Chapter 08 Assessing Body Composition Designing Cardiorespiratory Exercise Programs Chapter 08 Assessing Body Composition Bogle - HESS 544

Classification and Use of Body Composition Measures Body composition assessment is also good for the following: Estimating healthy body weight Formulating nutritional recommendations and exercise prescriptions Estimating competitive weight for athletes Monitoring growth Identifying those at risk because of under- or overfatness Assessing changes associated with aging, malnutrition, and certain diseases Assessing effectiveness of nutrition and exercise interventions in counteracting changes identified above

Table 8.1

Body Compsition Models Two-component (2C) model Categorizes total body mass into fat and fat-free body (FFB) Fat-free body is comprised of water, muscle (protein), and bone (mineral) Serves as foundation of hydrodensitometry (under-water weighing) Siri and Brozek are two popular formulas for converting body density (Db) into %BF

Two-Component Model 2C model assumptions: Density of fat is 0.901 g/cc. Density of the FFB is 1.100 g/cc. Densities of fat and the FFB components (water, protein, mineral) are the same for everyone. Densities of FFB components are constant for an individual, and their proportion remains constant. Person being measured differs from reference body only in the amount of fat. Reference FFB assumed to be 73.8% water, 19.4% protein, and 6.8% mineral. (continued)

Two-Component Model (cont.) 2C models work well if underlying assumptions about FFB are met. FFB density (FFBd) varies depending mainly on the relative proportion of water and mineral. FFBd varies with age, gender, ethnicity, level of body fatness, and physical activity level. Higher than assumed Db (1.10 g/cc) can produce negative %BF. %BF of those with lower than assumed Db will be overestimated using 2C model equations.

Two-Component Model (cont.) Two commonly used equations are: Siri (1961) equation, %BF = (4.95 / Db − 4.50) x 100 Brozek and colleagues (1963), %BF = (4.57 / Db − 4.142) x 100 These two equations yield similar %BF estimates for body densities ranging from 1.0300 to 1.0900 g·cc−1. Two-component model equations provide accurate estimates of %BF as long as the basic assumptions of the model are met. For certain population subgroups, therefore, scientists have applied multicomponent models.

Multicomponent Models These models account for bone mineral and or total body water contribution to FFB Improve estimation of %BF Avoid systematic errors in %BF estimation through use of population-specific reference bodies that take into account the age (e.g., for children, elderly persons), gender, and ethnicity of the individual Table 8.2 provides population-specific formulas for converting Db to %BF. You will note that population-specific conversion formulas do not yet exist for all age groups within each ethnic group.

Reference Methods Commonly used methods: densitometry and dual-energy X-ray absorptiometry (DEXA) For densitometric methods, Db is estimated from the ratio of body mass to body volume (Db = BM/BV) Two methods of densitometry: hydrodensitometry (hydrostatic weighing, HW) and air displacement plethysmography (ADP). A plethysmograph is an instrument for measuring changes in volume within an organ or whole body (usually resulting from fluctuations in the amount of blood or air it contains). Densitometry measures BV from which Db is calculated

Hydrostatic Weighing Relies on Archimedes’ principle and total body submersion to determine BV. Determine BV by totally submerging the body in an underwater weighing tank or pool and measuring the underwater weight (UWW) of the body. BV must be corrected for residual lung volume (RV) methods and gastrointestinal air (GV). GV assumed to be 100 ml or 0.1 L or 0.1 kg. BV must also be corrected for water density. BV = [(BM−net UWW)/density of water] − (RV + GV) Db is a function of the muscle, bone, water, and fat in the body. Db is converted to %BF using best conversion formula for the person being assessed. (see Table 8.2) Best results occur if you follow standardized techniques. See collection form (Figure 8.3), and Guidelinesf, p.195 (continued)

Hydrostatic Weighing (continued) HW is a valid, reliable, and widely used laboratory method. Precision with HW is excellent (predictive error ≤1% BF) when RV is measured. Precision with HW decreases substantially (predictive error ±2.8 to 3.7 %BF) when RV is estimated.

