Body composition is a physiologic characteristic that affects an individual’s ability to carry out daily tasks with vigor. Although body composition is not a demonstrative action like other health-related fitness components, the committee has operationally defined it as a component of fitness, a health marker, and a modifier of fitness for the purposes of this report. Both body weight (mass) and body fat (absolute fatness and relative fat distribution) are elements of body composition that have implications for health and fitness. It is important to measure weight and height in national youth fitness surveys to derive body mass index (BMI), an indicator of weight-for-height; waist circumference, an indicator of abdominal adiposity; and skinfolds, an indicator of subcutaneous adipose tissue. These three recommended field indicators of body composition for a national youth fitness survey uniquely measure different elements, and each can be linked to health markers and outcomes in both youth and adults. For example,
- A high BMI is related to the risk of type 2 diabetes and hypertension.
- Waist circumference is linked to risk factors for cardiovascular disease, type 2 diabetes, and all-cause mortality.
- Elevated skinfold thicknesses and proportionally more subcutaneous fat on the trunk are associated with an elevated risk for cardiovascular disease and metabolic syndrome.
Only standing height and weight should be measured in school and other educational settings to calculate BMI given such concerns as measurement errors and privacy.
Two approaches to interpreting the results of the above three measures are recommended to determine whether individuals or populations are at risk of poor health outcomes. For BMI, the cut-points (cutoff scores) based on the 2000 Centers for Disease Control and Prevention (CDC) growth charts and percentiles should be applied for underweight, overweight, and obesity evaluations. Interim cut-points for waist circumference and skinfold measures should be set at levels analogous to those currently being applied by the CDC for BMI. This approach should be used until evidence becomes available to support establishing waist circumference and skinfold cut-points by associating those measures with cardiometabolic risk factors.
Body weight (mass) and body fat distribution are elements of body composition that have implications for health and fitness. No element on its own adequately and comprehensively describes an individual’s body composition, and each element has been linked with various health markers and outcomes in youth.
Measures of body composition have been used in the past as a component of fitness test batteries (see Table 2-6 in Chapter 2). The background paper for the Second International Consensus Symposium on Physical Activity, Fitness and Health in 1992 offered an outline of “components and factors of health-related fitness” (Bouchard and Shephard, 1994; Bouchard et al., 2007) in which body composition was included as a morphological component of health-related fitness. In a review of existing fitness tests, 10 of 15 physical fitness test batteries for children and adolescents included body composition as a component of health-related fitness (Artero et al., 2011; Castro-Piñero et al., 2010), but the supporting evidence for their inclusion was quite variable.
Body composition differs from the other fitness components reviewed in this report at various levels. First, there are different perspectives on whether body composition should be considered a component of fitness. The committee considered body composition to be a physiologic characteristic that affects an individual’s ability to carry out daily tasks with vigor and to be influenced by physical activity behavior. Second, body composition influences performance on many fitness tests and itself is also an indicator of health. The committee thus defined body composition operationally as a component of fitness, a marker of health, and a modifier of fitness,
for the purposes of this report. Finally, the relationships between body composition, in particular percent body fat, and health outcomes are well established in both youth and adults. Thus, the committee did not collect evidence on the relationship between any body composition field measures and health outcomes. The committee identified appropriate measures of body composition by selecting field-based items that were valid, reliable, and feasible for implementation in either a national survey or a school or other educational setting.
This chapter provides an overview of the existing measures of body composition and presents the committee’s conclusions about the best measures of body composition based on their relationship to health in youth, as well as their integrity and feasibility. The committee’s full recommendations for measuring body composition in a national fitness survey and in schools and other educational settings can be found in Chapters 8 and 9, respectively.
Body weight is a gross measure of the mass of the body. The partitioning and quantification of mass into its basic elements has been a major focus of study historically and has accelerated with the refinement of models (Wang et al., 1992, 2005) and the development of technology (Ackland et al., 2012; Heymsfield et al., 2005; Roche et al., 1996). A variety of models and methods—developed largely in adults—have been used to partition body mass into several elements: fat-free mass, fat mass, total body water, fat-free dry mass, and bone mineral. As assessment techniques have become refined, models have evolved from those including the traditional two elements (body mass = fat-free mass + fat mass) to those including three, four, or five elements (Wang et al., 1992, 2005), with fat mass—or adipose tissue as it is labeled in anatomical models—being basic to all models.
Body composition can be approached at several levels: atomic, molecular, cellular, tissue, and whole body (Wang et al., 1992, 1995). The technology for measuring specific elements of body mass at each level and factors influencing body composition have been summarized (Heymsfield et al., 2005; Roche et al., 1996). While no single criterion measure of body composition is universally accepted as the gold standard (Ackland et al., 2012), laboratory measures (e.g., underwater weight, body potassium, total body water, and dual-energy X-ray absorptiometry [DXA]) are considered the most accurate techniques. DXA provides measures of bone mineral and of fat and lean tissues. The other three laboratory measures have major limitations. Underwater weighing is used to estimate body density, which is then converted to percentage body fat; total body potassium and total body water provide measures of fat-free mass. Quite often, the laboratory
measures are used together (especially underwater weighing, total body water, and a measure of bone mineral) to provide an estimate of body composition, depending on the model selected (see, e.g., Gutin et al., 1996). Several additional laboratory techniques, as well as field measurements available for estimating body composition in youth in various settings (e.g., research, education/practice, clinical), have been reviewed extensively by others (Heymsfield et al., 2005; Roche et al., 1996).
Critical evaluation of body composition methodology at each level of analysis (Wang et al., 1992, 1995) is beyond the scope of this report. Further, while laboratory methods—such as DXA, hydrostatic weighing, ultrasound, densitometry, and air displacement plethysmography (e.g., Bod Pod®)—have many advantages (such as more specific measurements and reduced measurement variation, measurement of the whole body, minimal subject burden, and relative ease of administration), they typically require highly specific training and special and expensive equipment. Some of the equipment also lacks the mobility that may be necessary to access large samples of youth.
