Validity of two-component models for estimating body fat of black men.

Commonly used two-component model conversion formulas that estimate relative body fat (%BF) from body density (Db) were cross-validated on a heterogeneous sample of black men (n = 30; age = 19--45 yr). A four-component model was used to obtain criterion measures of %BF, and linear regression and analysis of individual residual scores were conducted to assess the predictive accuracy of the formulas under investigation. The two-component formula commonly used to estimate %BF of black men (Schutte JE, Townsend EJ, Hugg J, Shoup RF, Malina RM, and Blomqvist CG. J Appl Physiol 56: 1647-1649, 1984) significantly (P < or = 0.01) and systematically (87% of sample) overestimated %BF (-1.28%); thus we developed the following two-component Db conversion formula: %BF = [(4.858/Db) - 4.394] x 100. Because our formula was derived from a four-component model and a larger, more heterogeneous sample than the commonly used two-component formula, we recommend using it to convert Db to %BF for black men. Additionally, there was good agreement between dual-energy X-ray absorptiometry and the four-component model, making this a suitable alternative for estimating the %BF of black men.

Validation of air displacement plethysmography for assessing body composition.

PURPOSE: The purpose of this study was to verify the validity of an air displacement plethysmography device (Bod Pod) for estimating body density (Db). METHODS: The Db from the Bod Pod (DbBP) was compared with the Db from hydrostatic weighing (DbHW) at residual lung volume in a heterogeneous sample of 30 black men who varied in age (32.0 +/- 7.7 yr), height (180.3 +/- 7.5 cm), body mass (84.2 +/- 15.0 kg), body fatness (16.1 +/- 7.5%), and self-reported physical activity level and socioeconomic status. The Db for each method was converted to relative body fat (%BF) using race-specific conversion formulas and subsequently compared with %BF obtained from dual-energy x-ray absorptiometry (%BFDXA). RESULTS: Linear regression, using DbHW as the dependent variable and DbBP as the predictor, produced an R2 = 0.84 and SEE = 0.00721 g x cc(-1). However, the mean difference between the two methods (0.00450 +/- 0.00718 g x cc(-1) was significant (P < 0.01). The Bod Pod underestimated the Db of 73% of the sample. The %BF estimates from the Bod Pod, HW, and DXA differed significantly (P < 0.01). The average %BFBP (17.7 +/- 7.4%) was significantly greater than %BFHW (15.8 +/- 7.5%) and %BFDXA (16.1 +/- 7.5%); however, there was no significant difference between %BFHW and %BFDXA. CONCLUSION: The Bod Pod significantly and systematically underestimated Db, resulting in an overestimation of %BF. More cross-validation research is needed before recommending the Bod Pod as a reference method.

Comparison of air-displacement plethysmography, hydrodensitometry, and dual X-ray absorptiometry for assessing body composition of children 10 to 18 years of age.

Body density (Db) of 54 boys and girls 10-18 years of age (13.9 +/- 2.4 years) was measured in an air-displacement plethysmograph, the BOD POD, and compared to Db determined by hydrodensitometry (HW). Both Db values were converted to percent body fat (%BF) using a two-component model conversion formula and compared to %BF determined by dual energy X-ray absorptiometry (DXA). Body density estimated from the BOD POD (1.04657 +/- 0.01825 g/cc) was significantly higher than that estimated from HW (1.04032 +/- 0.01872 g/cc). The relative body fat calculated from the BOD POD (23.12 +/- 8.39 %BF) was highly correlated but, on average, 2.9% BF lower than %BF DXA. Average %BF estimates from HW and DXA were not significantly different. Despite consistently underestimating the %BF of children, the strong relationship between DXA and the BOD POD suggests that further investigation may improve the accuracy of the BOD POD for assessing body composition in children.

Measures of body composition in blacks and whites: a comparative review.

