diet (MD) and a very low-calorie ketogenic diet (VLKCD), is the first-line treatment for prediabetes/diabetes and overweight/obesity. Eighty patients (forty women and forty men) affected by overweight/obesity and type 2 diabetes mellitus or impaired glucose tolerance or impaired fasting glucose (51 (ys) ± 1.75; BMI (kg/m2) 33.08 ± 1.93; HA1c (%): 6.8% ± 0.25) were enrolled at the University Service of Diet Therapy, Diabetology and Metabolic Diseases, Policlinico Riuniti Hospital of Foggia, and subjected to a very-low-calorie Mediterranean diet and a very-low-calorie ketogenic Mediterranean diet for thirty days. Both diets result in a marked decrease in body weight (kg) and BMI (kg/m2). At the same time, only the very-low-calories ketogenic Mediterranean diet reduced waist and hip circumferences. Both diets helped reduce fat mass, but a major loss was achieved in a very low-calorie ketogenic Mediterranean diet. Among gluco-metabolic parameters, only the very-low-calorie ketogenic Mediterranean diet group showed a significant decrease in fasting blood glucose and HbA1c, insulin, C-peptide total cholesterol, LDL, and triglycerides. The results of our study seem to show that the very-low-calorie ketogenic Mediterranean diet is a good strategy to improve rapidly metabolic, anthropometric, and body composition parameters in patients with prediabetes or diabetes and overweight/obesity.

Cavitation and radiofrequency versus cryolipolysis on leptin regulation in central obese subjects: A randomized controlled study

BACKGROUND AND OBJECTIVE

To investigate the efficacy of adding ultrasound cavitation and radiofrequency versus cryolipolysis to weight reduction program on leptin, insulin, waist circumference, skinfold, body weight in central obese subjects.

MATERIAL AND METHODS

Sixty centrally obese participants were randomly allocated into three equal groups. Subjects in the study group (I) received cavitation and radiofrequency plus dietary regimen, subjects in the second study group (II) received cryolipolysis in conjunction with the same diet program, and subjects in the control group (III) received the same dietary regimen only. Leptin, insulin level, waist circumference, skinfold, body weight, and body mass index were measured shortly before intervention techniques and 3 months afterward.

RESULTS

There were no statistically significant differences between cavitation plus radiofrequency and cryolipolysis on leptin and insulin levels after 3 months of intervention. However, statistically significant differences were found in waist circumference, skinfold, weight reduction, and body mass index in favor of the cavitation group (p < 0.05). In addition, both cavitation-radiofrequency and cryolipolysis were statistically significantly different than the diet alone in favor of the study groups (p < 0.05) in all the outcome measures. Furthermore, there were statistically significant differences in all outcome measures (p < 0.05) when comparing the baseline and postintervention results in each group except for leptin level in the diet group (p = 0.14).

CONCLUSION

Subjects who underwent cavitation plus radiofrequency had better improvement on waist circumference, skinfold, and body mass index than subjects who received cryolipolysis. However, no differences were found between cavitation plus radiofrequency and cryolipolysis on leptin and insulin levels.

Randomized boosting with multivariable base-learners for high-dimensional variable selection and prediction

BACKGROUND

Statistical boosting is a computational approach to select and estimate interpretable prediction models for high-dimensional biomedical data, leading to implicit regularization and variable selection when combined with early stopping. Traditionally, the set of base-learners is fixed for all iterations and consists of simple regression learners including only one predictor variable at a time. Furthermore, the number of iterations is typically tuned by optimizing the predictive performance, leading to models which often include unnecessarily large numbers of noise variables.

RESULTS

We propose three consecutive extensions of classical component-wise gradient boosting. In the first extension, called Subspace Boosting (SubBoost), base-learners can consist of several variables, allowing for multivariable updates in a single iteration. To compensate for the larger flexibility, the ultimate selection of base-learners is based on information criteria leading to an automatic stopping of the algorithm. As the second extension, Random Subspace Boosting (RSubBoost) additionally includes a random preselection of base-learners in each iteration, enabling the scalability to high-dimensional data. In a third extension, called Adaptive Subspace Boosting (AdaSubBoost), an adaptive random preselection of base-learners is considered, focusing on base-learners which have proven to be predictive in previous iterations. Simulation results show that the multivariable updates in the three subspace algorithms are particularly beneficial in cases of high correlations among signal covariates. In several biomedical applications the proposed algorithms tend to yield sparser models than classical statistical boosting, while showing a very competitive predictive performance also compared to penalized regression approaches like the (relaxed) lasso and the elastic net.

