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Fitness Measures and Health Outcomes in Youth (2012)

Chapter: 3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth

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Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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3


Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth

This chapter describes the methodology followed by the committee in reaching conclusions and making recommendations on the most appropriate health-related physical fitness test items for youth. Before reviewing the scientific literature, the committee developed a conceptual framework to illustrate its thinking on the theoretical associations among the various components of fitness, their modifiers, and relevant health markers. The chapter begins by describing this framework. It then describes the committee’s approach to the selection of test items for each of the four fitness components—body composition, cardiorespiratory endurance, musculoskeletal fitness, and flexibility. Included is a description of the literature review and the set of criteria that guided the selection process. The next section examines potential modifiers of fitness or of the associations between fitness and health, examples of which are included in the committee’s conceptual framework. Just as the extent of the evidence on the association of each fitness component and test item with health markers varies, so, too, does the evidence for the effect of potential modifying factors. In general, there is more evidence on the importance of gender and age, while less is known about the effect of developmental maturity, motor skill, and practice. Similarly, there is a dearth of information about the influence of some demographic factors, such as ethnicity and race or socioeconomic status, on performance on fitness tests and its interaction with health markers. The final section of the chapter presents the committee’s guidance for establishing cut-points (cutoff scores) for use in interpreting the results of youth fitness tests. Interpretation of test results is one of the

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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most crucial aspects of such testing because it serves as a way of communicating with participants, health and school officials, and parents about their risk of negative health outcomes based on test performances.

CONCEPTUAL FRAMEWORK

To illustrate the overall challenge of its task and create a model for physical fitness measures that are most clearly associated with health outcomes in youth, the committee developed a conceptual framework (Figure 3-1). This framework guided the committee’s analysis of research findings. Figure 3-1 depicts the potential relationships between physical fitness components—which can be measured by a variety of fitness test items represented by the smaller embedded boxes—and markers of health.

As illustrated in Figure 3-1, these relationships can be affected by both modifying factors and risk factors. As defined by the committee, modifying factors are those that can independently affect an individual’s level of fitness. They include both factors that are measurable in the field (e.g., gender, race, ethnicity, maturity) and those that are not (e.g., heredity, practice level, skill level). Likewise, health outcomes are modified by certain risk factors that characterize an individual (e.g., low HDL cholesterol is a risk factor for cardiovascular disease). In the case of youth, health outcomes (i.e., diseases or conditions) are defined in terms of health markers or risk factors since youth are unlikely to experience a disease or condition (e.g., heart disease) as a result of their fitness level. The potential health outcomes that result from a specified level of performance on a fitness test are depicted within five categories: four categories of (positive or negative) markers of health-related outcomes (i.e., cardiovascular/respiratory health, metabolic health and obesity, mental and cognitive health, and musculoskeletal health) and a category that includes adverse events. Note that in this report, the terms health marker and health risk factor are used in a broad sense and interchangeably to refer to indicators of health outcomes.

The committee included body composition as a component of fitness, even though perspectives on this categorization vary. Body composition is also considered a modifier of performance on fitness tests and a health marker. Thus, it appears in all three categories of variables in the framework—fitness components, modifying factors, and health markers—and is highlighted in a different color from that of the other fitness components because of this unique nature.

The next section describes the approach used by the committee to select the best youth fitness test items, considering (1) the strength of their association with health markers in youth, (2) their integrity (validity and reliability), and (3) the relative feasibility of their administration in the field.

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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image

Figure 3-1 Physical fitness measures and health outcomes: Conceptual framework.

NOTE: The variety of fitness tests that can measure a particular fitness component is represented by the embedded boxes under each component.

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

SELECTION OF APPROPRIATE FITNESS TEST ITEMS

Review of the Literature

The committee used various resources to collect scientific data to inform its selection of fitness test items. A main source of information for the committee was a systematic review of the literature conducted by the Centers for Disease Control and Prevention (CDC). The CDC search criteria and vocabulary are described in Box 3-1. The committee supplemented this systematic search with selected publications based on the members’ knowledge of the scientific literature.

For the purposes of its review, the CDC defined health as a “human condition with physical, social, and psychological dimensions, each characterized as a continuum with positive (i.e., the absence of disease, along with a capacity to enjoy life and withstand its challenges) and negative (i.e., illness and premature death) aspects.” The CDC defined health-related fitness as the fitness components that have an association with health-related outcomes and are typically identified as aerobic fitness (i.e., cardiorespiratory endurance), muscular strength, muscular endurance, body composition, flexibility, and balance. Only the literature on cardiorespiratory endurance, muscle strength, and muscle endurance was examined systematically, further selected based on the inclusion/exclusion criteria presented in Box 3-1, and abstracted (only experimental and longitudinal studies were abstracted). The CDC considered that the relationship between body composition and health outcomes is well established and therefore conducted a systematic review of it only as a health outcome. Although the CDC performed a systematic search for flexibility, the articles on this component were not abstracted because of limited time and resources. When studies addressing cardiorespiratory endurance or musculoskeletal strength or endurance also included flexibility as a fitness component, however, the CDC abstracted such information. A breakdown of the total number of studies that satisfied the CDC search criteria in Box 3-1 and were abstracted is as follows:

  • Cardiorespiratory endurance: 47 experimental, 29 quasi-experimental, 35 experimental (no control), 24 longitudinal
  • Musculoskeletal strength: 23 experimental, 12 quasi-experimental, 22 experimental (no control), 6 longitudinal
  • Musculoskeletal endurance: 12 experimental, 6 quasi-experimental, 15 experimental (no control), 5 longitudinal
  • Flexibility: 7 experimental, 5 quasi-experimental, 9 experimental (no control), 4 longitudinal
Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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Identification and Selection of Test Items

The committee followed the criteria listed in Box 3-2 in a stepwise fashion to select test items for the various components of fitness. Although the search for studies on tests measuring musculoskeletal strength and endurance was conducted separately by the CDC, the committee discusses those tests in Chapter 6 since they all measure dimensions of the same component, musculoskeletal fitness. As Box 3-2 shows, the committee applied five broad criteria in filtering and selecting the best test items for each fitness component: (1) the test item has been described and is currently being utilized; (2) the quality of the research of individual studies showing the relationship between a test item and a health marker is high; (3) based on all the evidence, there is an association between performance on the test item and one or more health markers; (4) the test item has adequate integrity (validity and reliability); and (5) administering the test item in the field is feasible.