Air Displacement Plethysmography Another densitometric method Utilizes displacement of air within a closed chamber (Bod Pod) and pressure–volume relationships (Boyle’s Law) to estimate BV (see also Figure 8.4) Less time-consuming than HW and requires less technician skill One assumption is that the Bod Pod controls the isothermal effects of clothing, hair, thoracic gas volume, and body surface area in the enclosed chamber. Clients are tested while wearing minimal clothing (a swimsuit) and a swim cap. (continued)

Air Displacement Plethysmography (continued) Research is divided as to whether ADP produces significantly different Db when compared to HW. Compared to multicomponent body composition models, the Bod Pod and HW methods have similar predictive accuracy. The Bod Pod is more accommodating than HW. It may be more suitable in clinical settings or with hydrophobic clients. See testing protocol for Bod Pod, p.199.

Dual-Energy X-ray Absorptiometry DXA yields estimates of bone mineral, fat, and lean soft-tissue mass. DXA is safe, rapid, requires minimal client cooperation, and accounts for individual variability in bone mineral content. The basic principle is that the attenuation of X rays with high and low photon energies is measurable and dependent on the thickness, density, and chemical composition of the underlying tissue. Attenuation ratios for the two X-ray energies are thought to be constant for all individuals. (continued)

Dual-Energy X-ray Absorptiometry (continued) Body composition results vary with manufacturer, model, and software version. Experts reviewing DXA studies have called for more standardization among manufacturers. No consensus exists that DXA is better than HW. Current investigations indicate DXA estimates of %BF are within 1% to 3% of reference measures from multicomponent model. Further research is needed before DXA can be firmly established as the best reference method. Still, the DXA method is widely used in light of its availability, ease of use, and low radiation exposure.

Field Methods of Body Composition Assessment They are more practical for estimating body composition compared to laboratory methods. You must closely follow standardized testing procedures. You must practice in order to perfect your measurement techniques for each method. Common tests: Skinfold (SKF) Bioelectrical impedance analysis (BIA) Anthropometry

Skinfold Method SKFs indirectly measure the thickness of subcutaneous adipose tissue. Assumptions: SKF is a good measure of subcutaneous fat. SKF measurements at 12 sites, is similar to the value obtained from magnetic resonance imaging Distribution of fat subcutaneously and internally is similar for all individuals within each gender/race/ages. The sum of several SKFs (ΣSKF) can be used to estimate total body fat. There is considerable biological variation in subcutaneous, intramuscular, intermuscular, and internal organ fat deposits There is a relationship between ΣSKF and Db. You will get an inaccurate estimate if you use a population-specific equation to estimate the Db of a client who is not representative of the sample used to develop that equation Age is an independent predictor of Db for adults.

Skinfold Method (continued) Population-specific or generalized equations are needed to convert Db to %BF. Population-specific %BF prediction equations are based on a linear relationship between SKF fat and Db (linear model). However, there is a curvilinear relationship (quadratic model) between SKFs and Db across a large range of body fatness. (see Figure 8.7, next slide) Population-specific equations tend to underestimate %BF in fatter subjects and overestimate it in leaner subjects. (continued)

Figure 8.7

Skinfold Method (continued) Generalized are equations developed using heterogeneous sample, diverse in age, %BF. Using the quadratic model, Jackson and colleagues (Jackson and Pollock 1978; Jackson, Pollock, and Ward 1980) developed generalized equations applicable to individuals varying greatly in age (18 to 60 yr) and body fatness (up to 45% BF). SEE TABLE 8.3 Only one equation is needed to estimate Db. Most equations use 2 or 3 SKFs to predict Db. Db is converted to %BF using appropriate population-specific conversion formula. You can accurately estimate the %BF of your clients within ±3.5% BF. Nomograms exist to estimate %BF for some SKF prediction equations. See Figure 8.8, p. 205

Skinfold Method (continued) Technician skill is key. (See sources for error p. 206) Follow and practice standardized SKF technique. (See standard procedures p. 207) Be meticulous about SKF site identification. Be attentive to span of thumb and index finger, direction of fold, and placement of caliper jaws. Continuously work on interpersonal communication skills. (See tips on interpersonal skills p. 206) Errors occur due to technician, caliper, and client factors.