CONCLUSIONS

The proposed randomized boosting approaches with multivariable base-learners are promising extensions of statistical boosting, particularly suited for highly-correlated and sparse high-dimensional settings. The incorporated selection of base-learners via information criteria induces automatic stopping of the algorithms, promoting sparser and more interpretable prediction models.

Direct Comparison of (Anthropometric) Methods for the Assessment of Body Composition

OBJECTIVE

Several methods for the assessment of body composition exist, yet they yield different results. The present study aimed to assess the extent of these differences on a sample of young, healthy subjects. We hypothesised that differences in body composition results obtained with different methods will vary to the extent that a subject can be misclassified into different nutritional categories.

RESEARCH METHODS AND PROCEDURES

Underwater weighing (UWW), bioelectrical impedance analysis (BIA), anthropometry (ANT), and dual-energy X-ray absorptiometry (DXA) were used to assess body composition. An extensive list of ANT regression equations (or sets of equations) was analysed in terms of accuracy and precision relative to DXA.

RESULTS

When DXA-determined body fat (BF) values were taken as a reference, UWW overestimated BF in both genders. In contrast, BIA (measured with a given bioimpedance analyser) underestimated BF in females, although BIA-determined BF did not differ from DXA in males. A huge difference in BF estimates (8-29% for females and 6-29% for males, for DXA-determined BF of 25.5% and 13.9% for females in males, respectively) was observed across a number of ANT regression equations; yet, ANT proved not to be inferior to DXA, provided that regression equations with the highest combinations of accuracy and precision were chosen.

CONCLUSIONS

The study proved grounds for comparison of body composition results of young, healthy subjects, obtained with different methods and across a wide range of ANT regression equations. It also revealed a list of the most appropriate ANT regression equations for the selected sample and reported their accuracy and precision.

Association of Metabolic Markers with self-reported osteoarthritis among middle-aged BMI-defined non-obese individuals: a cross-sectional study

BACKGROUND

Osteoarthritis (OA) is a chronic degenerative joint disease. While it is well-established that obesity affects OA through increased axial loading on the joint cartilage, the indirect effect of obesity through metabolic processes among the body mass index (BMI)-defined non-obese population, i.e., BMI < 30 kg/m2, is less known. Our goal was to evaluate the association of metabolic markers including body fat percentage (BF%), waist circumference, maximum weight gain during adulthood and serum creatinine with self-reported OA to establish if such measures offer additional information over BMI among the non-obese population between 40 and 65 years of age.

METHODS

Cross-sectional data from two cycles of the Canadian Health Measures Survey (CHMS) in 2007-2009 and 2009-2011 were analyzed. Sex-specific logistic regression models were developed to evaluate the association of self-reported OA with metabolic markers. Models were separately adjusted for age, BMI categories and serum creatinine, and a stratified analysis across BM categories was performed. In a secondary analysis, we evaluated the association of self-reported OA, cardiovascular diseases and hypertension across BF% categories.

RESULTS

Of 2462 individuals, 217 (8.8%) self-reported OA. After adjusting for age and BMI, those within BF%-defined overweight/obese category had 2.67 (95% CI: 1.32-3.51) and 2.11(95% CI: 1.38-3.21) times higher odds of reporting self-reported OA compared to those within BF%-defined athletic/acceptable category for females and males, respectively. BF% was also significantly associated with self-reported OA after adjusting for age and serum creatinine only among females (OR: 1.47, 95%CI: 1.12-1.84). Furthermore, among the BMI-defined overweight group, the age-adjusted odds of self-reported OA was significantly higher for overweight/obese BF% compared to athletic/acceptable BF% in both females and males. In a secondary analysis, we showed that the association of self-reported OA and hypertension/cardiovascular diseases is significantly higher among BF% overweight/obese (OR: 1.37, 95%CI: 1.19-3.09) compared to BF% athletic/acceptable (OR: 1.13, 95%CI: 0.87-2.82).

CONCLUSION

Our results provide corroborating evidence for a relationship between body fat and OA in a population-based study, while no significant independent correlates were found between other metabolic markers and OA prevalence. Future investigation on the longitudinal relationship between BF and OA among this sub-population may inform targeted prevention opportunities.

Accuracy of Anthropometric Equations for Estimating Body Fat in Professional Male Soccer Players Compared with DXA

Background

There are several published anthropometric equations to estimate body fat percentage (BF%), and this may prompt uncertainty about their application.