Biological differences exist in the body composition of blacks and whites. We reviewed literature on the differences and similarities between the 2 races relative to fat-free body mass (water, mineral, and protein), fat patterning, and body dimensions and proportions. In general, blacks have a greater bone mineral density and body protein content than do whites, resulting in a greater fat-free body density. Additionally, there are racial differences in the distribution of subcutaneous fat and the length of the limbs relative to the trunk. The possibility that these differences are a result of ethnicity rather than of race is also examined. Because most equations that predict relative body fat were derived from predominantly white samples, biological variation between the races in these body-composition indexes has practical significance. Systematic error can result in the inaccurate estimation of the relative body fat of blacks, and therefore of definitions of obesity, if these inherent differences are ignored.

Validation of near-infrared interactance and skinfold methods for estimating body composition of American Indian women.

PURPOSE: This study tested the predictive accuracy of the Jackson et al. skinfold (SKF) equations (sigma7SKF and sigma3SKF), a multi-site near-infrared interactance (NIR) prediction equation, and the Futrex-5000 NMR equation in estimating body composition of American Indian women (N = 151, aged 18-60 yr). METHODS: Criterion body density (Db) was obtained from hydrodensitometry at residual lung volume. RESULTS: Sigma7SKF significantly underestimated Db (P < 0.05). Sigma3SKF and Heyward's NIR equations significantly overestimated Db (P < 0.05). The Futrex-5000 NIR equation significantly underestimated percent of body fat (%BF) (P < 0.05). Prediction errors for SKF and multi-site NIR exceeded 0.0080 g x cc(-1). The SEE for Futrex-5000 was 5.5%BF. Thus, ethnic-specific SKF and NIR equations were developed. For the SKF model, the sigma3SKF (triceps, axilla, and suprailium) and age explained 67.3% of the variance in Db:Db = 1.06198316 -0.00038496(sigma3SKF) -0.00020362(age). Cross-validation analysis yielded r = 0.88, SEE = 0.0068 g x cc(-1), E = 0.0070 g x cc(-1), and no significant difference between predicted and criterion Db. For the NIR model, the hip circumference, sigma2AdeltaOD2 (biceps and chest), FIT index, age, and height explained 73.9% of the variance in Db:Db = 1.0707606 -0.0009865(hip circumference) -0.0369861(sigma2deltaOD2) + 0.0004167(height) + 0.0000866(FIT index) -0.0001894(age). Cross-validation yielded r = 0.85, SEE = 0.0076 g x cc(-1), E = 0.0079 g x cc(-1), and a small, but significant, difference between predicted and criterion Db. CONCLUSIONS: We recommend using the ethnic-specific SKF and NIR equations developed in this study to estimate Db of American Indian women.

Techniques of body composition assessment: a review of laboratory and field methods.

Body composition is one of the major health-related components of fitness. Thus, it is important for health and fitness professionals to have a general understanding of the most commonly used techniques for assessing body composition. This review presents the developmental background and underlying principles and theory of four laboratory (hydrodensitometry, air displacement plethysmography, isotope dilution, and dual-energy x-ray absorptiometry) and four field (bioelectrical impedance analysis, near-infrared interactance, skinfolds, and anthropometry) methods of body composition assessment. In addition to a description of the methods, the validity, and reliability, strengths, and limitations of each measurement tool are examined. Highlights of the laboratory methods include the relatively new Bod Pod air displacement device, which is a promising assessment tool more convenient than hydrodensitometry but still lacking substantial validity testing and the ability of dual-energy x-ray absorptiometry to measure regional composition making it an attractive method for clinicians. Advancements in segmental and multifrequency bioelectrical impedance for compartmental analysis have enhanced the value of this field method, but research continues to show that commercially available near-infrared interactance units are invalid. With this knowledge, the clinician and researcher should be able to make an informed decision regarding the most appropriate measurement device for their body composition assessments.

Cross-validation of modified fatness-specific bioelectrical impedance equations.