Overall, the measurement of body composition is dependent on the question being addressed, the information necessary, and the application of the assessment protocols (Ackland et al., 2012). For example, techniques used for collecting data to track the health status of a given population epidemiologically will likely differ from those used to collect data to achieve advances in sports performance. Also, many laboratory methods are not feasible for use in the field because of limitations cited earlier. Direct evaluation of body composition (i.e., DXA measure of adiposity) is not the same as indirect and associated proximity measures of body composition. Body mass index (BMI) is used for classification of weight status (underweight, normal, overweight, obese), although it does not accurately predict percent body fat (Moreno et al., 2006). Accordingly, the selection of body composition measures depends on what element is of interest, which in turn depends on the question(s) being asked. Given the desirability of a comprehensive understanding of an individual’s body composition, as well as considerations of feasibility in practice settings such as schools, the committee focused its review on low-cost field-based measures of body composition.
Laboratory measures, such as DXA, may be appropriate for some national surveys, like the National Health and Nutrition Examination Survey (NHANES), for which the equipment is transported in a trailer and only a small sample of youth is studied. For large national surveys in which youth are tested nationwide in a school setting, however, field-based measures are more suitable than laboratory measures. Field-based measures include anthropometry (skinfolds, weight, height [weight-for-height in the form of BMI], waist circumference) and bioelectric impedance analysis
(BIA). These measures were selected based on their relationship to health markers, their integrity and reliability, and their previous use.
- Skinfolds provide an indication of subcutaneous fat at specifically defined measurement sites. Skinfolds can also be used to predict percent body fat. They can be expressed as a sum of skinfolds (overall subcutaneous fat) and as a ratio of trunk to extremity skinfolds (relative subcutaneous fat distribution).
- BMI (kg/m2) is an indicator of weight-for-height. It is used internationally in public health and nutrition surveys to monitor weight status, specifically overweight and obesity. At the extremes of heaviness, BMI is probably a reasonable indicator of fatness in the general population.
- Waist circumference increasingly is used as an indicator of central or abdominal adiposity rather than percent body fat, which can vary greatly among individuals with a similar BMI. Located in the abdominal region, abdominal fat is composed of three elements: visceral, retroperitoneal, and subcutaneous.
- BIA provides a measure of resistance or impedance; some BIA systems are calibrated directly to fat-free mass (or fat). Some other systems provide a measure of total body water that is then transformed to an estimate of fat-free mass. The equation for converting resistance to total body weight usually includes height. Algorithms used in estimating body composition with BIA with commercially available units are considered proprietary information, which is a major shortcoming. Moreover, it has been suggested that equations provided by manufacturers may not be suitable for estimating body composition in youth of different racial/ethnic backgrounds (Haroun et al., 2010). Given its shortcomings and the abundant evidence on the effectiveness of other field-based measures, the committee did not explore BIA further. However, if shortcomings due to proprietary equations were resolved and the algorithms accounted for changes in the composition of fat-free mass during childhood and adolescence, for sex differences, and for racial/ethnic variations in body composition, BIA might be considered a useful measure of body composition in youth, particularly given its ease of administration.
As noted earlier, the fact that body composition is a measure of health is well established. Also well established is that percent body fat is related to health outcomes and that there are various tests with which to measure
percent body fat, subcutaneous fat, or abdominal adiposity. Therefore, the Centers for Disease Control and Prevention’s (CDC’s) literature review, described in Chapter 3, did not include body composition as a fitness component; the CDC review, however, included articles in which body composition appeared as a modifier of fitness or as a health marker or both. For this reason, the committee considered each such article for inclusion in its review, and this chapter includes findings from selected studies from the CDC review, as well as others, in which body composition was considered as a fitness component, a health marker, or a modifier of physical fitness. A body of literature from obesogenic intervention research was also reviewed. In addition, the committee reviewed validity and reliability data specific to field tests that measure various aspects of body composition. Further, articles on specific topics related to body composition (e.g., growth and maturation, race/ethnicity, and body composition and health) were identified and chosen for inclusion in this chapter.
In addition to age, energy intake, and other factors, individual differences in biological maturation, gender, and race/ethnicity affect elements of body composition such as fat mass and fat-free mass, subcutaneous fat, and fat distribution. The following discussion is based on trends described in Malina (1996, 2005) and Malina et al. (2004).
Variation in Body Composition with Age, Gender, and Maturation Status
Fat-free mass, fatness, and relative fat distribution in late childhood and adolescence (approximate school ages) vary with age, between genders, and among individuals of contrasting maturation status. Age- and gender-related changes are discussed in the subsections that follow. Variation associated with maturation status is then briefly considered.
The principles underlying several methods for estimating body composition warrant special consideration when applied to growing and maturing youth. It is important to determine when mature (adult) levels of the primary elements of fat-free mass are reached. This relates to the concept of chemical maturity, defined by Moulton (1923, p. 80): “The point at which the concentration of water, proteins, and salts [minerals] becomes comparatively constant in the fat-free cell is named the point of chemical maturity of the cell.” Chemical maturity of fat-free mass is not attained until after the adolescent growth spurt, probably about ages 16-18 in girls
and 18-20 in boys (Lohman, 1981, 1986; Malina, 2005; Wells et al., 2010). When adult values of its primary components are reached, fat-free mass is chemically mature.
On average, fat-free mass has a growth pattern like that of stature and body mass. Differences over time until chemical maturity is reached reflect a larger fat-free mass, specifically bone mineral content and skeletal muscle mass in males. That is, the relative contribution of water to body mass decreases while the relative contributions of solids—protein, mineral, and fat—increase during approximately the first two decades of life, which are dominated by the biological activities of growth and maturation. Sex differences are apparent during the adolescent growth spurt. On average, fat-free mass in males contains relatively less water and more protein and mineral compared with that in females from childhood into young adulthood (Malina et al., 2004). Density of fat-free mass is also greater in males, which reflects primarily sex differences in skeletal muscle mass and bone mineral. These are only average trends, and it should be noted that there are variations among individuals and with biological maturation (status and timing).
Although efforts continue to derive more accurate estimates of the chemical composition of fat-free mass, three points should be noted: (1) the composition of fat-free mass changes during growth and maturation, (2) variation among individuals is considerable, and (3) chemical maturity is not attained until late adolescence or young adulthood. Ideally, equations and constants used to estimate body composition should be adjusted for the chemical immaturity of the fat-free mass in growing and maturing individuals.