Purpose

To analyze the accuracy of several anthropometric equations (developed in athletic [AT] and nonathletic [NAT] populations) that estimate BF% comparing them with DXA.

Methods

We evaluated 131 professional male soccer players (body mass: 73.2 ± 8.0 kg; height: 177.5 ± 5.8 cm; DXA BF% [median, 25th–75th percentile]: 14.0, 11.9–16.4%) aged 18 to 37 years. All subjects were evaluated with anthropometric measurements and a whole body DXA scan. BF% was estimated through 14 AT and 17 NAT anthropometric equations and compared with the measured DXA BF%. Mean differences and 95% limits of agreement were calculated for those anthropometric equations without significant differences with DXA.

Results

Five AT and seven NAT anthropometric equations did not differ significantly with DXA. From these, Oliver's and Civar's (AT) and Ball's and Wilmore's (NAT) equations showed the highest agreement with DXA. Their 95% limits of agreement ranged from −3.9 to 2.3%, −4.8 to 1.8%, −3.4 to 3.1%, and −3.9 to 3.0%, respectively.

Conclusion

Oliver's, Ball's, Civar's, and Wilmore's equations were the best to estimate BF% accurately compared with DXA in professional male soccer players.

Novel Body Shape Descriptors for Abdominal Adiposity Prediction Using Magnetic Resonance Images and Stereovision Body Images

OBJECTIVE

The purpose of this study was to design novel shape descriptors based on three-dimensional (3D) body images and to use these parameters to establish prediction models for abdominal adiposity.

METHODS

Sixty-six men and fifty-five women were recruited for abdominal magnetic resonance imaging (MRI) and 3D whole-body imaging. Volumes of abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were measured from MRI sequences by using a fully automated algorithm. The shape descriptors were measured on the 3D body images by using the software developed in this study. Multiple regression analysis was employed on the training data set (70% of the total participants) to develop predictive models for VAT and SAT, with potential predictors selected from age, BMI, and the body shape descriptors. The validation data set (30%) was used for the validation of the predictive models.

RESULTS

Thirteen body shape descriptors exhibited high correlations (P < 0.01) with abdominal adiposity. The optimal predictive equations for VAT and SAT were determined separately for men and women.

CONCLUSIONS

Novel body shape descriptors defined on 3D body images can effectively predict abdominal adiposity quantified by MRI.

Association of body mass index (BMI) and percent body fat among BMI-defined non-obese middle-aged individuals: Insights from a population-based Canadian sample

OBJECTIVES

To evaluate the association between percent body fat (%BF) and body mass index (BMI) among BMI-defined non-obese individuals between 40 and 69 years of age using a population-based Canadian sample.

DATA AND METHODS

Cross-sectional data from the Canadian Health Measures Survey (2007 and 2009) was used to select all middle-aged individuals with BMI &lt; 30 kg/m2 (n = 2,656). %BF was determined from anthropometric skinfolds and categorized according to sex-specific equations. Association of other anthropometry measures and metabolic markers were evaluated across different %BF categories. Significance of proportions was evaluated using chi-squared and Bonferroni-adjusted Wald test. Diagnostic performance measures of BMI-defined overweight categories compared to those defined by %BF were reported.

RESULTS

The majority (69%) of the sample was %BF-defined overweight/obese, while 55% were BMI-defined overweight. BMI category was not concordant with %BF classification for 30% of the population. The greatest discordance between %BF and BMI was observed among %BF-defined overweight/obese women (32%). Sensitivity and specificity of BMI-defined overweight compared to %BF-defined overweight/obese were (58%, 94%) among females and (82%, 59%) among males respectively. According to the estimated negative predictive value, if an individual is categorized as BMI-defined non-obese, he/she has a 52% chance of being in the %BF-defined overweight/obese category.

CONCLUSION

Middle-aged individuals classified as normal by BMI may be overweight/obese based on measures of %BF. These individuals may be at risk for chronic diseases, but would not be identified as such based on their BMI classification. Quantifying %BF in this group could inform targeted strategies for disease prevention.