The Segal fatness-specific bioelectrical impedance (BIA) equations are useful for predicting fat-free mass (FFM). Stolarczyk et al. Proposed a modified method of averaging the two equations for individuals who are neither lean nor obese, thus eliminating the need to know % BF a priori. To cross-validate this modification, we compared FFM determined using the averaging method versus hydrostatic weighing for 76 adults. Per the averaging method, accuracy for males was excellent (r =.91, SEE = 2.7 kg, E = 2.7 kg), with 78% of individuals within +/- .5% BF predicted by hydrostatic weighing. Accuracy for females was lower (r =.88, SEE = 3.0 kg, E = 3.1 kg), with % BF of 51% within +/- 3.5% of the reference method. The relative ease and practicality of the averaging method and the results of this study indicate this method may be useful with a diverse group.

Assessing body composition of adults with diabetes.

Overweight and obesity are associated with the development of type 2 diabetes. Thus, it is important for clinicians to accurately measure and monitor the body composition of at-risk individuals and patients with diabetes. This article reviews valid and reliable field methods and prediction equations for assessing the body composition of obese individuals, as well as persons with type 2 diabetes. We also reviewed research that assessed the validity of practical methods in estimating the body composition of individuals with either type 1 or type 2 diabetes.

Predictive accuracy of skinfold equations for estimating body density of African-American women.

PURPOSE: The purpose of this study was to compare the predictive accuracy of previously published skinfold (SKF) equations for estimating body density of 134 premenopausal African-American women (18 to 40 yr). METHODS: The equations cross-validated were: the sum of seven skinfolds equation (JPW7) and the sum of three skinfolds equation (JPW3), both of Jackson et al. (1980); the generalized equation (DWgen) and the age-specific equation (DWage) of Durnin and Womersley (1974); and the equation of Wang et al. (1994). Total body density was determined by hydrodensitometry (BDuww) at residual lung volume and converted to %BFuww using the Siri (1991) formula. The predictive accuracy of the SKF equations tested in this study was evaluated using the cross-validation procedures outlined by Lohman (1992). RESULTS: The validity coefficients (ry,y') ranged from 0.83 (DWgen) to 0.87 (JPW7). The SEEs ranged from 0.0076 g.cc-1 (DWage) to 0.0122 g.cc-1 (Wang), and the total errors ranged from 0.0103 g.cc-1 (JPW7) to 0.0478 g.cc-1 (Wang). The percentage of individual residual scores falling within +/- 3.5% BF for this sample ranged from 31% (DWage) to 58% for the JPW7 equation. Comparison of the predictive accuracy of the five equations indicated that the JPW7 equation was the most valid equation, explaining 75% of the variance in reference body density with no significant difference between average reference BDuww (1.03035 g.cc-1) and average predicted BDJPW7 (1.03152 g.cc-1). CONCLUSIONS: We recommend using the JPW7 equation to assess body composition and %BF of premenopausal African-American women.

Practical body composition assessment for children, adults, and older adults.

This paper provides an overview of practical methods for assessing body composition of children, adults, and older adults. Three methods commonly used in field and clinical settings are skinfolds, bioelectrical impedance analysis, and anthropometry. For each method, standardized testing procedures, sources of measurement error, recommendations for technicians, and selected prediction equations for each age category are presented. The skinfold method is appropriate for estimating body fat of children (6-17 years) and body density of adults (18-60 years) from diverse ethnic groups. Likewise, bioimpedance is well suited for estimating the fat-free mass of children (10-19 years) as well as American Indian, black, Hispanic, and white adults. Anthropometric prediction equations that use a combination of circumferences and bony diameters are recommended for older adults (up to 79 years of age), as well as obese men and women.

Energy expenditure and physiological responses during indoor rock climbing.