Fat mass increases more rapidly in girls than in boys during childhood and continues to increase through adolescence in girls (Malina, 2000). Fat mass appears to reach a plateau, or to change only slightly, near the time of the adolescent spurt in boys (around age 13-15) (Malina, 2000). Fat mass as a percentage of body mass (percent body fat) increases gradually during childhood, and sex differences are small. Percent body fat increases through adolescence in girls; it increases into early adolescence in boys and then declines. The decline during male adolescence is a function of the adolescent spurt in fat-free mass, more specifically muscle mass. Sex differences in body composition are negligible in childhood, and are established during the adolescent spurt and sexual maturation (Malina, 2000). Although estimated fat mass is similar in male and female adolescents, females have greater percent body fat.
BMI, as a measure of weight-for-height, declines from infancy through early childhood and reaches its lowest point at about age 5-6. It then increases linearly with age through childhood and adolescence and into adulthood. Sex differences in BMI are small during childhood, rise during adolescence, and persist into adulthood (Malina et al., 2004). The rise in BMI after it reaches a nadir at age 5-6 has been labeled the “adiposity rebound” (Rolland-Cachera et al., 1984). It has been suggested that individuals who have an early adiposity rebound have an increased probability of being overweight in late adolescence and young adulthood (Rolland-Cachera et al., 1984). The concept of adiposity rebound needs further study. In the context of body composition, there is a need to document specific changes in body composition during the rebound. Does it reflect an increase in fat mass or an increase in fat-free mass? Some evidence suggests the latter (Katzmarzyk et al., 2012).
A skinfold thickness is a double fold of skin and underlying soft tissues, primarily adipose tissue. Two commonly used skinfolds are the triceps and subscapular. The former increases with age from childhood through adolescence in females, whereas it decreases during the adolescent spurt in males (Malina, 2000). On the other hand, the latter increases from childhood through adolescence in both sexes. As a result, the adolescent sex difference in the triceps skinfold is marked compared with the relatively small difference in the subscapular skinfold.
Any number of skinfolds can be and have been measured. Changes in individual skinfolds are variable during growth and specifically relative to the timing of peak height velocity, more so in boys than in girls (Malina et al., 1999). Such variation may influence age-associated trends.
Relative Fat Distribution
Fat distribution refers to regional variation in the accumulation of adipose tissue in the body. With advances in technology (computed tomography [CT] scans, magnetic resonance imaging [MRI]), attention shifted to abdominal fatness, specifically visceral versus subcutaneous. With widespread availability of DXA, trunk and extremity distribution of adipose tissue also has received more attention (Malina, 1996, 2005). Ratios of skinfolds measured on the trunk to those measured on the extremities are commonly used to estimate relative subcutaneous fat distribution. Ratios of trunk to extremity skinfold thicknesses increase gradually through child-
hood in both sexes, and there is no sex difference in the ratios. Subsequently, ratios tend to be rather stable in females but to increase in males through adolescence. Males accumulate proportionally more subcutaneous fat on the trunk than the extremities, while females accumulate relatively similar amounts on both the trunk and extremities (Malina, 1996; Malina and Bouchard, 1988). Ratios of trunk to extremity adiposity based on DXA show similar trends (He et al., 2004; Taylor et al., 2010). Ratios of abdominal visceral and subcutaneous adiposity show small differences with age and sex from childhood into early adolescence in normal-weight youth, but males have proportionally more visceral adiposity in later adolescence. A similar trend associated with age and sex is not clearly apparent in overweight/obese youth (Katzmarzyk et al., 2012).
Children and adolescents advanced in maturity status compared with their chronological-age peers tend to be fatter and to have proportionally more subcutaneous fat on the trunk (Malina and Bouchard, 1988; Malina et al., 2004). The maturity-associated trend also continues into young adulthood (Beunen et al., 1994a; Kindblom et al., 2006; Labayen et al., 2009; Sandhu et al., 2006). Samples in studies using DXA, CT scans, and MRI generally involve several age groups, so that it is difficult to clearly specify maturity differences in each gender. Stage of puberty (clinically and/or self-assessed) is often described, but not systematically analyzed. When it is described, youth typically are grouped by pubertal stage or stages so that several ages are represented within a group (Katzmarzyk et al., 2012).
Variation in Body Composition with Race/Ethnicity
The pattern of gender- and maturity-related differences is similar in all racial/ethnic groups. African Americans have greater total bone mineral content during childhood, adolescence, and adulthood than whites. Comparisons between Mexican Americans and whites show small differences in fat-free mass and bone mineral content, although Mexican Americans tend to have greater adiposity. Data for skinfolds indicate proportionally more subcutaneous adipose tissue on the trunk in African Americans, Mexican Americans, and Asian Americans compared with whites. In contrast, data on the distribution of visceral and subcutaneous adiposity overlap among ethnic groups. Unfortunately, the available data often combine multiple age groups and in some instances combine males and females and/or youth of different ethnic groups (Katzmarzyk et al., 2012; Malina, 2005).
This section considers body composition as both a modifier of physical fitness and a health marker.
Body Composition as a Modifier of Physical Fitness
Body composition is one of many factors that influence performance on laboratory- and field-based tests of physical fitness. Fat-free mass and its major tissue component, skeletal muscle mass (force-generating tissue of the body), obviously are important to performance on many tests. Absolute fat-free mass is significant in tests requiring the projection of objects (e.g., overhead medicine ball throw) and a variety of strength tests. Fat-free mass also is highly correlated with height in children and adolescents. Fat mass and percent body fat are more variable, but excess fatness (absolute and relative) tends to exert a negative influence on performances on fitness tests that require movement or projection of the body through space (i.e., runs and jumps) as opposed to projection of objects, as well as on endurance tests on cycle ergometers (Boileau and Lohman, 1977; Houtkooper and Going, 1994; Malina, 1975, 1992).
Two studies of national samples of Belgian youth considered relationships between the sum of skinfolds (four in boys, five in girls) and a variety of fitness tests (Beunen et al., 1983; Malina et al., 1995). Among males aged 12-20, partial correlations (controlling for height and body mass) and several relevant fitness test items (static arm pull strength, sit-and-reach, vertical jump, left lifts, flexed arm hang, agility) were negative and low to moderate, –0.13 to –0.40. Corresponding partial correlations in girls aged 7-17 ranged from –0.08 to –0.42 (Physical Working Capacity-170 [PWC-170], step test recovery, arm pull strength, sit-and-reach, sit-ups, leg lifts, flexed arm hang, standing long jump, vertical jump agility). Comparison of the fattest and leanest 5 percent of participants highlighted the negative influence of excessive subcutaneous fatness for all fitness test items except sit-and-reach, arm pull strength, and PWC-170. Differences in flexibility were negligible. The fattest were absolutely stronger (boys and girls) and generated more watts (girls only), reflecting their larger body size. The fattest youth of both sexes also were advanced in skeletal maturation compared with their leanest peers of the same age groups (Beunen et al., 1982, 1994b).