The selection of high-quality studies for cardiovascular endurance, musculoskeletal fitness, and flexibility test items was based on the following criteria: (1) study design (e.g., randomized controlled trials versus longitudinal studies), (2) representativeness of the population (e.g., age range), (3) freedom from bias, (4) sample size, (5) validity of health markers, (6) adequacy of description of the intervention, (7) relationship between performance on the test item and one or more health markers, (8) statistical rigor, and (9) adjustment for confounders. Limitations of the scientific literature with regard to these criteria are described in the chapters on the fitness components that were assessed for their relationship to health in youth (Chapters 5, 6, and 7).

Attempting to find associations between performance on fitness tests and health in youth entails important limitations that can help in understanding the committee’s approach to reviewing the evidence. In addition to challenges inherent in using field-based (as opposed to laboratory-based) fitness tests, two important challenges arise in analyzing associations between fitness performance and health in youth. First, health constructs in youth are not as well defined as they are in adults; for example, there are questions about whether elevated blood pressure in youth is directly associated with a poor health outcome. Second, diseases that typically are related to low levels of fitness in adults are found with low frequency in youth; therefore, finding an association between performance on fitness tests and health in youth is not highly probable, particularly in studies with small sample sizes. Consequently, studies that investigate the association between performance on a fitness test and health in youth often use health markers rather than health outcomes as health variables. Finding health markers with good ability to predict a future negative health outcome is in itself difficult. Although biological significance and strength of association are typical

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

BOX 3-1
CDC Literature Search: Criteria and Vocabulary

Literature Databases Searched

  • CINAHL
  • Sport Discus
  • Embase
  • Medline
  • PsychINFO
  • Pubmed
  • Web of Knowledge
  • Web of Science
  • ProQuest
  • PsyInfo

Inclusion/Exclusion Criteria

  • Peer-reviewed original research
  • At least one fitness measure and at least one health measure
  • No minimum sample size
  • All study designs
  • English language
  • Population aged 5-18, healthy, obese and nonobese, sedentary and athletic
  • Publication date: January 2000-December 2010
  • Exclusions: congenital diseases, disabilities (e.g., cerebral palsy, cystic fibrosis, heart abnormalities, motor deficits)

Search Vocabulary for Fitness Measures

Aerobic capacity: aerobic capacity, cardiorespiratory fitness, cardiovascular health, exercise tolerance, endurance capacity, maximum oxygen uptake, oxygen consumption, endurance training, aerobic exercise

Flexibility: range of motion (articular), joint flexibility, range of motion, joint range of motion, motor skills, motor fitness, sit-and-reach, fitnessgram, fitness gram, muscle stretching exercises, hamstring flexibility, low-back flexibility

criteria applied in reviewing scientific evidence, the above challenges led the committee to consider as evidence any significant positive association reported in a high-quality study. The strength of the association between

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

Muscular endurance: exercise test, fitnessgram, fitness gram, bicep curl, curl-up, pull-up, sit-up, muscle endurance, muscular endurance, physical exertion

Muscular strength: climb, stairs, fitness centers, strength training, resistance training, weight lifting, gymnastics, tree climbing, rope climbing, rock climbing, calisthenics, muscle strength

Search Vocabulary for Health Outcomes

Body composition/obesity/diabetes: obesity, overweight, adiposity, body weight, body mass index, abdominal fat, adipose tissue, glucose metabolism disorders

Cancer: neoplasms

Cardiovascular/pulmonary: cardiovascular diseases, cardiovascular system, cerebrovascular disorders, cardiac function, respiratory tract diseases, chronic obstructive pulmonary disease, lung diseases (obstructive), respiratory function tests, lung function, asthma, cardiovascular risk, bronchoconstriction

Cognitive/neurological: mental health, anxiety, depression, sleep disorders, cognition, memory, attention, dementia, stress (psychological), anger, self concept, Parkinson’s disease, multiple sclerosis, amyotrophic lateral sclerosis, attention deficit disorder with hyperactivity, pain, gait, gait disorders (neurologic)

Skeletal/muscular/connective: osteoporosis, calcification (physiologic), muscular atrophy, fat-free mass, arthritis, bone and bones, bone density, bone mineral density, scoliosis, rhabdomyolysis

Miscellaneous: risk, injury risk, functional health

a test item and a health marker was categorized as sufficient when most high-quality studies showed a significant association between the test results and a specific health outcome or marker.

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

BOX 3-2
Stepwise Application of Criteria for Selection of Fitness Test Items

Phase 1: Identification of fitness test items for consideration

  • Step 1. Review fitness test batteries currently used (those listed in Table 2-6 in Chapter 2 and other sources).
  • Step 2. Identify appropriate test items for each fitness component.
  • Step 3. If appropriate and feasible, add test items identified through sources other than the CDC literature search.

Phase 2: Summary of relationship of fitness components to health outcomes

  • Step 1. Review and summarize the literature that establishes a link between each fitness component and health outcomes.