OBJECTIVES: To report the physiological responses of indoor rock climbing. METHODS: Fourteen experienced climbers (nine men, five women) performed three climbing trials on an indoor climbing wall. Subjects performed three trials of increasing difficulty: (a) an easy 90 degrees vertical wall, (b) a moderately difficult negatively angled wall (106 degrees), and (c) a difficult horizontal overhang (151 degrees). At least 15 minutes separated each trial. Expired air was collected in a Douglas bag after four minutes of climbing and heart rate (HR) was recorded continuously using a telemetry unit. Arterialised blood samples were obtained from a hyperaemised ear lobe at rest and one or two minutes after each trial for measurement of blood lactate. RESULTS: Significant differences were found between trials for HR, lactate, oxygen consumption (VO2), and energy expenditure, but not for respiratory exchange ratio. Analysis of the HR and VO2 responses indicated that rock climbing does not elicit the traditional linear HR-VO2 relationship characteristic of treadmill and cycle ergometry exercise. During the three trials, HR increased to 74-85% of predicted maximal values and energy expenditure was similar to that reported for running at a moderate pace (8-11 minutes per mile). CONCLUSIONS: These data indicate that indoor rock climbing is a good activity to increase cardiorespiratory fitness and muscular endurance. In addition, the traditional HR-VO2 relationship should not be used in the analysis of this sport, or for prescribing exercise intensity for climbing.

Exercise mode and gender comparisons of energy expenditure at self-selected intensities.

The purpose of this study was to compare oxygen consumption (VO2) and energy expenditure after 20 min of self-selected submaximal exercise for four modes of exercise. Eighteen subjects (9 male and 9 female) first completed a test of VO2max during treadmill running. On separate days, subjects then completed 20 min submaximal treadmill running (TR), simulated cross-country skiing (XC), cycle ergometry (CE), and aerobic riding (AR) exercise. Total VO2 and energy expenditure were significantly higher for TR than all other modes for both males and females (43.6 +/- 10.4, 39.1 +/- 9.7, 36.1 +/- 7.6, 28.4 +/- 6.1 LO2, for TR, XC, CE, and AR, respectively, P < 0.0001). For males and females, heart rate was similar during TR and XC and lower during CE and AR (154.8 +/- 14.2, 152 +/- 13.1, 143.4 +/- 14.9, and 126.2 +/- 12.0 beats.min-1 for TR, XC, CE, and AR, respectively, P < 0.0001). Compared with females, males had significantly greater VO2 (P < 0.005) and energy expenditure (P < 0.004), while females had higher heart rates (P < 0.003). Ratings of perceived exertion (RPE) were not different between TR, XC, and CE, but were significantly lower during AR (13.4 +/- 1.3, 13.6 +/- 0.8, 13.2 +/- 0.9, and 12.6 +/- 1.0 for TR, XC, CE, and AR, respectively, P < 0.003). TR elicited the greatest VO2 and energy expenditure during self-selected exercise despite and RPE similar to XC and CE. Therefore, treadmill exercise may be the modality of choice for individuals seeking to improve cardiorespiratory endurance and expend a larger number of kjoules.

Predictive accuracy of BIA equations for estimating fat-free mass of black men.

This study assessed the predictive accuracy of previously published bioelectrical impedence analysis (BIA) equations in estimating the fat-free mass (FFM) of black men, 19 to 50 years. The reference method was hydrostatic weighing (HW) at residual lung volume. Body density (Db) was converted to relative body fat (%BF) for calculation of FFMHW using the Schutte et al. equation. Resistance and reactance were measured with a Valhalla bioimpedance analyzer. Age-specific, generalized, and fatness-specific BIA equations were cross validated using regression analysis. The Segal fatness-specific equations were modified using a method recommended by Stolarczyk. All of the equations significantly (P < 0.05) underestimated the average reference measure of FFMHW. However, the underestimation of FFM for the modified Segal fatness-specific equation was relatively small (-1.8 kg) and not likely to have much clinical significance. Furthermore, this equation had a high correlation with reference FFMHW (ry,y' = 0.97), low prediction errors (SEE = 2.1 kg; E = 2.7 kg), and accurately estimated the FFM within +/- 3.5 kg for 78% of the individuals in the sample. Thus, we recommend using the modified fatness-specific BIA equation for estimating the FFM of black men.

