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7. BODY WEIGHT STUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7.1. KEY BODY WEIGHT STUDY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 7.2. RELEVANT BODY WEIGHT STUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 7.3. RECOMMENDATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 7.4. REFERENCES FOR CHAPTER 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Volume I  General Factors Chapter 7  Body Weight Studies Exposure Factors Handbook Page August 1997 7 1 7. BODY WEIGHT STUDIES There are several physiological factors needed to included academic investigators and representatives from calculate potential exposures. These include skin surface CDC Nutrition Surveillance Program selected, collated, area ( see Volume I, Section 6), inhalation rate ( see Volume integrated, and defined appropriate data sets to generate I, Section 5) life expectancy ( see Volume I, Section 8), and growth curves for the age interval: birth to 36 months body weight. The average daily dose is typically normalized developed ( Hamill et al., 1979). The percentile curves to the average body weight of the exposed population. If were for assessing the physical growth of children in the exposure occurs only during childhood years, the average U. S. They are based on accurate measurements made on child body weight during the exposure period should be large nationally representative samples of children ( Hamill used to estimate risk ( U. S. EPA, 1989). Conversely, if et al., 1979). Smoothed percentile curves were derived for adult exposures are being evaluated, an adult body weight body weight by age ( Hamill et al., 1979). Curves were value should be used. developed for boys and for girls. The data used to construct The purpose of this section is to describe published the curves were provided by the Fels Research Institute, studies on body weight for the general U. S. population. The Yellow Springs, Ohio. These data were from an ongoing studies have been classified as either key or relevant studies, longitudinal study where anthromopetric data from direct based on the criteria described in Volume I, Section 1.3.1. measurements are collected regularly from participants Recommended values are based on the results of key (~ 1,000) in various areas of the U. S. The NCHS used studies, but relevant studies are also presented to provide advanced statistical and computer technology to generate the reader with added perspective on the current state of the growth curves. Table 7 1 presents the percentiles of knowledge pertaining to body weight. weight by sex and age. Figures 7 1 and 7 2 present weight 7.1. KEY BODY WEIGHT STUDY Hamill et al. ( 1979)  Physical Growth: National Center for Health Statistics Percentiles  A National Center for Health Statistics ( NCHS) Task Force that by age percentiles for boys and for girls aged birth to 36 months, respectively. Limitations of this study are that mean body weight values were not reported and the data are more Table 7 1. Smoothed Percentiles of Weight ( in kg) by Sex and Age: Statistics from NCHS and Data from Fels Research Institute, Birth to 36 Months Smoothed Percentile a 5th 10th 25th 50th 75th 90th 95th Sex and Age Weight in Kilograms Male Birth 2.54 2.78 3.00 3.27 3.64 3.82 4.15 1 Month 3.16 3.43 3.82 4.29 4.75 5.14 5.38 3 Months 4.43 4.78 5.32 5.98 6.56 7.14 7.37 6 Months 6.20 6.61 7.20 7.85 8.49 9.10 9.46 9 Months 7.52 7.95 8.56 9.18 9.88 10.49 10.93 12 Months 8.43 8.84 9.49 10.15 10.91 11.54 11.99 18 Months 9.59 9.92 10.67 11.47 12.31 13.05 13.44 24 Months 10.54 10.85 11.65 12.59 13.44 14.29 14.70 30 Months 11.44 11.80 12.63 13.67 14.51 15.47 15.97 36 Months 12.26 12.69 13.58 14.69 15.59 16.66 17.28 Female Birth 2.36 2.58 2.93 3.23 3.52 3.64 3.81 1 Month 2.97 3.22 3.59 3.98 4.36 4.65 4.92 3 Months 4.18 4.47 4.88 5.40 5.90 6.39 6.74 6 Months 5.79 6.12 6.60 7.21 7.83 8.38 8.73 9 Months 7.00 7.34 7.89 8.56 9.24 9.83 10.17 12 Months 7.84 8.19 8.81 9.53 10.23 10.87 11.24 18 Months 8.92 9.30 10.04 10.82 11.55 12.30 12.76 24 Months 9.87 10.26 11.10 11.90 12.74 13.57 14.08 30 Months 10.78 11.21 12.11 12.93 13.93 14.81 15.35 36 Months 11.60 12.07 12.99 13.93 15.03 15.97 16.54 Smoothed by cubic spline approximation. a Source: Hamill et al., 1979. Volume I  General Factors Chapter 7  Body Weight Studies Page Exposure Factors Handbook 7 2 August 1997 Figure 7 1. Weight by Age Percentiles for Boys Aged Birth 36 Months Source: Hamill et al., 1979. Volume I  General Factors Chapter 7  Body Weight Studies Exposure Factors Handbook Page August 1997 7 3 Figure 7 2. Weight by Age Percentiles for Girls Aged Birth 36 Months Source: Hamill et al., 1979 Volume I  General Factors Chapter 7  Body Weight Studies Page Exposure Factors Handbook 7 4 August 1997 that 15 years old. However, this study does provide body weight data for infants less than 6 months old. NCHS ( 1987)  Anthropometric Reference Data and Prevalence of Overweight, United States, 1976 80  Statistics on anthropometric measurements, including body weight, for the U. S. population were collected by NCHS through the second National Health and Nutrition Examination Survey ( NHANES II). NHANES II was conducted on a nationwide probability sample of approximately 28,000 persons, aged 6 months to 74 years, from the civilian, non institutionalized population of the United States. Of the 28,000 persons, 20,322 were interviewed and examined, resulting in a response rate of 73.1 percent. The survey began in February 1976 and was completed in February 1980. The sample was selected so that certain subgroups thought to be at high risk of malnutrition ( persons with low incomes, preschool children, and the elderly) were oversampled. The estimates were weighted to reflect national population estimates. The weighting was accomplished by inflating examination results for each subject by the reciprocal of selection probabilities adjusted to account for those who were not examined, and post stratifying by race, age, and sex ( NCHS, 1987). The NHANES II collected standard body measurements of sample subjects, including height and weight, that were made at various times of the day and in different seasons of the year. This technique was used because one's weight may vary between winter and summer and may fluctuate with recency of food and water intake and 13 years 49.9 12.3 50.9 11.8 50.4 other daily activities ( NCHS, 1987). Mean body weights of adults, by age, and their standard deviations are presented in Table 7 2 for men, women, and both sexes combined. Mean body weights and standard deviations for children, ages 6 months to 19 years, are presented in Table 7 3 for boys, girls, and boys and girls combined. Percentile distributions of the body weights of adults by age and race for males are presented in Table 7 4, and for females in Table 7 5. Data for children by age are presented in Table 7 6 for males, and for females in Table 7 7. Results shown in Tables 7 4 and 7 5 indicate that the mean weight for adult males is 78.1 kg and for adult females, 65.4 kg. It also shows that the mean weight for White males ( 78.5 kg) is greater than for Black males ( 77.9 kg). Additionally, mean weights are greater for Black females ( 71.2 kg) than for White females ( 64.8 kg). From Table 7 3, the mean body weights for girls and boys are approximately the same from ages 6 months to 14 years. Starting at years 15 19, the difference in mean body weight ranges from 6 to 11 kg. Table 7 2. Body Weights of Adults ( kilograms) a Age ( years) Men Women Women Men and Mean Std. Mean Std. Mean ( kg) ( kg) Dev. ( kg) Dev.