Phase 3: Evaluation of relationship of fitness test items to health markers in youth

  • Step 1. Review technical reports from currently used fitness tests and consider literature referenced in those reports, especially as it relates to health markers and the integrity of the fitness test items.
  • Step 2. Review the CDC literature (and additional sources).
  • Step 3. Evaluate the quality of the research of each study; select publications based on the quality of the research.
  • Step 4. Based on all the evidence, identify health-related test items that qualify for further review in Phases 4 and 5.

Phase 4: Evaluation of integrity of test items (i.e., validity and reliability)

  • Step 1. Review the relevant literature on validity and reliability.
  • Step 2. Identify the best test items (based on their association with health markers as identified in Phase 3 and on their integrity).

The committee deliberated at length on the issue of considering studies in adults to draw conclusions about the associations between fitness in youth and health outcomes. The committee also discussed the inclusion of studies exploring the relationship between meeting a level of fitness early in life and specific health outcomes as an adult. The committee concluded

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

Phase 5. Evaluation of administrative feasibility of test items

  • Step 1. Review the relevant literature.
  • Step 2. Complete a scorecard for the test items resulting from Phase 4 using the following list of questions:
    • Can the item be conducted in a timely and efficient manner?
    • Does the item impose an acceptable preparation burden on participants?
    • Does the item impose an acceptable preparation burden on administrators?
    • Is the item relatively free of motivational or self-esteem influence?
    • Is the test item free of interpretation misuse?
    • Can it be administered with acceptable privacy?
    • Can it be administered with minimal equipment and space?
    • Is (interpretation of) performance on the item independent of reading comprehension by the participant, socioeconomic status, and age bias?
    • Is performance on the item independent of familiarity with the item?
    • Is performance on the item relatively independent of prior practice?
  • Step 3. Assess the test items using the scorecard, considering whether they will be implemented in a national survey or in schools or other educational settings.

Phase 6. Formulation of conclusions and recommendations on appropriate fitness test items for youth.

that the assumptions entailed in extrapolating studies in adults to youth are sometimes uncertain, and therefore decided not to include such studies as the main or sole evidence of an association of a test item with health in youth but only as supportive evidence. In addition, because the literature search was limited to health in youth and prospective studies did not cover

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

the length of time until youth reach adulthood, studies of the long-term consequences of fitness (i.e., whether reaching a specific fitness level as a youth would result in health consequences as an adult) were considered only as secondary evidence in identifying fitness test items that are associated with health in youth. However, the committee understands the importance of assessing how well a health marker tracks into adulthood and identifying appropriate health markers in youth and makes recommendations to this effect.

The approach used to select appropriate test items for body composition differed. As noted earlier, the relationships between body composition, particularly percent body fat, and health outcomes are well established in both youth and adults. For this reason, the CDC did not provide the committee with a systematic review of literature demonstrating the relationship between test items for body composition and health outcomes. Therefore, to identify appropriate test items for body composition, the committee selected field-based items that were valid, reliable, and feasible for either a national survey or an educational setting.

CONSIDERATION OF MODIFYING FACTORS

Gender and age often are analyzed as confounders or effect modifiers in research studies, and gender- and age-specific cut-points have been set for fitness test items. There are, however, other factors that may modify performance on fitness test items or the association between an item and health but are not routinely included in surveys of youth fitness or in study designs.

For some modifiers (e.g., gender, age, race/ethnicity, body composition, maturation status, motor skill), evidence for their influence on specific fitness test items varies in quality (see, for example, Chapter 4 on the influence of body composition on fitness tests). In the studies reviewed, insufficient data were available with which to assess the influence of several potential modifiers—gender, age, race/ethnicity, body composition, maturation status, motor skill—on performance on cardiorespiratory endurance, musculoskeletal fitness, and flexibility tests. When these modifiers were considered in the designs of the studies reviewed, the committee comments on the results in the respective chapters (Chapters 5-7).

The committee recommends including measures of some of these factors in surveys and study designs to gain a better understanding of their influence. As more research is undertaken and survey data are collected, it may be appropriate to establish cut-points based on selected modifiers, but at this time the committee recommends that only age- and gender-based cut-points be established (see Chapter 8). Age- and gender-based cut-points, however,

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

need to be interpreted in the context of other potential modifiers (e.g., body composition, demographic characteristics). For that reason, the committee highlights the importance of training those who will be interpreting and communicating results (see Chapters 8 and 9). An important aspect of this training is learning to be cognizant of the influence of modifying factors.

The following is a summary of what is known about the potential effects of maturation status, motor skill, and demographic factors (race/ethnicity, socioeconomic factors) on fitness performance. Although body composition is also categorized as a modifying factor in the committee’s framework, a summary of what is known about the influence of selected elements of body composition on fitness performance is included in Chapter 4 and is not repeated here. The committee’s recommendations for including some of these factors in national surveys and research study designs can be found in Chapters 8 and 10, respectively.