Figure 8.9

Bioelectrical Impedance Method BIA is rapid, noninvasive, and relatively inexpensive. A low-level electrical current is applied and tissue opposition (Impedance) to the current is used to estimate body composition. You can estimate the individual’s total body water (TBW) from the impedance measurement because the electrolytes in the body’s water are excellent conductors of electrical current. Thus, the extent of hydration or dehydration determines resistance of tissues to flow of electrical current. When water reduces resistance and current moves easily it means tissue leaner. When dehydration or adipose tissue slows current it means tissue is fatter. (continued)

Bioelectrical Impedance Method (continued) Assumptions of BIA: The human body is shaped like a perfect cylinder with a uniform length and cross-sectional area. Because the body segments are not uniform in length or cross-sectional area, resistance to the flow of current through these body segments will differ. Assuming the above, at a fixed signal frequency, the impedance (Z) is directly related to the length (L) of the conductor (height) and inversely related to its cross-sectional area. (continued)

Bioelectrical Impedance Method (continued) Assumptions of BIA: Biological tissues act as conductors or insulators; the flow of current through the body follows the path of least resistance. Because the FFM contains large amounts of water (~73%) and electrolytes, it is a better conductor of electrical current than fat. Impedance is a function of resistance and reactance = √(R2 + Xc2). , where reactance is the measure of opposition of flow at the cell membrane. For these reasons, the resistance index (ht2/R), instead of ht2/Z, is often used in BIA models to predict FFM or TBW (continued)

Bioelectrical Impedance Method (continued) Several methods: Traditional, ipsilateral, tetrapolar whole body analysis via either single- or multiple-frequency analyzers (Figure 8.11) Upper-body impedance analysis via hand-to-hand analyzers (Figure 8.12) Lower-body impedance analysis via foot-to-foot analyzers (Figure 8.12) Vertical, bilateral, whole-body analysis via multiple-frequency analyzers (continued)

Bioelectrical Impedance Method (continued) Use caution when using %BF displayed on analyzer; you must know what equation was used. A population-specific equation is valid for only those individuals whose physical characteristics match the sample from which the equation was derived. (Table 8.5 presents commonly used population specific and generalized BIA equations.) Accuracy of BIA is similar to that of SKF using correct prediction equations Advantages of BIA: Does not require a high degree of technician skill More comfortable Less invasion of client’s privacy Can be used to estimate body composition of obese individuals (continued)

Bioelectrical Impedance Method (continued) Sources of error: Instrumentation (Research demonstrates significant differences in whole-body resistance when different brands of single-frequency analyzers are used ) Client factors (client should follow guidelines on p. 214 – see table) Technician skill (See Standardized procedures for the Whole-Body BIA method, p.215) Environmental factors / Post – exercise/Menstrual Cycle Prediction equation used to estimate FFM

Other Anthropometric Methods Anthropometry is the measurement of the size and proportion of the human body. These measures are relatively simple, inexpensive, and well suited for large epidemiological surveys and for clinical purposes. Minimal requirements are needed for technical skill and training. (continued)

Other Anthropometric Methods (continued) Circumferences: A circumference (C) is a measure of the girth of a body segment such as the arm, thigh, waist, or hip. A circumference is affected by fat mass, muscle mass, and skeletal size; they are related to fat mass and lean body mass. Bony diameters: A skeletal diameter (D) is a measure of bony width or breadth (e.g., of the knee, ankle, or wrist. Skeletal size directly relates to lean body mass. Body mass index: body weight divided by height squared; relationship of BMI to body fat varies with age, gender, and ethnicity. (continued)

Other Anthropometric Methods (continued) Anthropometric prediction equations estimate Db, %BF, and fat-free mass (FFM) from combinations of weight, height, skeletal diameters, and circumferences. Anthropometric equations are based on either population-specific or generalized models. Generalized equations include body weight or height, along with two or three circumferences, as predictors of Db or %BF. BMI, WHR (waist to hip ratio – see sequential slides) , waist circumference (WC – see sequential slides) , waist–height ratio (WHTR – see sequential slides) , and SAD (sagittal abdominal diameter– see sequential slides) are used to assess regional fat distribution and to identify at-risk individuals. Existing standardized techniques must be followed.