18 < 25 73.8 12.7 60.6 11.9 67.2 25 < 35 78.7 13.7 64.2 15.0 71.5 35 < 45 80.9 13.4 67.1 15.2 74.0 45 < 55 80.9 13.6 68.0 15.3 74.5 55 < 65 78.8 12.8 67.9 14.7 73.4 65 < 75 74.8 12.8 66.6 13.8 70.7 18 < 75 78.1 13.5 65.4 14.6 71.8 Note: 1 kg = 2.2046 pounds. Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. a Source: Adapted from National Center for Health Statistics ( NCHS), 1987.

Table 7 3. Body Weights of Children ( kilograms) a Age Boys Girls Girls Boys and Mean Std. Mean Std. Mean ( kg) Dev. ( kg) Dev. ( kg)

6 11 months 9.4 1.3 8.8 1.2 9.1 1 year 11.8 1.9 10.8 1.4 11.3 2 years 13.6 1.7 13.0 1.5 13.3 3 years 15.7 2.0 14.9 2.1 15.3 4 years 17.8 2.5 17.0 2.4 17.4 5 years 19.8 3.0 19.6 3.3 19.7 6 years 23.0 4.0 22.1 4.0 22.6 7 years 25.1 3.9 24.7 5.0 24.9 8 years 28.2 6.2 27.9 5.7 28.1 9 years 31.1 6.3 31.9 8.4 31.5 10 years 36.4 7.7 36.1 8.0 36.3 11 years 40.3 10.1 41.8 10.9 41.1 12 years 44.2 10.1 46.4 10.1 45.3 14 years 57.1 11.0 54.8 11.1 56.0 15 years 61.0 11.0 55.1 9.8 58.1 16 years 67.1 12.4 58. l 10.1 62.6 17 years 66.7 11.5 59.6 11.4 63.2 18 years 71.1 12.7 59.0 11.1 65.1 19 years 71.7 11.6 60.2 11.0 66.0 Note: 1 kg = 2.2046 pounds. Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. a Source: Adapted from National Center for Health Statistics ( NCHS), 1987.