Maturation Status

The literature review revealed extensive documentation of changes in fitness with age per se (Branta et al., 1984; Carron and Bailey, 1974; Ellis et al., 1975; Espenschade, 1960; Froberg and Lammert, 1996; Haubenstricker and Seefeldt, 1986; Keogh, 1965; Malina and Roche, 1983; Malina et al., 2004; Mizuno et al., 1973; Ostyn et al., 1980; Simons et al., 1990) and with individual differences in maturity status within a given age group (Espenschade, 1940; Jones, 1949; Little et al., 1997; Malina et al., 2004). This effect may be due in part to differentials in the timing of maturation. There are two indicators of this timing: age at menarche and age at peak height velocity (a measure of the maximum rate of growth in stature during a growth spurt) (Malina et al., 2004). Several measures of physical fitness have their own spurts, which have been documented more in boys than in girls (Beunen and Malina, 1988; Beunen et al., 1988; Carron and Bailey, 1974; Heras Yague and de la Fuente, 1998; Kemper and Verschuur, 1985; Mirwald and Bailey, 1986). Variation in fitness among youth has been classified as late, on time (average), or early in skeletal age, age at menarche, and timing of peak height velocity (Jones, 1949; Lefevre et al., 1990; Little et al., 1997; Malina et al., 2004). Differences in maturity are more marked for boys than for girls, although relevant data are not as extensive for girls (Malina et al., 2004). While evidence suggests a relationship between maturity stages per se and performance on fitness tests, some questions remain to be answered—in contrast to the influence of body size and/or body composition on fitness, which is affected independently by individual differences in maturation (Malina et al., 2004). The following four methods can be used to measure maturity.

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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Skeletal Age

Skeletal age indicates the level of skeletal maturity of the hand-wrist attained at a given point in time and can be measured from infancy through adolescence. Three measurement methods are commonly used: the Greulich-Pyle and Fels methods, based on American children, and the Tanner-Whitehouse method, based on British children. Measurement of skeletal age requires a small radiation dose and expertise in assessing films (Beunen et al., 2006; Malina, 2011; Malina et al., 2004).

Secondary Sex Characteristics

Secondary sex characteristics include pubic hair and genitalia in boys, and breasts and pubic hair in girls. Privacy and cultural issues arise with this measure, although self-assessments increasingly are being used. Use of this measure also is limited to the pubertal period. The criteria described by Tanner (1962) are most commonly used, whereby secondary sex characteristics are rated on five discrete-point scales (stages from prepubertal to mature status) superimposed upon a continuous process of sexual maturation. It is important to recognize that youth should not be grouped by developmental stage across chronological ages (Beunen et al., 2006; Malina et al., 2004). Moreover, there are differences among white, African American, and Mexican American youth, with African Americans beginning pubertal maturation in advance of their Mexican American and white counterparts (Chumlea et al., 2003; Sun et al., 2002, 2005).

Age at menarche and menarcheal status are an indicator of maturity in girls. As with pubertal stages, girls should be grouped by menarcheal status within each chronological age year (Malina et al., 2004).

Somatic Maturation

Somatic maturation is an after-the-fact indicator. It is defined as the age at the maximum rate of growth in height during the adolescent spurt (peak height velocity) and is an indicator of maturity timing. Estimation of age at peak height velocity requires longitudinal data spanning at least 5-6 years around the spurt (Beunen and Malina, 1988; Beunen et al., 2006; Malina et al., 2004).

Noninvasive Indicators

Two indicators of maturity status considered noninvasive have recently been used: (1) percentage of predicted mature (adult) height attained at a given age (Roche et al., 1983), and (2) maturity offset or predicted time

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

before or after peak height velocity (Mirwald et al., 2002). The former is an indicator of status, while the latter is an indicator of timing.

The most accurate prediction equations for mature height require the age, height, and weight of the child and midparent height (i.e., the average of the parents’ height). The prediction equations for maturity offset require age, height, weight, sitting height, and estimated leg length (height minus sitting height, technically subischial length) (Mirwald et al., 2002). Limitations of this measure are that it requires an additional measurement and a flat sitting surface and the fact that ethnic variation is a potential confounder (Hamill et al., 1973; Malina et al., 1974, 1986, 1987; Martorell et al., 1988). It should also be noted that leg length has its adolescent growth spurt before sitting height (Malina et al., 2004).

Although the above measures have been used to assess various populations of athletes (Cumming et al., 2006; Malina et al., 2005; Nurmi-Lawton et al., 2004; Sherar et al., 2007), they have not been applied and validated in large samples of youth (Malina et al., 2012).

Motor Skill

The association between motor skill (i.e., motor coordination and control) development and health-related fitness performance and health outcomes has not been thoroughly investigated. However, a growing body of cross-sectional and longitudinal evidence demonstrates positive relationships between motor skill competence levels and multiple aspects of health-related fitness in youth. Given the lack of experimental data, the literature does not provide adequate support for a recommendation to include a motor skill measure in a national youth fitness test battery. Further research is needed to examine the relationships between the development of motor skill and health-related fitness performance and health outcomes.

Motor Skill and Health-Related Fitness Performance

Children do not develop motor skill through maturation alone, but also through context-specific engagement in physical activity (Logan et al., 2011; Stodden et al., 2008). Successful technical completion of multijoint motor skill and fitness tests is promoted through practice and experience, and also is linked to a child’s maturation status. Therefore, it is logical to consider the potential influence of an individual’s motor skill status on the performance of tasks involving coordinated movements. Without intervention or formal instruction, such as physical education, youth with lower levels of motor coordination and control (i.e., low motor skill) are more likely to exhibit decreased performance on physical fitness tests (Cantell et al., 2008; Castelli and Erwin, 2007; Castelli and Valley,

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

2007; Erwin et al., 2007; Haga, 2009; Matvienko and Ahrabi-Fard, 2010; O’Beirne et al., 1994; Okely et al., 2001; Schott et al., 2007). However, the use of multiple types of motor skill assessments (i.e., process- and product-oriented assessments) (Fisher et al., 2005; McKenzie et al., 2002; Okely et al., 2001; Stodden et al., 2008) makes it difficult to compare relationships across studies and developmental time. Additionally, issues related to a lack of developmental validity, the sensitivity and skill-level discrimination capabilities of various assessments, and a lack of consensus on how motor skill versus health-related fitness is defined need to be addressed in future research (Fisher et al., 2005; McKenzie et al., 2002; Okely et al., 2001; Stodden et al., 2008).