Trends were generally similar in more recent samples of normal-weight and obese youth. For example, sum of skinfolds was inversely related to schoolchildren’s performance on the progressive aerobic cardiovascular endurance run (PACER), push-up, and curl-up tests (r = –0.30 to –0.49) (Lloyd et al., 2003). Low levels of cardiorespiratory endurance were associated with percent body fat in African American and white adolescents
(Gutin et al., 2005); with visceral and subcutaneous abdominal fat and waist circumference in African American and white youth aged 8-17, controlling for age, sex, pubertal status, and BMI (Lee and Arslanian, 2007); with percent body fat, percent abdominal fat, and waist circumference in 8-year-old boys and girls (Stigman et al., 2009); and with BMI, skinfolds, and predicted percent body fat in obese children of both sexes aged 6-13 (Nassis et al., 2005).
Studies evaluating the relationship between BMI and fitness tests generally have focused on the negative influence of obesity (Chatrath et al., 2002; Deforche et al., 2003; Kim et al., 2005; Mota et al., 2006; Stratton et al., 2007) or BMI as a covariate of aerobic fitness (Beets and Pitetti, 2004; Beets et al., 2005). Youth aged 5-14 classified as “underfit” (based on pass-fail scores on five fitness tests) were at greater risk of obesity (Kim et al., 2005). Correlations between BMI and indicators of fitness tended to be linear in well- and undernourished children aged 6-14 (Malina et al., 1998), but were curvilinear in youth aged 12-15 (Bovet et al., 2007) and young adults (Sekulic et al., 2005; Welon et al., 1988). A recent study with a representative sample of Brazilian youth showed that, after adjusting for potential confounding factors, weight and BMI were negatively correlated with performance on the long jump, curl-up, pull-up, 9-minute run, 20-meter run, and 4-meter shuttle run (Dumith et al., 2012).
Data on variations in fitness across the broad spectrum of BMI within relatively narrow age groups are limited. Relationships between BMI and fitness varied among fitness test items in four age groups—9-10, 11-12, 13-15, and 16-18—in a national sample of Taiwanese youth (Huang and Malina, 2010). Correlations were low to moderate and did not vary among age groups or between sexes. They were highest for a distance run/walk (800/1,600 meters, 0.17 to 0.34) and lowest for the sit-and-reach (0.04 to 0.12). For sit-ups and the standing long jump, however, correlations were higher for boys than for girls (r = 0.15 to 0.23 versus 0.10 to 0.14 and 0.22 to 0.27 versus 0.12 to 0.17, respectively). In a national sample of Taiwanese youth (Huang and Malina, 2010), sex-specific regressions of fitness items on BMI, using a nonlinear quadratic model, indicated differential effects for individual tests, which varied with age and sex. Relationships for the sit-and-reach were similar and slightly curvilinear in girls aged 9-10 and boys aged 9-12, but were parabolic among girls aged 11-18 and boys aged 13-18. Peaks of the parabola were sharper in adolescent boys than in adolescent girls. Youth of both sexes aged 13-18 with either higher or especially lower BMIs had the poorest flexibility. Relationships for sit-ups were similar in girls and boys aged 9-12. Above ~20 kg/m2 in girls and ~18 kg/m2 in boys, sit-ups declined with increasing BMI. The decline was initially slight but accelerated with increasing BMI, more so in girls. The relationship between BMI and performance on sit-ups was parabolic in
youth aged 13-18, more so in boys. Performance on the standing long jump (muscle power/explosive strength) declined linearly with increasing BMI in boys aged 9-10. The relationship was curvilinear in other age groups of boys and all age groups of girls, and was especially parabolic in boys aged 13-18. Times to complete the 800-meter run/walk increased (indicative of poorer performance) linearly with an increase in BMI in girls aged 9-10 and boys aged 9-12. Times varied little in older girls with BMI of 10-20 kg/m2 but became progressively higher (indicative of poorer performance) with increasing BMI. Among older boys, times on the 1,600-meter run/walk declined (improved performance) with an increase in BMI from 10 to ~20 kg/m2, and subsequently increased linearly (poorer performance) with increasing BMI.
Body Composition and Health
Excessive adiposity and especially abdominal obesity have been associated with risk factors for cardiovascular disease and metabolic syndrome in youth (e.g., Reed et al., 2008; Tjonna et al., 2009; Williams et al., 1992). The Bogalusa Heart Study, a longitudinal study investigating the risk factors for cardiovascular disease since 1972, provides many insights into the relationship between different measures of body composition and cardiovascular health in a biracial population (African American and white). The study found that by age 10, 60 percent of children who were overweight had at least one biomarker or risk factor for cardiovascular disease (Freedman et al., 1999a). Likewise, a dose-response relationship between increasing body weight and the presence of two or more cardiovascular disease risk factors—specifically prehypertension/hypertension, low high-density lipoprotein (HDL) cholesterol, and prediabetes/diabetes—was found in the NHANES 1999-2008 data set (May et al., 2012). More than one cardiovascular disease risk factor (besides body weight) was seen in 49 percent of overweight and 60 percent of obese adolescents (May et al., 2012). Other studies have confirmed these findings, suggesting that elevated weight status is associated with increased risk for cardiovascular disease (Chang et al., 2008; Jekal et al., 2009; Ribeiro et al., 2004), particularly with low cardiorespiratory fitness in children (Carnethon et al., 2005; Lobelo et al., 2010). Markers of metabolic syndrome (a cluster of precursory risk factors) also are associated with elevated childhood weight status (Rizzo et al., 2007). For example, obese youth have an increased risk for prediabetes compared with nonobese youth (Li et al., 2009). Among overweight children, those with prediabetes had 4 percent lower bone mineral content than those without prediabetes (Pollock et al., 2010).