7.2. RELEVANT BODY WEIGHT STUDIES Brainard and Burmaster ( 1992)  Bivariate Distributions for Height and Weight of Men and Women in the United States  Brainard and Burmaster ( 1992) examined data on the height and weight of adults published by the U. S. Public Health Service and fit bivariate distributions to the tabulated values for men and women, separately. Volume I  General Factors Chapter 7  Body Weight Studies Exposure Factors Handbook Page August 1997 7 5 Table 7 4. Weight in Kilograms for Males 18 74 Years of Age Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976 1980a Percentile Number of Persons Mean Standard Race and Age Examined ( kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th All racesb 18 74 years ........ 5,916 78.1 13.5 58.6 62.3 64.9 68.7 76.9 85.6 91.3 95.7 102.7 18 24 years ......... 988 73.8 12.7 56.8 60.4 61.9 64.8 72.0 80.3 85.1 90.4 99.5 25 34 years ........ 1,067 78.7 13.7 59.5 62.9 65.4 69.3 77.5 85.6 91.1 95.1 102.7 35 44 years ......... 745 80.9 13.4 59.7 65.1 67.7 72.1 79.9 88.1 94.8 98.8 104.3 45 54 years ......... 690 80.9 13.6 50.8 65.2 67.2 71.7 79.0 89.4 94.5 99.5 105.3 55 64 years ........ 1,227 78.8 12.8 59.9 63.8 66.4 70.2 77.7 85.6 90.5 94.7 102.3 65 74 years ........ 1,199 74.8 12.8 54.4 58.5 61.2 66.1 74.2 82.7 87.9 91.2 96.6 White 18 74 years ........ 5,148 78.5 13.1 59.3 62.8 65.5 69.4 77.3 85.6 91.4 95.5 102.3 18 24 years ......... 846 74.2 12.8 56.8 60.5 62.0 65.0 72.4 80.6 85.5 91.0 100.0 25 34 years ......... 901 79.0 13.1 59.9 63.7 65.9 69.8 78.0 85.6 91.3 95.3 102.7 35 44 years ......... 653 81.4 12.8 62.3 66.6 68.8 72.9 80.1 88.2 94.6 98.7 104.1 45 54 years ......... 617 81.0 13.4 62.0 66.1 67.3 71.9 79.0 89.4 94.2 99.0 104.5 55 64 years ........ 1,086 78.9 12.4 60.5 64.5 66.6 70.6 78.2 85.6 90.4 94.5 101.7 65 74 years ........ 1,045 75.4 12.4 55.5 59.5 62.5 67.0 74.7 83.0 87.9 91.2 96.0 Black 18 74 years ......... 649 77.9 15.2 58.0 61.1 63.6 67.2 75.3 85.4 92.9 98.3 105.4 18 24 years ......... 121 72.2 12.0 58.3 60.9 62.3 64.9 70.8 77.1 81.8 83.7 93.6 25 34 years ......... 139 78.2 16.3 58.7 63.4 64.9 68.4 75.3 84.4 90.6 92.2 106.3 35 44 years .......... 70 82.5 15.4 * 61.7 65.2 69.7 83.1 94.8 100.4 104.2 *

c 45 54 years .......... 62 82.4 14.5 * 64.7 67.0 73.2 81.8 93.0 100.0 102.5 *

55 64 years ......... 129 78.6 14.7 56.8 61.4 64.3 68.0 77.0 86.5 93.8 98.6 104.7 65 74 years ......... 128 73.3 15.3 52.5 56.7 58.0 61.0 71.2 81.1 90.8 97.3 105.1 Note: 1 kg = 2.2046 pounds.

Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.

a Includes all other races not shown as separate categories.

b Data not available.