Recently published data show highly variable correlation strengths (r = 0.00-0.74) between individual or composite product- or process-oriented motor skill assessments and individual health-related fitness measures in children, adolescents, and young adults, including both males and females (Anliker et al., 2011; Barnett et al., 2008a,b; Castelli and Valley, 2007; Castro-Piñero et al., 2010; Hands et al., 2009; Matvienko and Ahrabi-Fard, 2010; Okely et al., 2001; Tveter and Holm, 2010). Using multivariate regression, explained variance in either individual or composite measures of fitness by multiple individual or composite motor skill assessments has ranged from 0 to 79 percent (Barnett et al., 2008a,b; Hands, 2008; Stodden et al., 2009). With the exception of one quasi-experimental study (Matvienko and Ahrabi-Fard, 2010) and three longitudinal studies (Barnett et al., 2008a,b; Hands et al., 2009), these data were derived from cross-sectional study designs. Sample sizes varied from 230 to 2,026 in all studies except those of Matvienko and Ahrabi-Fard (2010) and Hands and colleagues (2009), which included only 90 and 19 subjects, respectively. It is important to note that the strength of relationships generally increases across age in both males and females. Relationships between various motor skills and flexibility generally are weaker (r = 0.01-0.25) than is the case for other aspects of health-related fitness performance.

Results of recent cross-sectional and longitudinal research examining associations between motor skill competence levels and body weight status (i.e., percent body fat and body mass index [BMI]), as either a component of fitness or a health outcome, indicate that motor skill competence is inversely correlated with body composition. As demonstrated with other aspects of health-related fitness, the strength of associations between motor skill competence and body weight status varies, but generally increases over time (r = 0.05-0.73) (Burgi et al., 2011; D’Hondt et al., 2009, 2011, 2012; Hands and Larkin, 2006; Lopes et al., 2011, 2012; Martins et al., 2010; Stodden et al., 2009). As body weight status may influence both motor skill and health-related fitness performance, it is difficult to identify a causal pathway for these relationships. Independent of a causal pathway,

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
×

however, these cross-sectional and longitudinal data indicate that youth with low motor skill competence have a higher risk of unhealthy trajectories not only for weight gain but also for physical activity and multiple aspects of health-related physical fitness (Barnett et al., 2009; Haga, 2009; Stodden et al., 2009). These data indirectly support the hypothesis of Stodden and colleagues (2008) that the development of motor skills may promote improvements in body weight status, physical activity, and health-related physical fitness through the dynamic and reciprocal relationships that occur among these variables across childhood. As mentioned previously, there is a need for long-term experimental studies to better understand the impact of motor skill development on body weight status and various aspects of health-related fitness.

It has been suggested that associations between cardiorespiratory endurance and fundamental motor skills are indirectly related to developmental trajectories of motor skill development, are reciprocal in nature (Barnett et al., 2008b, 2011; D’Hondt et al., 2011; Stodden et al., 2008), and may be sustained over time from childhood (Barnett et al., 2008b; Burgi et al., 2011; D’Hondt et al., 2011; Hands and Larkin, 2006; Martins et al., 2010). Associations between motor skill (i.e., motor control and coordination) performance and muscular strength and endurance performance are linked to direct mechanisms involving many aspects of neuromuscular adaptation (Enoka, 2002; Ratamess, 2008). This link supports the notion that motor skill development influences these variables (Myer et al., 2011; Stodden et al., 2008).

Although most of the data reported above were derived from correlational or prospective longitudinal studies, the increasing relationship strength trajectories between motor skill and fitness levels across ages suggest the need for additional research on the relationship trajectories between motor skill development and health outcomes. The committee could identify only a few studies examining the relationship between motor skill and any health outcomes.

Motor Skill and Health Outcomes

A small body of research (cross-sectional and longitudinal studies) indicates that low motor skill competence is associated with poor bone health in youth (Anliker et al., 2011; Vicente-Rodriguez et al., 2004, 2008). High-loading activities such as jumping and hopping, which integrate skill as well as strength and power attributes, have demonstrated strong relationships (r = 0.65-0.81) with site-specific lower-extremity bone mineral density in studies with 323 and 28 adolescents, respectively (Anliker et al., 2011; Vicente-Rodriguez et al., 2004). However, these relationships also can be attributed to lean mass (Anliker et al., 2011; Vicente-Rodríguez et al., 2008). Weaker associations have been demonstrated with other skill-related tests

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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(e.g., running, agility), as well as activities demanding specific sports skills (Vicente-Rodriguez et al., 2004). Overall, the proposed synergistic relationships and mechanisms involving skill development and muscle strength, power, and endurance make it difficult to delineate the contributions of skill, strength, and power to bone health (see Chapter 6 for a discussion of the relationship between musculoskeletal fitness and bone mineral density).

Even fewer studies have examined the relationship between any aspect of motor skill and cardiovascular or metabolic health outcomes in youth. In a cross-sectional study (N = 149), blood lipid profiles were weakly associated with motor skill (Cantell et al., 2008). One longitudinal study (N = 1,192) addressing cardiovascular health (Monyeki et al., 2008) showed no significant relationships between motor skill levels and blood pressure (systolic and diastolic).

In longitudinal and cross-sectional studies, relationships between aspects of motor skill competence and mental health outcomes generally range from weak to moderate (r = 0.10-0.68), depending on the nature of the behavior or disorder. Many of these studies, however, involved participants with mental or associated cognitive, motor, emotional, or behavioral developmental disorders (Emck et al., 2011; Piek et al., 2007, 2008, 2010; Skinner and Piek, 2001). Thus, these data may not be representative for normal populations of children.