The importance of prediction model validation and assessment in obesity and nutrition research

Deriving statistical models to predict one variable from one or more other variables, or predictive modeling, is an important activity in obesity and nutrition research. To determine the quality of the model, it is necessary to quantify and report the predictive validity of the derived models. Conducting validation of the predictive measures provides essential information to the research community about the model. Unfortunately, many articles fail to account for the nearly inevitable reduction in predictive ability that occurs when a model derived on one data set is applied to a new data set. Under some circumstances, the predictive validity can be reduced to nearly zero. In this overview, we explain why reductions in predictive validity occur, define the metrics commonly used to estimate the predictive validity of a model (for example, coefficient of determination (R(2)), mean squared error, sensitivity, specificity, receiver operating characteristic and concordance index) and describe methods to estimate the predictive validity (for example, cross-validation, bootstrap, and adjusted and shrunken R(2)). We emphasize that methods for estimating the expected reduction in predictive ability of a model in new samples are available and this expected reduction should always be reported when new predictive models are introduced.

A new strategy to estimate levothyroxine requirement after total thyroidectomy for benign thyroid disease

BACKGROUND

The current approach for calculating the starting dose of levothyroxine (LT4) after total thyroidectomy is based on the patient's body weight (BW). The aim of the study was to identify the major predictive factors of LT4 requirement and to elaborate a new method to improve the accuracy of the LT4 starting dose after total thyroidectomy.

METHODS

The study consists of two parts. The first part consisted of the retrospective identification of 92 adult patients (retrospective cohort) who had undergone a total thyroidectomy for benign disease and who had begun LT4 treatment at a dose of 1.6 μg/kg/day. Adjustments to optimize the LT4 dose were then performed at the post-surgery follow-up on the basis of serum thyrotropin (TSH) levels. The results of this retrospective analysis were used to formulate a nomogram for a proper calculation of the LT4 starting dose that was then used prospectively in the second part of the study on 31 consecutive patients (prospective cohort).

RESULTS

At the first follow-up, 37 (40%) patients from the retrospective cohort were euthyroid. Univariate analysis indicated significant correlations between the optimal dose of LT4 and BW, body mass index (BMI), age, preoperative mean corpuscular volume, and free triiodothyronine (fT3). The optimal dose of LT4, analyzed for BMI and age, showed an inverse relationship with these two parameters, and ranged from 1.4 to 1.8 μg/kg/day. In the prospective cohort, the use of an age- and BMI-related nomogram improved the prediction of the optimal LT4 starting dose, with 68% of patients being euthyroid at the first follow-up compared to 41% of patients reported to have reached euthyroid state using the best strategy proposed in the literature.

CONCLUSIONS

This study confirms that BW is not the only variable for predicting LT4 requirement, as it decreases with the increase in age and BMI, probably due to the relative decrease of lean body mass. A new correlation between optimal dose and presurgical levels of fT3 and mean corpuscular volume was observed. We propose an easy and more efficient method of calculating LT4 starting dose after total thyroidectomy for benign disease.

Percent body fat prediction equations for 8- to 17-year-old American children

BACKGROUND

Percent body fat equations are usually developed in specific populations and have low generalizability.

OBJECTIVES

To use a nationally representative sample of the American youth population (8-17 years old) from the 1999-2004 National Health and Nutrition Examination Survey data to develop gender-specific percent body fat equations.

METHODS

Percent body fat equations were developed for girls and boys using information on weight, height, waist circumference, triceps skin-folds, age, race/ethnicity and menses status compared to dual-emission X-ray absorptiometry. Terms were selected using forward and backward selection in regression models in a 2/3 development sample and were cross-validated in the remaining sample. Final coefficients were estimated in the full sample.

RESULTS

Final equations included ten terms in girls and eight terms in boys including interactions with age and race/ethnicity. In the cross-validation sample, the adjusted R2 was 0.818 and the root mean squared error was 2.758 in girls. Comparable estimates in boys were 0.893 and 2.525. Systematic bias was not detected in the estimates by race/ethnicity or by body mass index categories.

CONCLUSION

Gender-specific percent body fat equations were developed in youth with a strong potential for generalizability and utilization by other investigators studying adiposity-related issues in youth.

Body adiposity index assess body fat with high accuracy in nondialyzed chronic kidney disease patients

OBJECTIVE

High body fat (BF) is an alarming condition that also affects nondialyzed chronic kidney disease (CKD) patients. Distinct methods are used to evaluate BF; however, in CKD population it remains unclear which one is more reliable showing high accuracy. Dual-energy X-ray absorptiometry (DXA), used as reference method to estimate adiposity, is expensive and time consuming to be applied in clinical settings. Recently, a new body adiposity index (BAI), that estimates BF from easily accessible measures, was validated in the general population. The aim of this study was to evaluate which simple and practical method, routinely used to estimate BF, shows the highest accuracy compared with DXA, in nondialyzed CKD patients.