c Source: National Center for Health Statistics, 1987. Volume I  General Factors Chapter 7  Body Weight Studies Page Exposure Factors Handbook 7 6 August 1997 Table 7 5. Weight in Kilograms for Females 18 74 Years of Age Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976 1980a Percentile Number of Persons Mean Standard Race and Age Examined ( kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th All racesb 18 74 years ....... 6,588 65.4 14.6 47.7 50.3 52.2 55.4 62.4 72.1 79.2 84.4 93.1 18 24 years ....... 1,066 60.6 11.9 46.6 49.1 50.6 53.2 58.0 65.0 70.4 75.3 82.9 25 34 years ....... 1,170 64.2 15.0 47.4 49.6 51.4 54.3 60.9 69.6 78.4 84.1 93.5 35 44 years ......... 844 67.1 15.2 49.2 52.0 53.3 56.9 63.4 73.9 81.7 87.5 98.9 45 54 years ......... 763 68.0 15.3 48.5 51.3 53.3 57.3 65.5 75.7 82.1 87.6 96.0 55 64 years ....... 1,329 67.9 14.7 48.6 51.3 54.1 57.3 65.2 75.3 82.3 87.5 95.1 65 74 years ....... 1,416 66.6 13.8 47.1 50.8 53.2 57.4 64.8 73.8 79.8 84.4 91.3 White 18 74 years ....... 5,686 64.8 14.1 47.7 50.3 52.2 55.2 62.1 71.1 77.9 83.3 91.5 18 24 years ......... 892 60.4 11.6 47.3 49.5 50.8 53.3 57.9 64.8 69.7 74.3 82.4 25 34 years ....... 1,000 63.6 14.5 47.3 49.5 51.3 54.0 60.6 68.9 76.3 81.5 89.7 35 44 years ......... 726 66.1 14.5 49.3 51.8 52.9 56.3 62.4 71.9 79.7 85.8 94.9 45 54 years ......... 647 67.3 14.4 48.6 51.3 53.4 57.0 65.0 74.8 81.1 85.6 94.5 55 64 years ....... 1,176 67.2 14.4 48.5 50.7 53.7 57.1 64.7 74.5 81.8 86.2 92.8 65 74 years ....... 1,245 66.2 13.7 47.2 50.7 52.9 57.2 64.3 72.9 79.2 84.3 91.2 Black 18 74 years ......... 782 71.2 17.3 48.8 51.6 55.1 59.1 67.8 80.6 87.4 94.9 105.1 18 24 years ......... 147 63.1 13.9 46.2 49.0 50.6 53.8 60.4 70.0 75.8 79.1 89.3 25 34 years ......... 145 69.3 16.7 48.3 50.8 53.1 57.8 65.3 80.2 87.1 91.5 102.7 35 44 years ......... 103 75.3 18.4 50.7 55.2 57.2 63.0 70.2 85.2 95.3 103.5 113.1 45 54 years ......... 100 77.7 18.8 55.1 60.3 60.8 64.5 74.3 83.6 94.5 98.2 117.5 55 64 years ......... 135 75.8 16.4 54.2 55.2 57.6 65.4 74.6 83.4 91.9 95.5 108.5 65 74 years ......... 152 72.4 13.6 52.9 56.4 60.3 64.0 70.0 82.2 84.4 86.5 98.1 Note: 1 kg = 2.2046 pounds.

Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.

a Includes all other races not shown as separate categories.

b Source: National Center for Health Statistics, 1987. Volume I  General Factors Chapter 7  Body Weight Studies Exposure Factors Handbook Page August 1997 7 7 Table 7 6. Weight in Kilograms for Males 6 Months 19 Years of Age Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976 1980a Percentile Number of Persons Mean Standard Age Examined ( kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 6 11 months ........ 179 9.4 1.3 7.5 7.6 8.2 8.6 9.4 10.1 10.7 10.9 11.4 1 years ............ 370 11.8 1.9 9.6 10.0 10.3 10.8 11.7 12.6 13.1 13.6 14.4 2 years ............ 375 13.6 1.7 11.1 11.6 11.8 12.6 13.5 14.5 15.2 15.8 16.5 3 years ............ 418 15.7 2.0 12.9 13.5 13.9 14.4 15.4 16.8 17.4 17.9 19.1 4 years ............ 404 17.8 2.5 14.1 15.0 15.3 16.0 17.6 19.0 19.9 20.9 22.2 5 years ............ 397 19.8 3.0 16.0 16.8 17.1 17.7 19.4 21.3 22.9 23.7 25.4 6 years ............ 133 23.0 4.0 18.6 19.2 19.8 20.3 22.0 24.1 26.4 28.3 30.1 7 years ............ 148 25.1 3.9 19.7 20.8 21.2 22.2 24.8 26.9 28.2 29.6 33.9 8 years ............ 147 28.2 6.2 20.4 22.7 23.6 24.6 27.5 29.9 33.0 35.5 39.1 9 years ............ 145 31.1 6.3 24.0 25.6 26.0 27.1 30.2 33.0 35.4 38.6 43.1 10 years ........... 157 36.4 7.7 27.2 28.2 29.6 31.4 34.8 39.2 43.5 46.3 53.4 11 years ........... 155 40.3 10.1 26.8 28.8 31.8 33.5 37.3 46.4 52.0 57.0 61.0 12 years ........... 145 44.2 10.1 30.7 32.5 35.4 37.8 42.5 48.8 52.6 58.9 67.5 13 years ........... 173 49.9 12.3 35.4 37.0 38.3 40.1 48.4 56.3 59.8 64.2 69.9 14 years ........... 186 57.1 11.0 41.0 44.5 46.4 49.8 56.4 63.3 66.1 68.9 77.0 15 years ........... 184 61.0 11.0 46.2 49.1 50.6 54.2 60.1 64.9 68.7 72.8 81.3 16 years ........... 178 67.1 12.4 51.4 54.3 56.1 57.6 64.4 73.6 78.1 82.2 91.2 17 years ........... 173 66.7 11.5 50.7 53.4 54.8 58.8 65.8 72.0 76.8 82.3 88.9 18 years ........... 164 71.1 12.7 54.1 56.6 60.3 61.9 70.4 76.6 80.0 83.5 95.3 19 years ........... 148 71.7 11.6 55.9 57.9 60.5 63.8 69.5 77.9 84.3 86.8 92.1 Note: 1 kg = 2.2046 pounds.

Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.

a Source: National Center for Health Statistics, 1987. Volume I  General Factors Chapter 7  Body Weight Studies Page Exposure Factors Handbook 7 8 August 1997 Table 7 7. Weight in Kilograms for Females 6 Months 19 Years of Age Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976 1980a Percentile Number of Persons Mean Standard Age Examined ( kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 6 11 months ........ 177 8.8 1.2 6.6 7.3 7.5 7.9 8.9 9.4 10.1 10.4 10.9 1 years ............ 336 10.8 1.4 8.8 9.1 9.4 9.9 10.7 11.7 12.4 12.7 13.4 2 years ............ 336 13.0 1.5 10.8 11.2 11.6 12.0 12.7 13.8 14.5 14.9 15.9 3 years ............ 366 14.9 2.1 11.7 12.3 12.9 13.4 14.7 16.1 17.0 17.4 18.4 4 years ............ 396 17.0 2.4 13.7 14.3 14.5 15.2 16.7 18.4 19.3 20.2 21.1 5 years ............ 364 19.6 3.3 15.3 16.1 16.7 17.2 19.0 21.2 22.8 24.7 26.6 6 years ............ 135 22.1 4.0 17.0 17.8 18.6 19.3 21.3 23.8 26.6 28.9 29.6 7 years ............ 157 24.7 5.0 19.2 19.5 19.8 21.4 23.8 27.1 28.7 30.3 34.0 8 years ............ 123 27.9 5.7 21.4 22.3 23.3 24.4 27.5 30.2 31.3 33.2 36.5 9 years ............ 149 31.9 8.4 22.9 25.0 25.8 27.0 29.7 33.6 39.3 43.3 48.4 10 years ........... 136 36.1 8.0 25.7 27.5 29.0 31.0 34.5 39.5 44.2 45.8 49.6 11 years ........... 140 41.8 10.9 29.8 30.3 31.3 33.9 40.3 45.8 51.0 56.6 60.0 12 years ........... 147 46.4 10.1 32.3 35.0 36.7 39.1 45.4 52.6 58.0 60.5 64.3 13 years ........... 162 50.9 11.8 35.4 39.0 40.3 44.1 49.0 55.2 60.9 66.4 76.3 14 years ........... 178 54.8 11.1 40.3 42.8 43.7 47.4 53.1 60.3 65.7 67.6 75.2 15 years ........... 145 55.1 9.8 44.0 45.1 46.5 48.2 53.3 59.6 62.2 65.5 76.6 16 years ........... 170 58.1 10.1 44.1 47.3 48.9 51.3 55.6 62.5 68.9 73.3 76.8 17 years ........... 134 59.6 11.4 44.5 48.9 50.5 52.2 58.4 63.4 68.4 71.6 81.8 18 years ........... 170 59.0 11.1 45.3 49.5 50.8 52.8 56.4 63.0 66.0 70.1 78.0 19 years ........... 158 60.2 11.0 48.5 49.7 51.7 53.9 57.1 64.4 70.7 74.8 78.1 Note: 1 kg = 2.2046 pounds.

Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.