Influence of Amount of Practice Time on Fitness Testing Performance

Evidence for the effects of practice on performance on specific health-related physical fitness tests (i.e., 1-mile run, 20-meter shuttle run, curl-ups) is lacking. The relevant literature on the relationship between motor learning and development and general skill learning indicates that adequate learning and completion of a fitness test depend on many factors, including experience, instruction, feedback, cognitive capabilities, motivation, and the complexity of the test (Farpour-Lambert and Blimkie, 2008; Raudsepp and Pall, 2006). In addition, factors associated with age, level of coordination and control, and body composition may affect the short-term capability to learn and perform a test (D’Hondt et al., 2011; Hands and Larkin, 2006; Lloyd et al., 2003).

Race/Ethnicity and Socioeconomic Factors

The associations among race/ethnicity, gender, socioeconomic status, and health outcomes are well established (Baker et al., 2006; CDC, 2011; Floyd et al., 2009; Miech et al., 2006; National Center for Health Statistics, 2011; Whitt-Glover et al., 2009). The known presence of health dis-

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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parities by race/ethnicity and socioeconomic status highlights the potential importance of understanding the effects of these factors on fitness performance. Race/ethnicity and socioeconomic status have been identified as potential modifiers of test performance and interpretation, but their role is unknown and should be further investigated and included in surveys. For example, although the committee found no evidence to support the influence of socioeconomic status on test selection, delivery, or interpretation, one could hypothesize possible limitations due to lack of equipment if a school had a suboptimal built environment (e.g., having no outdoor track would limit the options for cardiorespiratory fitness tests). Measurement of race/ethnicity and socioeconomic status in research studies and surveys has become increasingly common as (1) social demography has expanded as a scholarly enterprise, (2) the U.S. population has become more diverse, and (3) evidence of the scientific relevance of demographic characteristics to human development and health outcomes has become more widely known (Entwisle and Astone, 1994).

The committee’s review included some studies that describe the population in terms of ethnic and racial background; often, however, no statistical analysis of the effects of these factors was carried out. One exception is the case of body composition, where the differences associated with race/ethnicity and socioeconomic status are well established. Previous youth fitness surveys in the United States have failed to consider these factors (see Malina, 2007).

Previous studies have typically used self-report, parent questionnaires, information taken from existing records, or assignment by a field worker to assess race/ethnicity among youth (Entwisle and Astone, 1994). A more appropriate method of assessing race/ethnicity in surveys and research would be the data collection standard for race and ethnicity developed by the Office of Management and Budget (OMB, 1997), which federal programs have been required to follow since 2003.

Previous studies have used proxy measures to collect information on socioeconomic status from youth themselves, such as the number of books or cars the family owns, parental education or occupation, and the number of rooms in the household.1 However, this method is potentially problematic and could have different implications for different parts of the country (e.g., children living in areas where public transportation is easily available and preferred, such as New York City, may not live in households with cars, and increased access to electronic books may mean children are not actually aware of the number of books the family owns). A better way to

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1Available at http://www2.lse.ac.uk/media@lse/research/EUKidsOnline/BestPracticeGuide/FAQ26.aspx (accessed August 27, 2012).

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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collect information on socioeconomic status would be a questionnaire to parents (Entwisle and Astone, 1994; Merola, 2005) at the time they are asked to provide consent for their children to participate in fitness testing. If collecting this information directly from parents is not feasible, it may be estimated from official school-level statistics, such as percentage of students eligible for free or reduced-price lunch (Merola, 2005).

Disability

The information in this report is driven by the evidence for healthy study populations and directed to the general population. However, the committee recognizes the significance of physical fitness for the health of youth with various disabilities (as defined in Appendix B), especially since they are likely to be less active than their nondisabled peers (Physical Activity Guidelines Advisory Committee, 2008). Other reviews, such as the report of the Physical Activity Guidelines Advisory Committee (2008), specifically examine the relationship between health outcomes and physical activity in people with disabilities (see also Seaman, 1999). More information on including youth with disabilities in school-based fitness testing is presented in Chapter 9.

ESTABLISHMENT OF CUT-POINTS FOR HEALTH-RELATED YOUTH FITNESS TESTS

As noted earlier, interpretation of the results of health-related fitness testing is one of the most important aspects of such testing, making the setting of cut-points essential. Cut-points serve as a way of discerning between individuals and populations that may be at risk of poor health outcomes based on performance on a fitness test and those that are not. For example, a 10-year-old boy with a BMI above 22 would be considered at increased risk of poor health. Cut-points thus are tools for communicating with participants, families, health and school officials, and the public in general about fitness status and setting goals for improvement.

Many challenges are entailed in setting and interpreting these cut-points (or standards). An important challenge, alluded to earlier, is the fact that most health outcomes can take years to develop, and there is no concurrent relationship between fitness test performance and any actual health outcomes in youth. In light of this challenge, the committee adopted the term health marker (or health risk factor) instead of health outcome. This was done with the assumption that those health markers are associated with a risk of a future health outcome. Another challenge is that, although the fitness and health variables are often continuous (i.e., a continuous improvement in fitness would be related to a continuous improvement in

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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health), for communication purposes, evaluation standards frequently are established as a discrete variable (e.g., meets or does not meet the standard). The results can still be presented as part of a continuous distribution to convey the concept that health is a continuous variable, and any improvement in fitness will likely be associated with a lower risk of negative health outcomes.

This section describes two evaluation approaches commonly used in setting health-related youth fitness standards—norm- and criterion-referenced (Safrit and Wood, 1989). It then presents the committee’s guidance on methods for establishing standards for health-related youth fitness testing based on the available evidence.