DESIGN AND METHODS

In this cross-sectional study BF was estimated by DXA, bioelectrical impedance analysis (BIA), anthropometry (ANTHRO), and BAI. Serum leptin levels were determined.

RESULTS

Studied patients (n = 134) were 55% males, 54% overweight/obese, and 64.9 ± 12.5 years old, with estimated glomerular filtration rate (eGFR) = 29.0 ± 12.7 ml/min. The correlation coefficient was higher between DXA vs. ANTHRO (r = 0.76) and BAI (r = 0.61) than with BIA (r = 0.57), after adjusting for gender, age, and eGFR (P < 0.0001). Therefore, the Lin's concordance correlation coefficient and Bland-Altman plots were performed to measure the accuracy (C_b) between DXA with both ANTHRO and BAI. A higher accuracy (C_b = 0.82) and lower mean difference (-3.4%) was observed for BAI than for ANTHRO (C_b = 0.61; -8.4%). Leptin levels correlated (P < 0.0001) with DXA (r = 0.56) and BAI (r = 0.59).

CONCLUSIONS

These findings suggest that BAI estimates BF with high accuracy in nondialyzed CKD patients and may be helpful in the treatment of this population with increased BF.

[Prediction of optimal gluteal intramuscular needle length by skinfold thickness measurements in Korean adults]

PURPOSE

This study was conducted to assess optimal needle length for gluteal intramuscular injections (IM) via simple skinfold thickness (SFT).

METHODS

For this study, 190 healthy adults were recruited and grouped into eight groups according to gender and body mass index (BMI) (kg/m²). The Korean Society for the Study of Obesity criteria defines a BMI under 20 as underweight, 20.1-22.9 as normal, 23-24.9 as overweight and over 25 as obese. For each participant, the SFT of dorsoguteal (DG) and ventrogluteal (VG) sites were measured using a caliper. Subcutaneous tissue thickness was acquired through ultrasonic images.

RESULTS

For men in the overweight and obese groups at the DG site, for the obese group at the VG site, and for women in the normal weight, overweight and obese groups at both sites, the mean subcutaneous tissue thickness exceeded 1.84 cm, the minimal length for a 1 inch needle used for IM. At the DG site, optimal intramuscular needle length (OINL) was 1.4 times in women and 1.0 times in men compared to SFT. At the VG site, OINL was 1.3 times in women and 0.9 times in men compared to SFT.

CONCLUSION

The results of this study suggest that SFT is a reliable index to determine optimal needle length with minimal effort prior to IM.

Body composition in severe refractory asthma: comparison with COPD patients and healthy smokers

Background

Body composition is an important parameter for patients with chronic obstructive pulmonary disease (COPD) whereas the association between asthma and obesity is not fully understood. The impact of severe refractory asthma (SRA) on fat free mass (FFM) has not been investigated.

Methodology and Principal Findings

213 subjects (70 healthy smokers, 71 COPD patients and 72 asthma patients) without significant comorbidities were included in the study. In all patients, body composition assessment (using bioelectrical impendance analysis, skinfold and anthropometric measurements) and spirometry were performed. Differences in fat free mass index (FFMI) between groups were assessed and determinants of FFMI in asthma were evaluated. Patients with SRA had lower values of FFMI compared to patients with mild-to-moderate asthma [18.0(17.3–18.3)–19.5(18.4–21.5), p<0.001], despite the fact that they were more obese. The levels of FFMI in SRA were lower than those of GOLD stage I–III COPD and comparable to those of stage IV COPD patients [18.0(17.3–18.3)–18.8(17.8–20.1), p = ns]. These differences were present even after proper adjustments for sex, age, smoking status, daily dose of inhaled corticosteroids (ICS) and daily use of oral corticosteroids (OCS). In multivariate analysis, independent predictors of FFMI in asthmatic patients were age, use of OCS and the presence of SRA, but not smoking, sex or cumulative dose of ICS used.

Conclusions and Significance

SRA is related to the presence of low FFMI that is comparable to that of GOLD stage IV COPD. The impact of this observation on asthma mechanisms and outcomes should be further investigated in large prospective studies.

Comparing body composition assessment tests in long-term hemodialysis patients

BACKGROUND

Protein-energy wasting is common in chronic kidney disease and is associated with decreases in body muscle and fat stores and poor outcomes. The accuracy and reliability of field methods to measure body composition is unknown in this population.

STUDY DESIGN

Cross-sectional observational study.