a Source: National Center for Health Statistics, 1987. Volume I  General Factors Chapter 7  Body Weight Studies Exposure Factors Handbook Page August 1997 7 9 Height and weight of 5,916 men and 6,588 women females and 4,379 males 6 months to 20 years of age in the in the age range of 18 to 74 years were taken from the U. S. ( Burmaster et al., 1994). The NHANES II data had NHANES II study and statistically adjusted to represent the been statistically adjusted for non response and probability U. S. population aged 18 to 74 years with regard to age of selection, and stratified by age, sex, and race to reflect the structure, sex, and race. Estimation techniques were used entire U. S. population prior to reporting ( Burmaster et al., to fit normal distributions to the cumulative marginal data 1994). Burmaster et al. ( 1994) conducted exploratory and and goodness of fit tests were used to test the hypothesis quantitative data analyses, and fit normal and lognormal that height and lognormal weight follow a normal distributions to percentiles of body weight for children. distribution for each sex. It was found that the marginal Cumulative distribution functions ( CDFs) were plotted for distributions of height and lognormal weight for both men female and male body weights on both linear and and women are Gaussian ( normal) in form. This conclusion logarithmic scales. was reached by visual observation and the high R values Two models were used to assess the probability 2 for best fit lines obtained using linear regression. The R density functions ( PDFs) of children's body weight. Linear 2 values for men's height and lognormal weight are reported and quadratic regression lines were fitted to the data. A to be 0.999. The R values for women's height and number of goodness of fit measures were conducted on data 2 lognormal weight are 0.999 and 0.985, respectively. generated by the two models. Burmaster et al. ( 1994) found Brainard and Burmaster ( 1992) fit bivariate that lognormal distributions give strong fits to the body distributions to estimated numbers of men and women aged weights of children, ages 6 months to 20 years. Statistics 18 to 74 years in cells representing 1 inch height intervals for the lognormal probability plots are presented in Tables and 10 pound weight intervals. Adjusted height and 7 8 and 7 9. These data can be used for further analyses of lognormal weight data for men were fit to a single bivariate body weight distribution ( i. e., application of Monte Carlo normal distribution with an estimated mean height of 1.75 analysis). meters ( 69.2 inches) and an estimated mean weight of 78.6 kg ( 173.2 pounds). For women, height and lognormal weight data were fit to a pair of superimposed bivariate normal distributions ( Brainard and Burmaster, 1992). The average height and weight for women were estimated from the combined bivariate analyses. Mean height for women was estimated to be 1.62 meters ( 63.8 inches) and mean weight was estimated to be 65.8 kg ( 145.0 pounds). For women, a calculation using a single bivarite normal distribution gave poor results ( Brainard and Burmaster, 1992). According to Brainard and Burmaster, the distributions are suitable for use in Monte Carlo simulation. 8 to 9 years 3.31 0.156 Burmaster et al. ( 1994) ( Submitted 2/ 19/ 94 to Risk Analysis for Publication)  Lognormal Distributions of Body Weight as a Function of Age for Female and Male Children in the United States  Burmaster et al. ( 1994), performed data analysis to fit normal and lognormal distributions to the body weights of female and male children at age 6 months to 20 years ( Burmaster et al., 1994). Data used in this analysis were from the second survey of the National Center for Health Statistics, NHANES II, which included responses from 4,079 Table 7 8. Statistics for Probability Plot Regression Analyses Female's Body Weights 6 Months to 20 Years of Age Age Linear Curve Lognormal Probability Plots F F 2 a 2 a 6 months to 1 year 2.16 0.145 1 to 2 years 2.38 0.128 2 to 3 years 2.56 0.112 3 to 4 years 2.69 0.137 4 to 5 years 2.83 0.133 5 to 6 years 2.98 0.163 6 to 7 years 3.10 0.174 7 to 8 years 3.19 0.174 9 to 10 years 3.46 0.214 10 to 11 years 3.57 0.199 11 to 12 years 3.71 0.226 12 to 13 years 3.82 0.213 13 to 14 years 3.92 0.216 14 to 15 years 3.99 0.187 15 to 16 years 4.00 0.156 16 to 17 years 4.06 0.167 17 to 18 years 4.08 0.165 18 to 19 years 4.07 0.147 19 to 20 years 4.10 0.149 F , F  correspond to the mean and standard deviation, respectively, of the a 2 2 lognormal distribution of body weight ( kg). Source: Burmaster et al., 1994.

Table 7 9. Statistics for Probability Plot Regression Analyses Volume I  General Factors Chapter 7  Body Weight Studies Page Exposure Factors Handbook 7 10 August 1997 Age Lognormal Probability Plots Linear Curve F F 2 a 2 a 6 months to 1 year 2.23 0.132 1 to 2 years 2.46 0.119 2 to 3 years 2.60 0.120 3 to 4 years 2.75 0.114 4 to 5 years 2.87 0.133 the confidence ratings for body weight recommendations. 5 to 6 years 2.99 0.138 6 to 7 years 3.13 0.145 7 to 8 years 3.21 0.151 8 to 9 years 3.33 0.181 9 to 10 years 3.43 0.165 10 to 11 years 3.59 0.195 11 to 12 years 3.69 0.252 12 to 13 years 3.78 0.224 13 to 14 years 3.88 0.215 14 to 15 years 4.02 0.181 15 to 16 years 4.09 0.159 16 to 17 years 4.20 0.168 17 to 18 years 4.19 0.167 18 to 19 years 4.25 0.159 19 to 20 years 4.26 0.154 F , F  correspond to the mean and standard deviation, a 2 2 respectively, of the lognormal distribution of body weight ( kg). Source: Burmaster et al., 1994.