Higher levels of body fatness predicted from skinfolds have been linked to increased cardiovascular disease risk in youth (Going et al., 2011). Estimated fatness levels above 20 percent in boys and 30 percent in girls
were associated with risk factors for cardiovascular disease and metabolic syndrome, especially elevated C-reactive protein and insulin levels (Going et al., 2011).
The location of adipose tissue stores also influences cardiometabolic risk. Compared with more generalized obesity (measured as BMI), abdominal obesity was more strongly associated with risk of myocardial infarction, stroke, and premature death in adult men (Larsson et al., 1984). Waist circumference has been associated with cardiovascular risk factors such as insulin levels (Bassali et al., 2010) and may be a better predictor of cardiovascular disease than BMI alone (Savva et al., 2000; WHO, 2011). A review of the adult literature, however, found that neither waist circumference nor BMI had superior discriminatory capability in identifying cardiovascular disease risk (Huxley et al., 2010), thus demonstrating the value of measuring both. Abdominal adipose tissue also was associated with higher blood pressure, type 2 diabetes, and dyslipidemia in adults, but the relationship remains unclear in children (Daniels et al., 1999; Freedman et al., 1999b, 2012; Goran and Gower, 1998). Nevertheless, relationships between markers of disease risk and body composition were noted in school-aged youth in the Bogalusa Heart Study, specifically among African American girls aged 5-17, in whom a 20-cm increase in waist circumference was associated with a decrease in concentration of HDL cholesterol and increases in triacylglycerol and insulin (Freedman et al., 1999b). The association with the risk factors was stronger for waist circumference than for skinfold thickness (subscapular and triceps measurements). In overweight children, neither BMI nor the sum of skinfolds was a good predictor of risk factors for cardiovascular disease; a measure of fat distribution (waist-to-height ratio) was a better predictor of cardiovascular risk factors (low-density lipoprotein [LDL] cholesterol, HDL cholesterol, fasting insulin, and systolic and diastolic blood pressure) (Freedman et al., 2009).
Evidence for the contribution of measures of body composition to cardiovascular health also was noted in the European Youth Heart Study. Among children aged 9 and 15 from Denmark, Estonia, and Portugal, waist circumference and the sum of skinfolds were associated with clustered cardiovascular disease risk, determined by a composite score of systolic blood pressure, triglycerides, insulin resistance (using the homeostasic model assessment-insulin resistance [HOMA-IR] level), and ratio of total cholesterol to HDL (Andersen et al., 2008).
The relationship between weight status and risk for cardiovascular disease tends to track from childhood and adolescence into adulthood (Freedman et al., 2001; Herman et al., 2009). For example, changes in BMI and childhood blood pressure were found to be strongly correlated with adult blood pressure in both sexes (Lauer and Clarke, 1989). Based on logistic models developed with BMI data from youth aged 3-20 and
adults aged 30-39 in the Fels Longitudinal Study, childhood and adult obesity are related, and the risk becomes stronger in adolescence (Guo et al., 2002). Another analysis of data from the Bogalusa study showed that the sum of skinfold thicknesses (triceps and subscapular measurements) and BMI z-score in childhood were the main contributors to higher levels of high-sensitivity C-reactive protein in adults, a risk factor for cardiovascular disease. The effect of skinfold thicknesses was greater in African Americans than in whites and in girls than in boys (Toprak et al., 2011). A recent systematic review of the tracking of obesity and its association with metabolic risk in adulthood, however, suggests that weight status and cardiometabolic risk factors should perhaps be considered independently of each other, given the limitations of current research designs (Lloyd et al., 2012). Finally, analysis of data from the Bogalusa study shows that BMI and subscapular skinfold measurements are positively correlated with the risk of becoming a diabetic adult (Nguyen et al., 2008).
In summary, indicators of body composition, specifically adiposity, are determinants of health. Prevention of the accumulation of excess adiposity and specifically overweight/obesity among youth holds potential for yielding immediate and long-term health benefits. Health implications of fat-free mass in youth apparently have not been systematically addressed.
By definition, field-based measurements such as skinfolds, BMI, and waist circumference are, to a large extent, indirect estimates of body composition. The advantages of field measures include minimal subject burden, adequate reliability in the hands of trained technicians (see more on quality control in Annex 4-1), and relatively rapid data acquisition for a large number of subjects. Limitations include reduced accuracy, high variability, and lack of broad applicability in all populations. The validity of field-based measurements is usually assessed by comparison with laboratory measures (e.g., underwater weight, body potassium, total body water, and DXA). Although evidence for the validity of field-based measures of body composition is variable (see below), their associations with markers of health risk justifies including them in a survey of youth fitness.
It is important to note that the accuracy of anthropometric measures is strongly dependent upon the experience and training of technicians in implementing the measurements. Care in interpreting the data also is necessary in working with youth. Anthropometric measures (BMI, percent body fat, skinfolds, circumferences) and other indicators of body composition (fat-free mass based on densitometry, total body water and potassium con-
centration, lean and fat tissue, bone mineral via DXA) change with age and are influenced by gender, race/ethnicity, and biological maturation status (Daniels et al., 1997; Malina, 1996, 2005; Malina et al., 2004). Elements of body composition, especially bone mineral content, also may be influenced by regular physical activity (Strong et al., 2005).
Body Mass Index (BMI)
BMI is an indicator of weight-for-height. As discussed earlier, in contrast to height and weight, which increase with age during childhood, BMI declines from infancy through early childhood and reaches its lowest point at about age 5-6.
BMI is reasonably well correlated with fat mass and percent body fat in heterogeneous samples of youth, but has limitations (Goran et al., 1995); it also is related to fat-free mass. Among youth aged 8-18 in the Fels Longitudinal Study, age-specific correlations between BMI and components of body composition ranged from 0.37 to 0.78 for percent body fat, 0.67 to 0.90 for fat mass, and 0.39 to 0.72 for fat-free mass in girls, and from 0.64 to 0.85 for percent body fat, 0.83 to 0.94 for fat mass, and 0.25 to 0.78 for fat-free mass in boys (Maynard et al., 2001). When chronological age was statistically controlled in five samples of boys and girls aged 8-18, correlations for BMI were a bit lower: percent body fat, 0.28 to 0.61; fat mass, 0.46 to 0.81; and fat-free mass, 0.27 to 0.64 (Malina and Katzmarzyk, 1999). Correlations for fat mass and fat-free mass were similar in four of the five samples, but those for BMI and percent body fat were variable. In a nationally representative sample of American children aged 2-19 in NHANES III, BMI was better than other anthropometric indicators (Rohrer index and weight-for-height) in predicting underweight and overweight when percent body fat or total fat mass based on DXA was the criterion measure (Mei et al., 2002).