Norm-Referenced Versus Criterion-Referenced Evaluation

Norm-Referenced Setting of Cut-Points and Evaluation of Fitness

In the norm-referenced evaluation approach, a test taker’s performance is compared with that of his/her peers, often by gender and age. For example, students might be categorized depending on whether they score below, equal to, or higher than the 85th percentile of their peers. When the interest is in performance (e.g., strength of an individual’s upper body), norm-referenced evaluation is appropriate. Computing and deriving norms (e.g., percentiles) is relatively simple as long as data from a nationally representative sample exist and can be updated. The following are four important limitations associated with this norm-referenced evaluation approach to setting cut-points:

  • Time dependence—Population distributions, and therefore norm-referenced values, change with time. Updating these values is costly in terms of both time and human resources, but is necessary to avoid misleading results.
  • Population dependence—The interpretation depends on the fitness of the reference population. If a population is abnormally healthy or unhealthy, the comparisons with an individual fitness level (e.g., better than average) will not be meaningful.
  • Discouraging unfit youth—The use of a norm-referenced approach tends to reward youth who are already fit while potentially discouraging those who are not fit because they know their chances of achieving the standard are low.
  • Favoring genetically talented or punishing disadvantaged youth—Standards based on the norm-referenced approach often are set at the high end of a population and thus may favor genetically talented or punish disadvantaged youth.
Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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Criterion-Referenced Setting of Cut-Points and Evaluation of Fitness

Most of the limitations listed above are overcome with a criterion-referenced evaluation approach, whereby a test taker’s performance is compared with an absolute criterion related to whether a child meets a minimal necessary physical fitness level. In contrast with the norm-referenced approach, because the criterion is defined independently, it is not impacted by changes in a population that occur over time or in the level of fitness of a specific population. Limitations related to genetic differences or the potential for discouraging unfit participants also can be minimized with this approach.

Many methods have been developed for setting performance standards (Cizek, 2001; Livingston and Zieky, 1982), but for criterion-referenced evaluation of health-related fitness, the health outcome–centered method (Zhu et al., 2011) has predominated. Basically, this method involves linking health-related fitness performance with a particular (set of) health outcome measure(s). Specifically, this approach identifies a level of test performance that discriminates, with acceptable specificity and sensitivity, between participants who have and do not have a defined health characteristic. An example is identifying a level of performance on a measure of cardiorespiratory endurance that discriminates between groups of youth who have or do not have an at-risk score for metabolic syndrome.

Steps completed before developing cut-points for the health-outcome centered method include determining the components of health-related fitness (e.g., cardiorespiratory endurance) and selecting valid, reliable criterion measures and field tests and health outcomes or markers. Field tests are selected because even though criterion measures (criterion-referenced standards) are the most accurate measure of a construct, they often are more expensive and time-consuming and require sophisticated equipment. Field tests are more practical, less costly, and less time-consuming for mass testing. It is important, however, to determine the validity and reliability of field tests by deriving the predictive relationship and determining its consistency with the selected criterion measure.

The selection of health outcomes can be based on the expected relationship between field tests and health markers or outcomes. Health is a construct, so there are many possible health outcome measures, such as mortality, a single risk factor (e.g., blood pressure), or a group of risk factors (e.g., metabolic syndrome). Because no specific measure is considered superior, it is advisable to use multiple outcome measures to validate the test results when possible. Those selecting cut-points also need to identify health outcome measures using existing standards (e.g., a systolic blood pressure level of ≥103 mmHg for a 5-year-old child 104 cm in height) and make adjustments for specific populations if needed.

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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Guidance for Establishing Cut-Points for Youth Fitness Tests

As mentioned above, setting cut-points for evaluating results of health-related fitness tests entails a number of challenges, one of which is the lack of appropriate data. Ideally, cut-points are established from data on performance on a specific fitness test and health outcomes in a broad-based youth population. More often, however, these data are not available; instead, there may be enough data on an association with health in the adult population but only growing evidence from studies in small samples of the youth population. In yet a different scenario, only growing evidence for an association between a specific test and health exists, with no data coming from broad populations. Until data in broad youth populations are generated so cut-points can be derived, cut-points should be referred to as interim criterion-referenced cut-points (or interim cut-points). Various approaches can be used to select these interim criterion-referenced cut-points, depending on the available data. The committee’s guidance on these approaches is presented in this section. Often a number of field tests are used simultaneously to measure the same fitness component. The reader is referred to Zhu et al. (2010) and Jackson (1989) for information on setting cut-points for multiple tests of a single component.

Several considerations apply in interpreting the results of fitness tests. For health-related fitness testing in youth, the key interest is not only whether a test taker is “fit enough” to be free of potential health risks but also whether the test taker is “fit enough for the future.” In addition, because the key outcome of interest of the criterion-referenced approach to evaluating test results is classification (e.g., being at risk of a health outcome versus not being at risk), the accuracy of the classification is key. Further, regardless of how well the related cut-point is established, it will be possible to misclassify individuals. There are two kinds of misclassification: (1) when a fit test taker is misclassified as unfit and (2) when an unfit test taker is misclassified as fit. The committee considered the first of these to be more problematic because it would result in a greater likelihood of recommending an exercise intervention to youth who do not need it, thereby depleting already limited resources that should be used for youth who need them the most. To minimize the effects of misclassification, cut-points need to be validated or cross-validated using additional measures and samples.

Finally, whether cut-points should be established differently for various subpopulations must be examined and determined empirically. As discussed earlier, while age and gender often have been taken into consideration in setting cut-points, many other factors, such as race/ethnicity, maturation status, and disability, have not been considered.