AIHC  Exposure Factors Sourcebook  The Exposure Factors Sourcebook ( AIHC, 1994) provides similar body weight data as presented here. Consistent with this document, an average adult body weight of 72 kg is recommended on the basis of the NHANES II data ( NCHS, 1987). These data are also used to derive probability distributions for adults and children. In addition, the Sourcebook presents probability distributions derived by Brainard and Burmaster ( 1992), Versar ( 1991) and Brorby and Finley ( 1993). For each distribution, the @ Risk formula is provided for direct use in the @ Risk simulation software ( Palisade, 1992). The organization of this document, makes it very convenient to use in support of Monte Carlo analysis. The reviews of the supporting studies are very brief with little analysis of their strengths and weaknesses. The Sourcebook has been classified as a relevant rather than key study because it is not the primary source for the data used to make recommendations in this document. The Sourcebook is very similar to this document in the sense that it summarizes exposure factor data and recommends values. As such, it is clearly relevant as an alternative information source on body weights as well as other exposure factors. 7.3. RECOMMENDATIONS The key studies described in this section was used in selecting recommended values for body weight. The general description of both the key and relevant studies are summarized in Table 7 10. The recommendations for body weight are summarized in Table 7 11. Table 7 12 presents The mean body weight for all adults ( male and female, all age groups) combined is 71.8 kg as shown in Table 7 2. The mean values for each age group in Table 7 2 were derived by adding the body weights for men and women and dividing by 2. If age and sex distribution of the exposed population is known, the mean body weight values in Table 7 2 can be used. If percentile data are needed or if race is a factor, Tables 7 4 and 7 5 can be used to select the appropriate data for percentiles or mean values. For infants ( birth to 6 months), appropriate values for body weight may be selected from Table 7 1. These data ( percentile only) are presented for male and female infants. For children, appropriate mean values for weights may be selected from Table 7 3. If percentile values are needed, these data are presented in Table 7 6 for male children and in Table 7 7 for female children. Body weight is a function of age, gender, and race and populations of many geographic regions may vary from the general population across geographic regions. Therefore, the user should make appropriate adjustments when applying the percentiles to other geographic regions. The mean recommended value for adults ( 71.8 kg) is different than the 70 kg commonly assumed in EPA risk assessments. Assessors are encouraged to use values which most accurately reflect the exposed population. When using values other than 70 kg, however, the assessors should consider if the dose estimate will be used to estimate risk by combining with a dose response relationship which was derived assuming a body weight of 70 kg. If such an inconsistency exists, the assessor should adjust the doseresponse relationship as described in the appendix to Chapter 1. The Integrated Risk Information System ( IRIS) does not use a 70 kg body weight assumption in the derivation of RfCs and RfDs, but does make this assumption in the derivation of cancer slope factors and unit risks.

Table 7 10. Summary of Body Weight Studies Volume I  General Factors Chapter 7  Body Weight Studies Exposure Factors Handbook Page August 1997 7 11 Study Number of Subjects Population Comments KEY STUDIES Hamill et al. ( 1979) ~ 1,000 U. S. general Authors noted that data are accurate measurements from a population large nationally representative sample of children.

NCHS, 1987 20,322 U. S. general Based on civilian non institutionalized population aged 6 ( NHANES II) population months to 74 years. Response rate was 73.1 percent.

RELEVANT STUDIES Brainard and Burmaster, 1992 12,501 ( 5,916 men and 6,588 U. S. general Used data from NHANES II to fit bivarite distributions to women) population women and men age 18 to 74 years.

Burmaster et al., 1994 8,458 ( 4,079 females and 4,379 U. S. general Used data from NHANES II to develop fitted distributions males) population for children aged 6 to 20 years old. Adjusted for nonresponse by age, gender, and race.

Table 7 11. Summary of Recommended Values for Body Weight Population Mean Upper Percentile Multiple Percentiles Adults 71.8 kg ( See Table 7 2) See Tables 7 4 and 7 5 See Tables 7 4 and 7 5 Children See Table 7 3 See Tables 7 6 and 7 7 See Tables 7 6 and 7 7 Infants Not Available See Table 7 1 See Table 7 1 7.4. REFERENCES FOR CHAPTER 7 American Industrial Health Council ( AIHC). ( 1994) Exposure factors sourcebook. AIHC, Washington, DC. Brainard, J.; Burmaster, D. ( 1992) Bivariate distributions for height and weight of men and women in the United States. Risk Anal. 12( 2): 267 275. Brorby, G.; Finley, G. ( 1993) Standard probability density functions for routine use in environmental health risk assessment. Presented at the Society of Risk Analysis Annual Meeting, December 1993, Savannah, GA. Burmaster, D. E.; Lloyd, K. J.; Crouch, E. A. C. ( 1994) Lognormal distributions of body weight as a function of age for female and male children in the United States. Submitted 2/ 19/ 94 to Risk Analysis for publication. Hamill, P. V. V.; Drizd, T. A.; Johnson, C. L.; Reed, R. B.; Roche, A. F.; Moore, W. M. ( 1979) Physical growth: National Center for Health Statistics Percentiles. American J. Clin. Nutr. 32: 607 609. National Center for Health Statistics ( NCHS) ( 1987) Anthropometric reference data and prevalence of overweight, United States, 1976 80. Data from the National Health and Nutrition Examination Survey, Series 11, No. 238. Hyattsville, MD: U. S. Department of Health and Human Services, Public Health Service, National Center for Health Statistics. DHHS Publication No. ( PHS) 87 1688. Palisade. ( 1992) @ Risk Users Guide. Palisade Corporation, Newfield, NY. U. S. EPA ( 1989) Risk assessment guidance for Superfund, Volume I: Human health evaluation manual. Washington, DC: U. S. Environmental Protection Agency, Office of Emergency and Remedial Response. EPA/ 540/ 1 89/ 002. Versar, Inc. ( 1991) Analysis of the impact of exposure assumptions on risk assessment of chemicals in the environment, phase II: uncertainty analyses of existing exposure assessment methods. Draft Report. Prepared for Exposure Assessment Task Group, Chemical Manufacturers Association, Washington, DC. Volume I  General Factors Chapter 7  Body Weight Studies Page Exposure Factors Handbook 7 12 August 1997 Table 7 12. Confidence in Body Weight Recommendations Considerations Rationale Rating Study Elements ° Level of peer review NHANES II was the major source of data for NCHS ( 1987). This is a High published study which received a high level of peer review. The Hamill et al. ( 1979) is a peer reviewed journal publication.