Nevertheless, youth with the same BMI can differ considerably in fat mass and percent body fat, so care is essential when interpreting BMI as an indicator of fatness in youth. BMI is, more appropriately, an indicator of heaviness and, indirectly, of adiposity; at the extremes of heaviness, BMI is probably a reasonable indicator of fatness in general population surveys, but its limitations must be recognized (Pietrobelli et al., 1998).
Limited evidence supports higher intra- and interobserver reliability for BMI and waist circumference than for skinfold thicknesses (Artero et al., 2011). Beyond the debate about what the measurement of BMI actually represents (body composition, body fat, body weight, etc.), the association between BMI and health markers justifies its use among school-aged children as a means of tracking health status.
Waist circumference is an emergent measure of body composition. Its use as a dimension of body composition is justified for various reasons. First, it is an indicator of abdominal fat as opposed to waist-to-hip circumference ratio, which is an indicator of fat distribution (Despres et al., 1989). Second, criterion measures that relate to health have already been established in certain populations of youth (Liu et al., 2010). Further, other measures are more challenging to administer, such as measuring hip circumference to determine waist-to-hip ratio (WHO, 2011). Additionally, other waist measures have insufficient data to support their consideration and have not been found to be a better predictor of health risk than waist circumference (Huxley et al., 2010). Waist circumference is strongly associated with intra-abdominal (visceral) adipose tissue (r = 0.84) and subcutaneous abdominal adipose tissue (r = 0.93) in prepupertal children (Goran and Gower, 1998) and with trunk fat (r = 0.92) in children and youth aged 3-19 (Taylor et al., 2000). On the other hand, it has been suggested that waist circumference has no advantage over BMI for diagnosing high fat mass in youth aged 9-10 (Reilly et al., 2010).
According to a measurement protocol for adolescents, intra- and interobserver technical errors of measurement for waist circumference have been calculated at 1.31 cm and 1.56 cm, respectively (Malina et al., 1973). As mentioned above, a review of reliability found higher intra- and interobserver reliability for BMI and waist circumference than for skinfold thicknesses (Artero et al., 2011). Mueller and Malina (1987) report high intra- and interobserver reliabilities for waist circumferences of 0.97 and 0.96, respectively, based on data from the Health Examination Survey for youth aged 12-17. Technical errors have also been reported in national surveys (ODPHP, 1985, 1987).
Unlike other field measures, waist circumference may not be a good indicator of percent body fat or fatness in youth. However, it is an indicator of abdominal adiposity (Lee et al., 2011), which provides information about a different dimension of body composition that is linked to health risks.
Sum of Skinfolds
Skinfolds are considered valid and reliable estimates of subcutaneous fat and predictors of percent body fat, assuming they are measured by trained individuals. Criterion-related validity for the sum of skinfold (triceps and calf) measurements ranged from r = 0.70 to 0.90 compared with hydrostatic weighing (Boileau et al., 1984). Specifically, reliability coefficients for sum of skinfolds vary by pubertal status in girls (Gutin et al., 1996). Others have reported acceptable interobserver reliability coefficients of 0.89 to 0.98 for
children aged 11-14 (Safrit, 1990). The technical error of measurement for subscapular skinfold varies from 0.88 to 1.16 mm for intraobserver error and from 0.88 to 1.53 mm for interobserver error (Harrison et al., 1988). For triceps skinfold, the technical error of measurement ranges from 0.4 to 0.8 mm for intraobserver error and from 0.8 to 1.89 mm for interobserver error (Harrison et al., 1988).
The triceps and subscapular skinfolds are the most widely used in growth studies, and national reference data were developed by using the samples included for BMI in the CDC 2000 growth charts (Addo and Himes, 2010). Skinfolds can be and have been measured on any number of bodily sites. A key is standard definition and location of the sites and proper marking of the sites prior to application of the skinfold calipers. As noted earlier, ratios of skinfolds measured on the trunk to those measured on the extremities are commonly used to estimate relative subcutaneous fat distribution, which has been related to chronic disease risk factors in youth.
When selecting fitness test items, an important criterion is the feasibility and practicality of the measures. The committee evaluated the feasibility and practicality of body composition measures assuming that they would be implemented by trained personnel as recommended in this report.
The measurements recommended for inclusion in a youth fitness test battery are height, weight, waist circumference, and triceps and subscapular skinfolds. All of these measurements can be taken reasonably quickly. The selected measurements, however, are not free of potential motivational or self-esteem influences; self-esteem may be affected by the interpretation of results for estimated body composition. For this reason and to protect privacy, waist circumference and subscapular skinfold thickness should not be assessed in group settings. It is assumed that appropriate space (e.g., a nurse’s office) would be available to ensure the privacy of the measurement process since measurement of skinfolds and waist circumference requires exposure of the trunk to allow the test administrator to access the subscapular area on the back and the waist. This setting also would minimize the potential for embarrassment when two test administrators are needed in the room (see below).
Equipment needed to measure body composition using the tests recommended above includes a stadiometer, a scale, skinfold calipers, and a tape measure. The NHANES measurement techniques are presented in Annex 4-1 as an example of commonly used methodology for indicators of body composition. As noted there, these anthropometric measurements, while not difficult, are highly error-prone. To avoid error, only high-quality equipment should be used, and test administrators should have the necessary
technical training. This training includes proper positioning for measuring height (standard erect posture with the head and eyes in the Frankfurt horizontal plane), procedures for stepping on and off the scale (for example, some children may require assistance, and children must be kept from jumping on the scale), positioning for measuring waist circumference (feet together), identification of the correct level for measuring waist circumference, and identification of the correct sites for measuring the triceps and subscapular skinfolds. The level for measuring waist circumference and the sites for each skinfold measurement should be marked on the skin.
