Running Head: VALIDITY OF A NEW TEST ITEM 1 Validity of the Body Mass Index for Estimating Body Composition for Young Adults with Intellectual Disabilities Mary Ware Western Michigan University Mary Ware is a graduate student in the Master s Degree Program in Special (Adapted) Physical Education at Western Michigan University. This paper was submitted to the instructor in partial fulfillment of the requirements of HPER 6250, Assessment in Special (Adapted) Physical Education.
VALIDITY OF A NEW TEST ITEM 2 Abstract The purpose of this study was to evaluate the validity of the body mass index for assessing body fat percentage in individuals with intellectual disabilities. Participants were 20 males, aged 19-27 (M of age= 22.3 years; SD of age= 2.56). These participants were assessed using both a new test item (body mass index) and a criterion test item (body composition analyzer). The validity of the new test item was measured for concurrent validity using the criterion test as comparison. In order to measure the validity, the Pearson product-moment correlation method was used. A Pearson product-moment correlation coefficient of 0.86 between the two tests was found, demonstrating that body mass index is a valid method of assessing body fat percentage. Additionally, the mean and standard deviation of the body mass index scores were identified during the course of this study, as were the Z and T scores for each of the new test item scores. Keyword: body mass index, validity, new test, fat percentage
VALIDITY OF A NEW TEST ITEM 3 Validity of the Body Mass Index for Estimating Body Composition for Young Adults with Intellectual Disabilities Obesity is a major global problem which increases risk of life-threatening diseases such as cardiovascular disease and diabetes. Between 1980 and 2008, the prevalence of agestandardized obesity nearly doubled, from 6.4% to 12%, with half of that increase occurring more recently between 2000 and 2008 (Stevens et al., 2012). Obesity in individuals with intellectual disabilities is considered a major health risk, and research indicates that obesity levels are similar or higher in individuals with intellectual disabilities when compared to nondisabled peers (Rimmer & Yamaki, 2006). Body composition is a critical component when discussing obesity. Body composition is defined as the components that make up one s total body weight, including fluid, muscle, bone and fat content, and is an important part to one s health and of one s ability to perform functional activities. (Going, Lohman, & Eisenmann, 2013). Body composition, with particular focus in body fat percentage, is an essential part of physical fitness testing in both schools and the medical field. There are many ways to estimate body fat percentage, with the most common being the use of body composition analyzers and body mass index. Body composition analyzers use bioelectrical impedance analysis (BIA). BIA is method of determining body composition by measuring body tissue opposition to the flow of minimal alternating currents (National Institute of Health, 1994). With the ability to determine components of body composition with greater detail, body composition analyzers using BIA are often used for research purposes specifically for determining body fat percentage due to the ability to distinguish body fat from muscle (Li et al., 2013).
VALIDITY OF A NEW TEST ITEM 4 Body mass index (BMI) has been identified as the most commonly used surrogate measure for prediction of body fat percentage (Rangasinghe et al., 2013). It measures body fat by diving weight in kilograms by the square of height in meters ( Understanding body mass, 2005). BMI numbers are then compared to a body mass index table which categorizes results as underweight, normal weight, overweight and obesity. Combined with other health indicators, BMI can be helpful in determining risk and level of personal health. According to Freedman & Sherry (2009), BMI is considered to be more of a measure of excess weight rather than excess body fat, and is a better indicator of excess adiposity in relatively fat children. However, it is considered useful despite its inability to distinguish between fat and lean mass (Wells & Fewtrell, 2006). The rationale for this test is that BMI is a useful tool to estimate a person s body fat, and can be used to identify individuals who are considered overweight or obese. It is also used by both the National Institute of Health and the World Health Organization to determine overweight and obesity statistics (Nguyen & El-Serag, 2010). The purpose of this study was to check the validity of a new test item, body mass index, for use in testing young adults with intellectual disabilities. To complete this, participants were assessed using the new test item (body mass index), and a criterion test item (body composition analyzer), and the data was compared using the Pearson product-moment correlation method to determine the correlation coefficient. The mean and standard deviation of the BMI (new test) scores as well as the Z and T scores for each of the raw scores from the new test were also identify in this study. Method Participants