The fatness-specific bioelectrical impedance analysis equations of Segal et al: are they generalizable and practical?

The fatness-specific bioelectrical impedance analysis (BIA) equations of Segal et al (Am J Clin Ntr 1988;47: 7-14; Segal equations) have been shown to be generalizable across sex, ethnicity, age, and degrees of adiposity. However, these fatness-specific equations require an a priori determination of percentage body fat (%BF) by using a skinfold equation or densitometry to categorize subjects into obese or nonobese groups. These procedures negate the use of BIA as a fast and simple method. It was hypothesized that the average of the Segal nonobese and obese fatness-specific equations (BIA average method) could be used in lieu of the skinfold method for categorizing subjects who are not obviously lean or obese. In phase 1 these three methods were compared for a subsample of 59 women who were not obviously lean or obese. The %BF of 75% of these subjects was accurately estimated within 3.5%BF by using the BIA average method whereas only 71% and 46% were accurately estimated by fusing the densitometric and skinfold methods, respectively. In phase 2, the predictive accuracy of the Segal fatness-specific equations, used in combination with the BIA average method, was compared with other BIA equations published previously for 602 American Indian, Hispanic, and white women and men. The Segal fatness-specific equations yielded the smallest prediction error (SEE = 2.22 kg for women and 3.59 kg for men) and the %BF of 70% of the subjects was accurately estimated within 3.5%BF compared with 24-59% for other BIA equations. Therefore, we recommend using the Segal fatness-specific and average equations to assess body composition in heterogeneous populations.

Predictive accuracy of bioimpedance in estimating fat-free mass of African-American women.

The purpose of this study was to identify the BIA (bioimpedance analysis) equation that yields the best estimate of body composition for 122 premenopausal African-American women (18-40 yr). Total body density (Db) was determined by hydrodensitometry at residual lung volume and converted to %BFHD using the Siri (31) formula, %BFHD was used to calculate reference fat-free mass (FFM). Resistance and reactance were measured using a Valhalla bioimpedance analyzer. The predictive accuracy of generalized, age-gender, race-specific, fatness-specific, and the Valhalla manufacturer's BIA equations was compared. There were significant correlations between FFMHD and FFMBIA for all BIA equations (r = 0.85 to 0.92). Except for the modified Segal fatness-specific equations, the prediction errors (SEE and E) exceeded 2.8 kg. For individuals, the %BF derived from FFMBIA predicted by the modified Segal equations was within +/- 3.5% BF for 69% of the subjects. This percentage was less (34-53%) for other equations. These results suggest that the predictive accuracy of BIA for estimating body composition of African-American women is improved when fatness-specific equations are used. We recommend using the modified Segal fatness-specific equations to assess FFM and %BF of premenopausal African-American women.

Blood pressure measurement during exercise: a review.

This review summarizes research dealing with the validity of commonly used methods for measuring systemic blood pressure during exercise. Arterial blood pressures measured from within peripheral arteries exaggerate systolic blood pressures because of wave form reflection but provide representative mean and diastolic pressures of the central arterial circulation. Manual and automated sphygmomanometry are the best noninvasive indirect methods of blood pressure measurement to estimate ascending aorta systolic pressures; however, both methods significantly underestimate diastolic pressures at rest and during exercise. The error in diastolic pressure measurement increases with increasing exercise intensity. The accuracy of many indirect noninvasive devices for blood pressure measurement at rest and during exercise can be questioned because of the use of unsuitable criterion methods. Ascending aorta pressures should ideally be used as a gold standard or criterion method for blood pressure measurement during exercise and instrument/method validation. However, given the constraints of varied criterion standards and current recommendations for blood pressure measurement, the following units were found to be acceptable devices for measuring systolic blood pressure during exercise: Accutracker II, A&D TM 2421, Colin 630 (auscultation), Critikon 1165, and possibly the Paramed 9350.