Height and weight typically are measured without shoes and in light indoor clothing (e.g., shorts and a t-shirt); the subscapular site is easily accessed by raising the back of the t-shirt. Waist circumference is measured from the side (measurements taken face-to-face are generally invasive). Two technicians may be needed to measure waist circumference in some overweight and obese youth. This should not be a problem as a separate individual (who is well versed in the measurement protocols) should serve as recorder for the measurements. Other duties of the recorder include observation of the position of the subject (e.g., young children often slouch after being placed in the standard erect posture), proper identification of skinfold and waist circumference sites; and in measurement of waist circumference, checking to ensure that the tape is horizontal or is not pulled too tightly, resulting in major skin and soft tissue compression. The lack of a recorder will slow down the measurement process and contribute to potential error in transcribing measurements.
The committee acknowledges that there are multiple approaches to establishing cut-points (cutoff scores) for estimates of body composition depending on the purpose and on the available data. In general, the committee considered the following two approaches:
- Direct associations with health-related biomarkers—This method involves examining associations between BMI, waist circumference, or sum of skinfold scores and cardiometabolic risk factors in youth. Ideally, as discussed in Chapter 3, data necessary to establish those associations will exist from broad populations of youth.
- Indirect associations with health-related biomarkers using adult cut-points or data from other body composition measures—When the necessary data in youth are not available, associations can be examined in adult data, and cut-points established for adults can be projected to the corresponding percentile in children, if appropriate. When data needed to establish associations between a specific
test and health do not exist in youth or adults or when a cut-point exists in adults but extrapolation to youth is not appropriate (i.e., waist circumference, sum of skinfolds), the percentiles from another fitness measure (such as the 85th and 95th percentiles used for BMI) can be used temporarily to derive interim cut-points. As research progresses, cut-points based on the measure’s relationship to health in youth should be developed.
The committee concludes that these two approaches are appropriate for interpretation of body composition measurements administered in the context of a national youth fitness survey. For these approaches, a cut-point is determined specifically for each body composition test recommended. Obtaining information for the different indicators of body composition in this manner allows for a more complete and accurate description of an individual’s body composition. As a result, the interpretation of the tests in terms of health risks is expanded and possibly more accurate than if only one test is administered.
A third approach, which involves transforming the raw data to a measure of percent body fat by using prediction equations, has been used for interpreting body composition test items. This approach makes it possible to compare results from more than one measurement with a selected standard for percent body fat. This approach may be appropriate when test administrators must select one measure of body composition from multiple alternatives, such as when a battery of tests is applied in schools and other educational settings.
Body Mass Index
Cut-points for BMI have been calculated by age and gender from percentiles developed using the CDC growth charts based on data from large national surveys. The CDC growth charts are based primarily on data from the National Health Examination Survey (NHES) and NHANES from 1963 to 1994 (NHES II and III and NHANES I, II, and III). Data on body weight from NHANES III for subjects ≥6 years of age were not used so as to avoid the influence of an increase in body weight from previous years.1 Details are described in the CDC growth charts (Kuczmarski et al., 2000, 2002). Sample sizes were sufficiently large in the national surveys, which
1Questions arose over which population was appropriate for establishing such percentiles related to health given concern for the increasing prevalence of obesity between NHANES II (1976-1980) and NHANES III (1988-1994) (Kuczmarski et al., 2002; Ryan et al., 1999). Developing percentiles for weight using elevated values from NHANES III would have raised the percentiles and thus resulted in a false sense of having a satisfactory weight, specifically relative to stature.
TABLE 4-1 Centers for Disease Control and Prevention (CDC) Reference Values for Body Mass Index (BMI)
|Percentile Ranking||Weight Status|
|Less than 5th percentile||Underweight|
|5th percentile to less than 85th percentile||Healthy weight|
|85th percentile to less than 95th percentile||Overweight|
|Equal to or greater than 95th percentile||Obese|
were combined to produce the charts. Percentiles were derived for specific age groups by sex and were subsequently smoothed. Recommendations for the 85th percentile (P) to identify overweight, initially labeled as at risk of overweight (P85 ≥ BMI < P95), and the 95th percentile to identify obesity, initially labeled overweight (BMI ≥ P95), were based on the findings of an expert committee (Barlow and Dietz, 1998; Himes and Dietz, 1994). The recommendations have remained unchanged with the exception of overweight being used in place of risk of overweight and obesity in place of overweight (Barlow and Expert Committee, 2007). The CDC developed cut-points for underweight youth based on the 5th percentile as recommended by the World Health Organization’s Expert Committee on Physical Status (WHO, 1995).
A national survey of youth fitness in the United States should use the CDC cut-points for weight status (Table 4-1). An alternative set of cut-points is that developed by the International Obesity Task Force (Cole et al., 2000), which are widely used internationally.2
The same U.S. national data used to develop growth charts for body weight and BMI were used to develop reference curves for the triceps and subscapular skinfolds for youth through age 19 (Addo and Himes, 2010). The committee recommends using the established percentiles for BMI to derive interim cut-points until more studies are conducted to determine health-related cut-points in youth. The interim cut-points could be verified using the corresponding percentiles for the concurrent relationship to health in adults.
2Data used to develop the criteria for children and adolescents were based on six nationally representative cross-sectional samples from Brazil, Great Britain, Hong Kong, the Netherlands, Singapore, and the United States. In establishing the cut-points for children and adolescents, curves were mathematically fit to the pooled BMI data from the six studies so that they passed through the adult criteria for overweight (BMI of 25.0 kg/m2) and obesity (30 kg/m2) at age 18. Cut-points recommended by the World Health Organization (1995) were used for adults: overweight, BMI 25.0 to 29.9 kg/m2 and obesity, BMI ≥30.0 kg/m2.
The development of cut-points for waist circumference is complicated by methodological variation, that is, different levels at which the measurement is taken in various studies. Although the recommended level is midway between the iliac crest and the lowest rib (WHO, 2008), NHANES reference data (1999-2002 and 2003-2006) were based on measures taken at the uppermost lateral border of the iliac crest (McDowell et al., 2005, 2008). Corresponding reference values for Canadian youth were derived at the narrowest waist (Katzmarzyk et al., 2004). A report describing suggested percentiles for British youth indicates that waist circumference was measured midway between the tenth rib and the iliac crest, but later in the paper, the authors indicate it was measured at the “natural waist” (McCarthy et al., 2001). Wang and colleagues (2003) found that waist circumference estimates taken at different levels on adults are not comparable, especially among females. A systematic review of the adult literature, however, found that differences in the level of measurement did not have a considerable influence on the relationship between waist circumference and health outcomes (Ross et al., 2008).