VALIDITY OF A NEW TEST ITEM 5 This study consisted of a total of 20 individuals between the ages of 19 and 27 (M of age = 22.3 years; SD of age = 2.56 years). All of the participants in this study were male. Each of the participants had an intellectual disability, with all IQ scores falling below 70 (M of IQ = 48.6; SD of IQ = 14.2). Research Design The concurrent validity design (Burton & Miller, 1998) was employed to determine the validity of body mass index as the new test item in this study. To conduct this study, a new test item (BMI) and a criterion-test item (Body composition analyzer) were tested, with the criterion test being used to test the validity of the new test. The body composition analyzer which utilizes bioelectrical impedance was selected due to the fact that previous studies have proven it to be a valid reference method to determine body fat percentage (Castro-Pin ero et al, 2009, p. 940). Test Items The two test items administered to each participant included body mass index (BMI) and body composition analyzer. To determine BMI, each participant was asked to step on a digital platform scale with height rod where weight (in kilograms) and height (in meters) were then recorded. BMI was then calculated using the formula BMI = kg/m². All equipment was calibrated and tested prior to the start of the testing session to ensure accuracy. To measure body fat percentage using BIA, a body composition analyzer (Tanita BC- 418) was used. The test was conducted by having study participants, who were wearing lightweight clothing, first remove their shoes. The participant s individual details, including height, weight, and body type, were then entered into the system, and the participant then stepped onto
VALIDITY OF A NEW TEST ITEM 6 the BC-418, where 8 electrodes on both feet and hands began measuring once the hands grasped the grips (Li et al, 2013). Results were reported as body fat percentage. Data Collection Tests were administered and data collected on two separate days, Tuesday and Thursday, of the same week. Participants were tested in an adapted physical education lab on a one-to-one basis without disturbance from outside sources. A trained graduate student in adapted physical education administered the tests. Data Analysis After both test results were recorded, the Pearson product-moment correlation method was used to find the correlation coefficient. To determine concurrent validity, the correlation coefficient between the two score sets needs to be significant. An acceptable magnitude for indicators of physical fitness is at least r =.80 in order to show a relationship between the two. Additionally further data analysis was completed for the BMI score set, including mean and standard deviation, as well calculating Z and T scores for the BMI scores. Results In Table 1, the raw data is presented for both the new test and the criterion test. Additional information, including XY, X², and Y², are also included. This information is used to determine the Pearson product-movement correlation coefficient between scores from the new test and the criterion test. The Pearson product-movement correlation coefficient was found to be r =.86. The steps taken to determine the correlation coefficient are listed at the bottom of Table 1.
VALIDITY OF A NEW TEST ITEM 7 In Table 2, the raw data from the new test (BMI) is presented, in addition to information derived from this data. This information includes the mean, standard deviation, Z scores, and T scores for the BMI scores. At the end of Table 2, steps taken to calculate the mean, standard deviation, and examples for calculating the Z and T scores (using Participant 1 as the example) are included. Discussion Based on this study, the results demonstrate that body mass index is a valid assessment tool for estimating body composition in young adults with intellectual disabilities. To be considered valid, a Pearson product-movement correlation coefficient must have a magnitude of about.80 for indicators of physical fitness. The correlation coefficient of scores between the new test (BMI) and the criterion test (body composition analyzer) in this study is r = 0.86, which does in fact fall within the acceptable range and is therefore demonstrates a relationship between the two sets of scores. These results indicate that the new test item (BMI) should be considered a valid method of determining body fat percentage. These findings support the widely held belief that suggests a higher BMI is an indicator of excess weight and puts the individual at risk for obesity and disease. It should be noted however that a limitation of the study is that it only included males who have intellectual disabilities. While it may be suggested that the results would stand true for females as well, there were no females included in the test. Additionally, it is possible that testing individuals with other disabilities in addition to intellectual disabilities may produce difference results. For example, young adults with Prader-Willi syndrome have an unusual body
VALIDITY OF A NEW TEST ITEM 8 composition with lower total lean mass and increased adiposity (Theodoro, Talebizadeh, & Butler, 2006, p. 1685) and therefore may not produce similar results in repeated trials. The included tables indicate that this author is able to correctly calculate the correlation coefficient (r), mean, and standard deviation, as well Z scores and T scores. The mean in this study is 29.445. The standard deviation is 9.14. The Z and T scores are listed for individual participants on Table 2. Summary In summary, body mass index is considered a valid assessment tool, based on the proven concurrent validity, for estimating body composition for young adult males with intellectual disabilities between the ages of 19 and 27. It is recommended that the body mass index be used as an assessment tool for males between these ages and that further research be completed to confirm that this would also be a valid tool for estimating body composition in females of a similar age. Additionally, it can be stated that the author of this study understands how to complete the calculations necessary to identify the mean, standard deviation, Z scores and T scores.