Once cut-points have been established for a specific test and age/gender group, they should be used in interpreting test results and communicating

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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with participants, families, school and health officials, and the general public. Doing so will minimize the confusion that might arise from communicating in terms of the percentiles used to derive the cut-points. For example, the CDC has used the 95th percentile from a previous decade to derive cut-points for obesity in children, yet more than 15 percent of youth currently exceed that 95th percentile. These are challenging issues to communicate. In cases where percentiles may allow for a clearer presentation of the results than cut-points, as with BMI, the year of data collection should be reported with the percentile. In this connection, researchers developing percentile data with which to derive cut-points should also report the time of data collection.

Establishing Cut-Points When the Relationship Between the Test of Interest and a Health Marker in Youth Is Known

In the ideal situation, when there is a concurrent relationship between a health outcome and a fitness test, the cut-points for the test are determined using a data mining procedure2 to establish statistical evidence for the relationship. While not common, this kind of concurrent relationship does exist and has been used for setting cut-points. For example, based on the concurrent relationship between body composition and a set of health outcome measures (total cholesterol, serum lipoprotein ratio, and blood pressure) (Williams et al., 1992), a set of cut-points was derived for evaluating body composition (Going et al., 2008). Similar applications have been reported for setting cut-points for cardiorespiratory endurance (Lobelo et al., 2009) and waist circumference in Chinese school-aged children (Liu et al., 2010) and for body composition and cardiorespiratory endurance tests (Going et al., 2011; Welk et al., 2011).

Establishing Cut-Points When a Concurrent Relationship Has Not Been Confirmed in Youth

Even if a concurrent relationship between a health outcome measure and a putative health-related fitness test has been well established in adults and cut-points exist for that population, such a relationship often has not been confirmed in youth. Because a negative health outcome (e.g., low-back pain, cardiovascular diseases) may take years to develop, children’s health

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2Data mining involves varying cut-points, computing agreement-related statistics with the classification of health outcome measures each time, and determining the cut-points according to optimal statistical results (e.g., highest P- and kappa-coefficients, specificity index and relative risk statistics, findings and illustration of receiver operating characteristic [ROC] curve analysis). If the cut-points are set across a large range of groups, the data from these groups usually are smoothed before the data mining procedure is applied.

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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outcome measures may be in a normal range even if they are not fit. Methods of setting cut-points based on evidence in adults assume that a fit child will likely become a fit adult. While there is some evidence to support this assumption for certain fitness components (see, e.g., Beunen et al., 1992; Campbell et al., 2001; Malina, 1996, 2001), more research, especially longitudinal studies, is needed to confirm this assumption.

When a relationship can be confirmed only in adults, there are two methods for estimating the cut-points for health-related fitness tests in youth—the relative position and the panel-driven methods. With the relative position method, the percentile of adults considered to be at risk based on their performance on a fitness test is taken as the fitness standard in youth. For example, the lowest 20th percentile for performance on a cardiorespiratory endurance test item could be selected based on the demonstration by Blair and colleagues (1989) that morbidity and mortality are disproportionately elevated in the lowest quintile for performance on a maximal treadmill test in adults. In the panel-driven method, a panel of experts uses the cut-points from adults and all available information (e.g., growth curves and performance characteristics for different ages and genders) to derive the cut-points for youth. For example, the criterion maximal oxygen uptake (VO2max) value in youth could be determined in various ways, ranging from expert opinion to extrapolation from associations between VO2max and health outcomes in adults. The panel-driven method was used to set the Fitnessgram® standards for cardiorespiratory endurance test items (Cureton, 1994; Cureton and Warren, 1990).

Establishing Cut-Points When the Relationship Between a Fitness Test and Health Outcomes Is Not Confirmed in Youth or Adults

While the importance of some fitness components to health has been suggested, the relationship between specific fitness test items and health outcomes may not be confirmed. For example, while the validity and reliability of commonly used tests have generally been well established, evidence for the importance of muscular strength for health in adults is still growing and may be equivocal for some tests, and for youth remains largely unconfirmed. Until these relationships are confirmed, an alternative approach for setting cut-points is to use the comparatively relative position method, in which a percentile established for another measure is borrowed. If the percentile from another test is borrowed, the two tests should be as comparable as possible in their nature (e.g., both require movement of the body) and in the dimension they measure (e.g., upper-body strength). For example, if the cut-points for tests of the cardiorespiratory endurance component derived through a criterion-referenced evaluation procedure were set at about the 20th percentile, the cut-points for tests of the musculo-

Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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skeletal fitness component would also be set temporarily by being derived from the 20th percentile. Until health-related cut-points were developed specifically for the test of interest, these interim cut-points might be used.

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Suggested Citation:"3 Methodology for Selection and Interpretation of Health-Related Fitness Measures in Youth." Institute of Medicine. 2012. Fitness Measures and Health Outcomes in Youth. Washington, DC: The National Academies Press. doi: 10.17226/13483.
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Physical fitness affects our ability to function and be active. At poor levels, it is associated with such health outcomes as diabetes and cardiovascular disease. Physical fitness testing in American youth was established on a large scale in the 1950s with an early focus on performance-related fitness that gradually gave way to an emphasis on health-related fitness. Using appropriately selected measures to collected fitness data in youth will advance our understanding of how fitness among youth translates into better health.

In Fitness Measures and Health Outcomes in Youth, the IOM assesses the relationship between youth fitness test items and health outcomes, recommends the best fitness test items, provides guidance for interpreting fitness scores, and provides an agenda for needed research.

The report concludes that selected cardiorespiratory endurance, musculoskeletal fitness, and body composition measures should be in fitness surveys and in schools. Collecting fitness data nationally and in schools helps with setting and achieving fitness goals and priorities for public health at an individual and national level.

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