Evaluation of body composition. Current issues.

In the selection of body composition field methods and prediction equations, exercise and health practitioners must consider their clients' demographics. Factors, such as age, gender, level of adiposity, physical activity and ethnicity influence the choice of method and equation. Also, it is important to evaluate the relative worth of prediction equations in terms of the criterion method used to derive reference measures of body composition for equation development. Given that hydrodensitometry, hydrometry and dual-energy x-ray absorptiometry are subject to measurement error and violation of basic assumptions underlying their use, none of these should be considered as a 'gold standard' method for in vivo body composition assessment. Reference methods, based on whole-body, 2-component body composition models, are limited, particularly for individuals whose fat-free body (FFB) density and hydration differ from values assumed for 2-component models. Use of field method prediction equations developed from 2-component model (Siri equation) reference measures of body composition will systematically underestimate relative body fatness of American Indian women, Black men and women, and Hispanic women because the average FFB density of these ethnic groups exceeds the assumed value (1.1 g/ml). Thus, some researchers have developed prediction equations based on multicomponent model estimates of body composition that take into account interindividual variability in the water, mineral, and protein content of the FFB. One multicomponent model approach adjusts body density (measured via hydrodensitometry) for total body water (measured by hydrometry) and/or total body mineral estimated from bone mineral (measured via dual-energy x-ray absorptiometry). Skinfold (SKF), bioelectrical impedance analysis (BIA), and near-infrared interactance (NIR) are 3 body composition methods used in clinical settings. Unfortunately, the overwhelming majority of field method prediction equations have been developed and cross-validated for White populations and are based on 2-component model reference measures. Because ethnicity may affect the composition of the FFB and regional fat distribution, race-specific prediction equations may need to be developed for some ethnic groups. To date, race-specific SKF (American Indian women, Black men, and Asian adults), BIA (American Indian women and Asian adults), and NIR (American Indian women and White women) equations have been developed. However, these equations need to be cross-validated on additional samples from these ethnic groups. In summary, research strongly suggests that multicomponent models need to be used in order to quantify differences in FFB composition due to ethnicity so that accurate SKF, BIA, and NIR prediction equations can be developed. Assessment of body composition in vivo may be enhanced by using advanced technologies such as dual-energy x-ray absorptiometry and hydrometry to refine hydrodensitometry. Practitioners should carefully select and use only those prediction equations that have been developed and cross-validated for specific ethnic groups. Additional research is needed to test the accuracy and applicability of previously published prediction equations for the American Indian, Asian, Black, and Hispanic populations.

Predictive accuracy of bioimpedance equations in estimating fat-free mass of Hispanic women.

This study assessed the predictive accuracy of previously published bioelectrical impedance analysis equations for estimating fat-free mass of young (20-39 yr) Hispanic women (N = 29). The reference method was hydrostatic weighing at residual lung volume. Body density was converted to percent body fat using the Siri equation. Resistance and reactance were measured with a Valhalla bioimpedance analyzer. The bioelectrical impedance analysis equations of Lohman, Rising, Stolarczyk, Segal, Gray, and Van Loan were cross-validated. There were significant correlations between criterion and predicted fat-free mass (r = 0.86-0.95) for all equations. The standard error of estimate for each equation was acceptable; however, the total error for the Stolarczyk (3.2 kg) and the Van Loan (4.6 kg) equations exceeded the recommended value (2.8 kg). For all equations, the difference between average criterion and predicted fat-free mass was significant (P < 0.05). However, the mean differences for the Lohman (0.8 kg), Segal (0.8 kg), and Gray (0.9 kg) equations were small. In conclusion, the Segal, Lohman, and Gray equations may have potential for assessing the body composition of healthy, acculturated, Hispanic women.