SETTING & PARTICIPANTS

118 maintenance hemodialysis patients were seen at the General Clinical Research Center at Harbor-UCLA Medical Center, Torrance, CA.

INDEX TESTS

Triceps skinfold, near-infrared interactance, and bioelectrical impedance analysis using the Segal, Kushner, and Lukaski equations.

REFERENCE TEST

Dual-energy x-ray absorptiometry (DEXA).

RESULTS

Participants (42% women, 52% with diabetes, 40% African Americans, and 38% Hispanics) were aged 49.4 +/- 11.5 (mean +/- SD) years, and had undergone dialysis therapy for 41.1 +/- 32.9 months. Body mass index was 27.0 +/- 6.0 kg/m(2). Using DEXA as the reference test, the bioelectrical impedance analysis-Kushner equation, triceps skinfold, and near-infrared interactance were most accurate of the index tests in estimating total-body fat percentage, whereas bioelectrical impedance analysis-Segal equation and bioelectrical impedance analysis-Lukaski equation overestimated total body fat percentage. Bland-Altman analyses and difference plots showed that bioelectrical impedance analysis-Kushner and near-infrared interactance were most similar to the reference test. Bioelectrical impedance analysis-Kushner, triceps skinfold, and near-infrared interactance had the smallest mean differences from DEXA, especially in women (1.6%, 0.7%, and 1.2%, respectively). Similar results were observed in African American participants (n = 47).

LIMITATIONS

Measurements were performed 1 day after a hemodialysis treatment, leading to more fluid retention, which may have affected the reference and index tests differently.

CONCLUSIONS

Using DEXA as the reference test, both near-infrared interactance and bioelectrical impedance analysis-Kushner method yield more consistent estimates of total body fat percentage in maintenance hemodialysis patients compared with the other index tests. Near-infrared interactance is not affected by skin color. Field methods with portable devices may provide adequate precision.

Body frame dimensions are related to obesity and fatness: Lean trunk size, skinfolds, and body mass index

We explore relationships between BMI and skinfolds and anthropometric variables reflecting variation in lean body frame. Data on the middle class adult Australian women (n = 1260) collected in 2002 during a National Body Size and Shape Survey were used. Standard measurements of stature, weight, skeletal dimensions (shoulder width, hip width, chest width, and depth, limb lengths), circumferences of head, trunk, limbs and triceps, subscapular and abdominal skinfolds were taken. Techniques for measurements of skeletal frame minimized the inclusion of adipose tissue thickness. Analysis of variance and parametric and nonparametric correlations were used. Vertical dimensions show weak correlations with fatness, while body frame circumferences and transverse dimensions are consistently, significantly, and substantially correlated with fatness, each explaining from 3 to 44% of variation in skinfold thickness. Skeletal dimensions explain up to 50% of variation in skinfold thickness (multiple regression). Especially high correlations with skinfold thickness occur for chest width, depth, and hip width (r range from 0.42 to 0.66). Body frame dimensions reflect largely trunk volume and the trunk/limb proportions. Larger lean trunk size is associated with greater fatness. Since the size of the abdominal cavity, and thus the gastrointestinal system (GI), is reflected in the trunk size, we speculate that larger frame may predispose to obesity in two ways: (1) larger stomachs require greater bulk of food to produce feeling of satiety as mediated through antral distension, (2) larger GIs may absorb more nutrients. Frame size may help to detect the risk of obesity among young adults.

Central-to-peripheral fat ratio, but not peripheral body fat, is related to insulin resistance and androgen markers in polycystic ovary syndrome

BACKGROUND

Overweight, hyperandrogenism and insulin resistance are cardinal features of patients with polycystic ovary syndrome (PCOS). Women with PCOS have excess accumulation of trunkal fat and metabolic complications. Recent findings suggest that peripheral fat may have metabolic protective behaviour. The aim of this study was to investigate body fat distribution in patients with PCOS and associations of peripheral fat with metabolic and hormonal profile.

METHODS

The study included 24 patients with PCOS and a control group of 13 women. Anthropometrical evaluation and dual-energy X-ray absorptiometry to determine body composition was performed. Plasma metabolic and hormonal profiles were evaluated.

RESULTS

Patients with PCOS have increased proportion of central to peripheral fat ratio (CPFR) when compared to controls (p = 0.008). There was a positive correlation among trunkal fat, insulin, HOMA-IR and triglycerides (all p < 0.05). Regarding to peripheral fat there was no difference between groups, a trend to negative correlation to insulin appeared. Positive correlation between free androgens index and CPFR (p = 0.058) and a negative correlation between SHBG and CPFR (p = 0.016) were appeared.