VALIDITY OF A NEW TEST ITEM 9 References Burton, A.W., & Miller, D.E. (1998). Movement skill assessment. Champaign, IL: Human Kinetics. Castro-Pin ero, J., Artero, E.G., & Espan a-romero, V., et al. (2009). Criterion-related validity of field-based fitness tests in youth: A systematic review. British Journal of Sports Medicine, 44, 934-943. doi: 10.1136/bjsm.2009.058321. Freedman, D.S., & Sherry, B. (2009). The validity of BMI as an indicator of body fatness and risk among children. Pediatrics, 124. S23-S34. doi: 10.1542/peds.2008-3586E. Going, S.B., Lohman, T.G., & Eisenmann, J.C., (2013). Body composition assessments. In S.A. Plowman & M.D. Meredith (Eds.), Fitnessgram/Activitygram Reference Guide (4 th ed.) Dallas, TX: The Cooper Institute, 7-1, 7-12. Li, Y.-C., Li, C.-I., Lin, W.-Y, Liu, C.-S., Hsu, H.-S., Lee, C.-C,... Lin, C.-C. (2013). Percentage of body fat assessment using bioelectrical impedance analysis and dual-energy x-ray absorptiometry in a weight loss program for obese or overweight Chinese adults. PLOS One, 8(4), e58272. doi:10.1371/journal.pone.0058272. National Institute of Health. (1994). Bioelectrical impedance analysis in body composition measurement. NIH Technology Assessment Statement. Bethesda, MD: United States Department of Health and Human Services. Nguyen, D. M., & El-Serag, H. B. (2010). The epidemiology of obesity. Gastroenterology Clinics of North America, 39(1), 1-7. doi: http://dx.doi.org/10.1016/j.gtc.2009.12.014. Ranasinghe, C., Gamage, P., Katulanda, P., Andraweera, N., Thilakarathne, S., & Tharanga, P. (2013). Relationship between body mass index (BMI) and body fat percentage, estimated by
VALIDITY OF A NEW TEST ITEM 10 bioelectrical impedance, in a group of Sri Lankan adults: A cross sectional study. BMC Public Health, 13, 797. Rimmer, J. H., & Yamaki, K. (2006). Obesity and intellectual disability. Mental Retardation and Developmental Disabilities Research Reviews, 12(1), 22-27. doi:10.1002/mrdd.20091. Stevens, G.A., Singh, G.M., Lu, Y., Danaei, G., Lin, J.K., Finucane, M.M.,... the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group (Body Mass Index. (2012). National, regional, and global trends in adult overweight and obesity prevalences. Population Health Metrics, 10(1), 22. doi: 10.1186/1478-7954-10-22. Theodoro, M.F., Talebizadeh, Z., & Butler, M.G. (2006) Body composition and fatness patterns in Prader-Willi syndrome: Comparison with simple obesity. Obesity, 14(10), 1685-1690. Understanding body mass index. (2005). Postgraduate Medicine, 117(2), 46. Wells, J.C.K., & Fewtrell, M.S. (2006). Measuring body composition. Archives of Diseases in Childhood,91, 612-617. doi: 10.1136/adc.2005.085522.