Using the Anthropometric Method to Estimate Body Composition – Additional Considerations The predictive accuracy of anthropometric (circumference and diameter) equations is not greatly improved by the addition of SKF measures. Anthropometric equations using only circumferences estimate the body fatness of obese individuals more accurately than SKF prediction equations (see Table 8.6, p.219, for prediction equations) Compared to SKFs, circumferences and skeletal diameters can be measured with less error Some practitioners may not have access to SKF calipers

Body Mass Index Easily calculated (body weight ÷ height squared). See also Nomogram, Figure 8.13 Widely used to identify at-risk individuals (a significant predictor of cardiovascular disease and type 2 diabetes) Does not account for composition of the body Possible misclassifications of underweight, overweight, and obese status (because BMI is a better measure of non-abdominal and abdominal subcutaneous fat than of visceral fat, other anthropometric indices need to be used to assess fat distribution.) BMI cutoff to define obesity (≥30 kg/m2) may not be appropriate. Ethnic-specific cutoff values need to be established that account for the relationship between BMI and %BF and for the morbidity and mortality risks in relation to BMI for specific ethnic groups

Table 8.7

Waist Circumference Indirect assessment of abdominal adiposity Some studies show that Waist circumference (WC) alone may predict obesity-related health risk better than the combination of BMI and waist circumference. Gender-specific circumference cutoff values are used to classify obesity. (info on waist circumference measures - myhealthywaist.org)

Waist-to-Hip ratio (WHR) An indirect measure of lower- and upper-body fat distribution Calculated as waist circumference (cm) ÷ hip circumference (cm) Young adults with WHR values >0.94 for men and >0.82 for women are at high risk for adverse health consequences Location of waist site is not universally standardized (Table 8.8, Nomogram 8.14 on p. 221 and 222 is from Anthropometric Standardization Reference Manual, where the waist circumference is at the narrowest part of the torso and the hip circumference at the level of the maximum extension of the buttocks.)

Waist-to-Hip ratio (WHR) - Limitations ■ The WHR of women is affected by menopausal status. Postmenopausal women show more of a male pattern of fat distribution than do premenopausal women. ■ The WHR is not valid for evaluating fat distribution in pre-pubertal children. ■ The accuracy of the WHR in assessing visceral fat decreases with increasing fatness. ■ Hip circumference is influenced only by subcutaneous fat deposition; waist circumference is affected by both visceral fat and subcutaneous fat depositions. Thus, the WHR may not accurately detect changes in visceral fat accumulation.

Waist–Height Ratio (WHTR) WHTR = waist circumference at the umbilical level divided by standing height May be better indicator of adiposity and health risks than waist circumference alone A cutoff boundary value of WHTR >0.50 indicates an increased health risk for men and women As a rule, waist circumference should be less than half the height The Ashwell Shape Chart can be used to identify your client’s health risk based on body shape (see appendix D.6, p. 371).

Sagittal Abdominal Diameter SAD measures antero-posterior thickness of the abdomen at the umbilical level. Excellent indirect measure of visceral fat. SAD is strongly related to visceral adipose tissue in men and women, even after adjusting for BMI SAD is more strongly related to risk factors for cardiovascular and metabolic diseases in adults. Procedures to assess SAD are not standardized. In most studies, SAD was measured while the client was lying supine, legs extended, on an examination table. A sliding-beam anthropometer is used to measure the vertical distance (to the nearest 0.1 cm) between the top of the table and the abdomen at the level of the umbilicus or iliac crests.

Skeletal Frame Size Skeletal Diameters are used to classify frame size to improve validity of height–weight tables for evaluating body weight Helps differentiate weight due to a large musculoskeletal mass from weight due to a large fat mass You can classify frame size by using reference data for elbow breadth (see table 8.9). The anatomical landmarks for measurement are described in appendix D.5, “Standardized Sites for Bony Breadth Measurements,” page 370.

Frame Size Possible causes of errors: Instrumentation - instruments must be carefully maintained and must be calibrated periodically so that their accuracy can be checked and restored. Client factors – may be difficult in muscular or obese individuals Technician skill - Closely follow standardized testing procedures for locating measurement sites, and positioning the anthropometer. See standardized proCedures for AnthropometriC meAsurements, p. 224. END