CONCLUSIONS

Patients with PCOS showed an android pattern fat distribution when compared to controls. Peripheral fat contribution and its relations to androgens in this context could not be established. Android pattern of fat distribution showed inverse correlation to SHBG levels, suggesting that SHBG may be related to fat distribution.

Using simple anthropometric measures to predict body fat in South Asians

Previously determined predictive equations for body fat mass (BFM) are primarily derived from populations of European origin, which may not be appropriate for all ethnic groups. The objective of this study was to develop an improved predictive equation for BFM specific to South Asians and derived from common anthropometric measurements that include measures of central adiposity. A total of 208 apparently healthy South Asian men and women, aged 30–65 years, were recruited. Anthropometric measurements and BFM by dual energy X-ray absorbitometry (DEXA) were obtained. Sex-specific equations predicting BFM were developed using regression models on a reference subset (68 men, 70 women) and tested on a validation group. New predictive equations (BFMNEW) were tested for agreement with Durin and Wormersley and Siri equations and with the reference method, DEXA. The best predictive sex-specific equation involved a combination of skinfolds, waist circumference, hip circumference, humerus breadth, height, mass, and age. Models significantly correlated with BFM determined by DEXA (r = 0.946 for men; r = 0.974 for women; p < 0.001). The estimates of BFM from reference and validation groups had excellent correlations and displayed excellent agreement to DEXA measures. We demonstrated new predictive equations for BFM that are specific to South Asians and incorporate measures of central adiposity. This may help resolve issues surrounding inaccurate determination of adiposity in South Asians, and consequently provide better estimations of disease risk.

Considering the inclusion of metabolic and cardiovascular markers in the Panel Study of Income Dynamics

The inclusion of biomarkers in social surveys such as the Panel Study of Income Dynamics (PSID) has the potential to answer many elusive questions in social science and public health, including the much-studied relationship between socioeconomic status and health. This article reviews the potential inclusion of biomarkers of cardiovascular and metabolic risk in the PSID. We first discuss the considerable analytical benefits of adding these biomarkers to the PSID, including the exploration of life course hypotheses and the potential to test causal relationships between the social environment and biological systems. Next, we review evidence on the reliability of self-reports of cardiovascular and metabolic risk factors, concluding that the potential bias from relying on self-reports may be substantial. Based on evidence of biological importance as well as practical considerations of ease of in-home collection, our first tier of recommended biomarkers includes measured height, weight, waist and hip circumference, diastolic and systolic blood pressure, resting heart rate, total and high-density lipoprotein (HDL) cholesterol, glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and cystatin C. Additional markers of secondary priority are also discussed.

An obesity-associated FTO gene variant and increased energy intake in children

BACKGROUND

Variation in the fat mass and obesity-associated (FTO) gene has provided the most robust associations with common obesity to date. However, the role of FTO variants in modulating specific components of energy balance is unknown.

METHODS

We studied 2726 Scottish children, 4 to 10 years of age, who underwent genotyping for FTO variant rs9939609 and were measured for height and weight. A subsample of 97 children was examined for possible association of the FTO variant with adiposity, energy expenditure, and food intake.

RESULTS

In the total study group and the subsample, the A allele of rs9939609 was associated with increased weight (P=0.003 and P=0.049, respectively) and body-mass index (P=0.003 and P=0.03, respectively). In the intensively phenotyped subsample, the A allele was also associated with increased fat mass (P=0.01) but not with lean mass. Although total and resting energy expenditures were increased in children with the A allele (P=0.009 and P=0.03, respectively), resting energy expenditure was identical to that predicted for the age and weight of the child, indicating that there is no defect in metabolic adaptation to obesity in persons bearing the risk-associated allele. The A allele was associated with increased energy intake (P=0.006) independently of body weight. In contrast, the weight of food ingested by children who had the allele was similar to that in children who did not have the allele (P=0.82).

CONCLUSIONS

The FTO variant that confers a predisposition to obesity does not appear to be involved in the regulation of energy expenditure but may have a role in the control of food intake and food choice, suggesting a link to a hyperphagic phenotype or a preference for energy-dense foods.

Simultaneous inference in general parametric models

Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here.