VALIDITY OF A NEW TEST ITEM 11 Table 1 Raw Data, Derived Data, and Steps for Calculating the Pearson Product-Moment Correlation Coefficient for Body Mass Index and Fat Percentage from Body Composition Analyzer Participant X (BMI) Y (Fat %) XY X² Y² 1 14.20 16.00 227.2 201.64 256 2 30.05 30.10 904.505 903.0025 906.01 3 29.40 35.80 1052.52 864.36 1281.64 4 24.95 37.20 928.14 622.5025 1383.84 5 24.60 20.80 511.68 605.16 432.64 6 31.30 30.90 967.17 979.69 954.81 7 30.60 28.40 869.04 936.36 806.56 8 55.75 48.25 2689.9375 3108.0625 2328.0625 9 27.50 29.30 805.75 756.25 858.49 10 43.00 44.10 1896.3 1849 1944.81 11 27.20 30.10 818.72 739.84 906.01 12 20.20 21.50 434.3 408.04 462.25 13 16.00 17.80 284.8 256 316.84 14 33.80 32.60 1101.88 1142.44 1062.76 15 33.70 31.40 1058.18 1135.69 985.96 16 28.20 31.90 899.58 795.24 1017.61 17 27.50 23.00 632.5 756.25 529 18 24.75 25.10 621.225 612.5625 630.01 19 27.40 27.75 760.35 750.76 770.0625 20 38.80 29.60 1148.48 1505.44 876.16 n = 20 ΣX= 588.90 ΣY= 591.60 ΣXY= 18612.2575 ΣX²= 18928.29 ΣY²= 18709.525 Correlation Coefficient Calculation Procedure Step 1 r = [(n)(σxy) - (ΣX)(ΣY)] / [(n)(σx²) - (ΣX)²] [(n)(σy²) - (ΣY)²] r = [(20)(18612.2575) - (588.90)(591.60)] / [(20)(18928.29) - Step 2 (588.90)²] [(20)(18709.525) - (591.60)²] Step 3 r = [372245.15-348393.24] / [378565.8-346803.21] [374190.5-349990.56] Step 4 r = 23851.91 / [31762.59] [24199.94] = 23851.91 / 768652772.2446 Step 5 r = 23851.91 / 27724.5878643 = 0.86
VALIDITY OF A NEW TEST ITEM 12 Table 2 Raw Data, Derived Data, and Steps for Calculating Mean, Standard Deviation, Z score, and T score for Body Mass Index Participant X (BMI) (X - Mean)² Z Score T Score 1 14.20 232.41-1.67 33.32 2 30.05 0.37 0.07 50.66 3 29.40 0.0020 0.00 49.95 4 24.95 20.21-0.49 45.08 5 24.60 23.47-0.53 44.70 6 31.30 3.44 0.20 52.03 7 30.60 1.33 0.13 51.26 8 55.75 691.95 2.88 78.78 9 27.50 3.78-0.21 47.87 10 43.00 183.74 1.48 64.83 11 27.20 5.04-0.25 47.54 12 20.20 85.47-1.01 39.89 13 16.00 180.77-1.47 35.29 14 33.80 18.97 0.48 54.76 15 33.70 18.11 0.47 54.66 16 28.20 1.55-0.14 48.64 17 27.50 3.78-0.21 47.87 18 24.75 22.04-0.51 44.86 19 27.40 4.18-0.22 47.76 20 38.80 87.52 1.02 60.24 n = 20 ΣX= 588.90 (X - Mean)² = 1588.13 Mean, Standard Deviation, and Examples of Z score and T score Calculation Procedure Mean Mean = X / n = 588.90 / 20 = 29.445 Standard Deviation S = (X - Mean)² / (n-1) = 1588.13 / 19 = 83.59 = 9.14 Z for Participant 1 Z = (X-Mean) / S = (14.20-29.445) / 9.14 = -1.67 T for Participant 1 T = {[10(X-Mean)]/S} + 50 = {[10(14.20-29.445)] / 9.14} +50 = {[10(-15.245)]/9.14} + 50 = {[-152.45]/9.14} + 50 = {-16.68}+50 = 33.32