• the lowest performers (e.g., 20th percentile) to ensure a high probability that an individual identified as being low fit is really low fit and thus at risk for poor health outcomes.

  • Musculoskeletal fitness—Until population-based evidence in youth is available, interim cut-points borrowed from the interim cardiorespiratory endurance percentile (e.g., the 20th percentile) are recommended. There are no data sets from youth or adult populations for any musculoskeletal fitness test. As stated in Chapter 3, in such cases, cut-points should be derived by borrowing the percentile from a test that is as comparable as possible in nature (e.g., requires movement of the body) and in the dimension it measures (e.g., upper-body strength) to the test of interest.

Further research is needed to better understand the relationship between fitness and health and to support selection and validation of the ideal criterion-referenced cut-points for fitness measures. This research should involve the implementation of national surveys that include measures of health outcomes. This and other research recommendations are presented in Chapter 10.

While the use of percentiles in establishing interim cut-points is appropriate until more evidence is collected, the committee recommends that once age- and gender-specific interim cut-points have been established, those cut-points rather than percentiles be used in communicating test results to those being tested, health and school officials, and parents. Doing so will minimize the confusion that might arise in communicating in terms of the percentiles used to derive the cut-points. For example, the CDC has used the 95th percentile from the 1960s to the 1990s as a cut-point for obesity in children, yet more than 15 percent of youth currently exceed the 95th percentile. In instances where percentiles may allow a clearer presentation of the results, as for BMI, the year of data collection should be reported with the percentile. The committee also notes that test administrators, those interpreting and communicating the results, and researchers should be fully familiar with the derivation of cut-points so they can interpret distribution changes in the population. To this end, survey administrators and those communicating the results should receive the appropriate training in interpreting tests to minimize classification errors. In addition, researchers developing percentile data for use in deriving interim cut-points should report the year of data collection. Fitness data from large populations are needed to derive the appropriate cut-points from percentiles. If such data are not available, developers of interim cut-points should consult with statisticians to design a small study with a representative sample of U.S. youth to provide such data.



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