Suprailiac or Abdominal Skinfold Thickness Measured with a Skinfold Caliper as a Predictor of Body Density in Japanese Adults

Measurement of subcutaneous fat thickness with a skinfold caliper is a simple and inexpensive technique for assessment of body composition, but is influenced by the skin site or the obesity level. The resulting measurement errors may influence the prediction accuracy of body density. We therefore aimed to clarify the characteristics of measurement errors with a skinfold caliper and to determine useful measurement sites for the prediction of body density in Japanese adults of wide-ranging age and obesity levels. The present study included 126 Japanese male and 77 female subjects ranging from 21 to 81 years old. They were divided into a "non-obese group" and an "obese group", based on the Japanese criteria of obesity (BMI > or = 25 kg/m(2)). Subcutaneous fat thickness was measured at 14 sites with a skinfold caliper and ultrasound. Percent body fat was measured by dual-energy x-ray absorptiometry, and body density was calculated using Brozek's formula. Sex and obesity level differences in the measurement error of skinfolds (ultrasound minus skinfold caliper measurements) were examined by 2 x 2 ANOVA (sex and obesity groups) for each site. The relationship between body density and the systematic error was examined. We developed an accurate prediction equation for body density with smaller measurement and systematic errors. Although measurement errors in skinfold thickness tended to increase with increasing obesity levels, the influence was smaller for the abdominal and suprailiac skinfolds compared with other sites. Measurement of suprailiac or abdominal skinfold thickness is useful to accurately estimate body density in Japanese adults.

Two-dimensional predictive equation to classify visceral obesity in clinical practice

OBJECTIVE

Visceral obesity assessment is not easy, and although computed tomography (CT) is an accurate tool, this technique is expensive and sometimes not suitable in clinical practice. We developed a new two-dimensional elliptical anthropometric equation to classify visceral obesity and evaluated the validity and the reliability of the new equation compared with CT.

RESEARCH METHODS AND PROCEDURES

We collected anthropometric and CT data from overweight/obese subjects (n = 61, BMI = 32.4 +/- 3.7 kg/m2). A validation group of 32 subjects was also selected. An equation for the assessment of visceral obesity was developed using multiple regression analysis. Once validated, the equation was compared with previous models. Tests for accuracy included mean differences, analysis of diagnostic, R2, Snedecor's F-test, and Bland-Altman plot.

RESULTS

Multiple regression analysis revealed that the sagittal and coronal diameters and the triceps skinfold were significant contributors to the model. The final equation was: visceral area (VA)/subcutaneous area (SA)predicted = 0.868 + 0.064 x sagittal diameter - 0.036 x coronal diameter - 0.022 x triceps skinfold. Patients with visceral-subcutaneous area ratio (VA/SA) > 0.42 were classified as having visceral obesity. The predictive equation was valid, showing a significant association with VA/SA assessed by CT (VA/SA(CT); r = 0.68; p < 0.0001). Paired Student's t test showed no significant differences with VA/SACT (p = 0.541). The reliability was high [F(24/60) = 2.12; p = 0.01].

DISCUSSION

The new two-dimensional and elliptical predictive equation is valid to assess visceral obesity and is more precise than previous models.

Evaluation of Body Fat Changes during Weight Loss by Using Improved Anthropometric Predictive Equations

BACKGROUND/AIM

Skinfold-based equations are widely used to evaluate body fat (BF), but over-/underestimation is often reported. We evaluate the capacity of improved skinfold-based equations to estimate BF changes during weight reduction and compare them against well-established equations.

METHODS

Overweight adults (n = 44) participated in a 4-month weight reduction intervention. Dual-energy X-ray absorptiometry (DXA) and anthropometric measurements were taken at baseline and after intervention. The BF% was calculated using García, Peterson, and Durnin and Womersley (DW) equations.

RESULTS

Baseline and postintervention BF% measured by DXA correlated highest with BF% predicted according to García (r = 0.934 and r = 0.948, respectively), followed by Peterson (r = 0.941 and r = 0.932, respectively) and DW (r = 0.557 and r = 0.402, respectively); only a slight systematic error in overestimating the BF% was observed in estimates according to García (r = 0.147 and r = 0.104, respectively; p < 0.001), while increasing errors occurred using the Peterson (r = 0.624 and r = 0.712, respectively; p < 0.001) and DW (r = 0.767 and r = 0.769, respectively; p < 0.001) equations. Moderate correlations between BF changes (kg) measured by DXA and predicted by DW (r = 0.7211), Peterson (r = 0.697), and García (r = 0.645) were observed.

CONCLUSION

Improved skinfold equations cannot accurately measure changes in BF after weight reduction.