Criterion-referenced cut-points for waist circumference have been established in adults (WHO, 2011). Although recommendations for cut-points have been developed for different samples, generally reflecting the 90th percentile by age and gender, standardized cut-points for youth have not yet been established. The committee recommends using the established percentiles for BMI to derive interim cut-points until more studies are conducted to determine health-related cut-points in youth. The interim cut-points could be verified using the corresponding percentiles for the concurrent relationship to health in adults.
Body composition can influence performance on some physical fitness tests and is also a health-related risk factor associated with physical fitness. The committee operationally defined body composition as a component of fitness, a marker of health, and a modifier of fitness for the purposes of this report. Given its well-known central role in both fitness and health, body composition should be included in a survey of youth fitness and measured across the life span.
The committee’s recommendations with respect to body composition are premised on the committee’s intention that the test administrators will have the necessary knowledge and training in test protocols and interpretation of results. The committee recommends inclusion of the following anthropometric measurements in a youth fitness test battery: (1) height and
weight for the derivation of BMI, (2) waist circumference, and (3) triceps and subscapular skinfold thicknesses. Height also serves as an indicator of linear growth status. (See Annex 4-1 for common examples of measurement techniques.)
The committee concluded that the above three measures of body composition are important to collect in a national youth fitness survey for several reasons. First, each measure is a proximal estimation of body fat and has increased standard of error of over laboratory measures. Also, there is consensus that the measurement of body composition is multidimensional (Bouchard et al., 1994). Second, no single measure is considered the gold standard and representative of all body composition tenets for children of all morphologies: BMI is a marker of obesity, waist circumference is a marker of abdominal adiposity, and skinfold thicknesses are a measure of subcutaneous fat. The measures recommended have acceptable validity and reliability.
To interpret the findings of body composition testing and determine whether individuals or populations are at risk of negative health outcomes, the committee recommends employing two approaches. For BMI, the CDC’s current established cut-points for underweight, overweight, and obesity should be applied. Interim cut-points for the waist circumference and skinfold measures should be set at levels that are analogous to those currently being applied by the CDC for BMI. This approach should be used until the necessary evidence becomes available to support establishing waist circumference and skinfold cut-points by associating those measures with cardiometabolic risk factors. The committee’s full recommendation for including body composition in a national youth fitness survey is presented in Chapter 8.
When body composition is measured in schools and other educational settings, important concerns arise related to the measurement of waist circumference and skinfolds. Therefore, the committee recommends that only BMI be used in these settings. A full description of considerations and the committee’s recommendation for schools and other educational settings is included in Chapter 9.
Body composition measurements should be taken by trained individuals using established techniques. Error—the discrepancy between a measured value and its true quantity—is inherent in anthropometry. It can be random3 or systematic.4
Replicate measurements of the same subject are used to estimate variability or error. Replicates on the same individual are taken independently by the same technician after a period of time has elapsed (intraobserver) or are taken on the same individual by two different technicians (interobserver). Replicate measurements provide an estimate of imprecision. The technical error of measurement is a widely used measure of replicability (Malina et al., 1973; Mueller and Martorell, 1988). Technical errors are reported in the units of the specific measurement. Intra- and interobserver technical errors for a variety of dimensions in national surveys and several more local studies are summarized by Malina (1995).
Accuracy is another aspect of the measurement process. It refers to how closely measurements taken by one or several technicians approximate the “true” measurement. Accuracy ordinarily is assessed by comparing measurements taken by technicians with those obtained by a well-trained or “criterion” anthropometrist (the reference). Note, however, that well-trained, expert anthropometrists do make errors.
The height, weight, waist circumference, and triceps and subscapular skinfold measurement techniques described below are provided as examples from the commonly used NHANES Anthropometry Procedures Manual.5
Stature and Weight
Stature, or standing height, is the linear distance from the floor or standing surface to the top (vertex) of the skull. It is measured to the nearest millimeter with the subject in standard erect posture, without shoes.
3Random error is associated with variation within and among individuals in measurement technique, problems with the measuring instruments (e.g., variation in or even lack of calibration or random variation in manufacture), and errors in recording. Random error is nondirectional, i.e., above or below the true dimension. Random errors tend to cancel each other out in large-scale surveys and ordinarily are not a major concern.
4Systematic error results from the tendency of a technician or a measuring instrument to consistently under- or overmeasure a dimension. Such error is directional and introduces bias. Measurement variability also is associated with the individual (e.g., normal variation in physiology, temperament, cooperativeness, and stranger anxiety).
5Available at http://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf (accessed May 10, 2012).
Body weight is a measure of body mass. It is measured to the nearest 100 grams (depending on the type of scale) with the individual attired in ordinary, light, indoor clothing without shoes (e.g., gym shorts and a t-shirt). It assumed that the scales would be calibrated regularly for a national survey. Height and weight are used to derive body mass index (BMI) (kg/m2).
The protocol for waist circumference calls for measuring just above the uppermost lateral border of the right illium after normal expiration. The level should be marked on the skin. When the tape is applied, it should make contact with the skin without indenting it. The measurement should not be made over clothing. Two individuals may be needed, especially for some overweight and obese individuals.
A skinfold thickness is a double fold of skin and underlying soft tissue at a specific site. Skinfolds are measured to the nearest 0.5 mm (some calipers measure to the nearest millimeter, while others measure to the nearest 0.2 mm). Three measurements usually are taken for each skinfold (some protocols recommend two).
Triceps skinfold is measured on the back of the arm (over the triceps muscle) at the level midway between the lateral border of the acromial process of the scapula (acromion) and the inferior border of the olecranon process of the ulna. With the arm flexed to 90 degrees at the elbow, the acromion is marked. A measuring tape is placed on the acromion (zero marker) and run down the lateral side of the upper arm. The distance midway between the acromion and the olecranon is marked and extended to the back of the arm. The skinfold is measured with the arm hanging relaxed (loosely) at the side by grasping a vertical fold about 1 cm above the mark, with the caliper being placed at the level of the mark.
Subscapular skinfold is measured 1 cm below the tip (inferior angle) of the scapula. The measurement site should be marked on the skin. The skinfold should follow the natural anatomical (cleavage) lines of the skin. It is not a vertical fold like that taken over the triceps.
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