° Accessibility Both studies are available to the public. High ° Reproducibility Results can be reproduced by analyzing NHANES II data and the Fels High Research Institute data.

° Focus on factor of interest The studies focused on body weight, the exposure factor of interest. High ° Data pertinent to US The data represent the U. S. population. High ° Primary data The primary data were generated from NHANES II data and Fels studies, Medium thus these data are secondary.

° Currency The data were collected between 1976 1980. Low ° Adequacy of data collection The NHANES II study included data collected over a period of 4 years. High period Body weight measurements were taken at various times of the day and at different seasons of the year.

° Validity of approach Direct body weights were measured for both studies. For NHANES II, High subgroups at risk for malnutrition were over sampled. Weighting was accomplished by inflating examination results for those not examined and were stratified by race, age, and sex. The Fels data are from an ongoing longitudinal study where the data are collected regularly.

° Study size The sample size consisted of 28,000 persons for NHANES II. Author noted High in Hamill et al. ( 1979) that the data set was large.

° Representativeness of the Data collected focused on the U. S. population for both studies. High population ° Characterization of Both studies characterized variability regarding age and sex. Additionally High variability NHANES II characterized race ( for Blacks, Whites and total populations) and sampled persons with low income.

° Lack of bias in study design There are no apparent biases in the study designs for NHANES II. The Medium ( high rating is desirable) study design for collecting the Fels data was not provided. High ° Measurement error For NHANES II, measurement error should be low since body weights were High performed in a mobile examination center using standardized procedures and equipment. Also, measurements were taken at various times of the day to account for weight fluctuations as a result of recent food or water intake. The authors of Hamill et al. ( 1979) report that study data are based on accurate direct measurements from an ongoing longitudinal study.

Other Elements ° Number of studies There are two studies. Low ° Agreement between researchers There is consistency among the two studies. High Overall Rating High


[Federal Register Volume 86, Number 13 (Friday, January 22, 2021)]
[Notices]
[Pages 6694-6700]
[FR Doc No: 2021-01341]

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SECURITIES AND EXCHANGE COMMISSION

[Release No. 34-90932/January 15, 2021]

Order Making Fiscal Year 2021 Annual Adjustments to Transaction
Fee Rates

I. Background

    Section 31 of the Securities Exchange Act of 1934 (``Exchange
Act'') requires each national securities exchange and national
securities association to pay transaction fees to the Commission.\1\
Specifically, Section 31(b) requires each national securities exchange
to pay to the Commission fees based on the aggregate dollar amount of
sales of certain securities (``covered sales'') transacted on the
exchange.\2\ Section 31(c) requires each national securities
association to pay to the Commission fees based on the aggregate dollar
amount of covered sales transacted by or through any member of the
association other than on an exchange.\3\
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    \1\ 15 U.S.C. 78ee.
    \2\ 15 U.S.C. 78ee(b).
    \3\ 15 U.S.C. 78ee(c).
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    Section 31 of the Exchange Act requires the Commission to annually
adjust the fee rates applicable under Sections 31(b) and (c) to a
uniform adjusted rate.\4\ Specifically, the Commission must adjust the
fee rates to a uniform adjusted rate that is reasonably likely to
produce aggregate fee collections (including assessments on security
futures transactions) equal to the regular appropriation to the
Commission for the applicable fiscal year.\5\
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    \4\ In some circumstances, the SEC also must make a mid-year
adjustment to the fee rates applicable under Sections 31(b) and (c).
    \5\ 15 U.S.C. 78ee(j)(1) (the Commission must adjust the rates
under Sections 31(b) and (c) to a ``uniform adjusted rate that, when
applied to the baseline estimate of the aggregate dollar amount of
sales for such fiscal year, is reasonably likely to produce
aggregate fee collections under [Section 31] (including assessments
collected under [Section 31(d)]) that are equal to the regular
appropriation to the Commission by Congress for such fiscal
year.'').
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    The Commission is required to publish notice of the new fee rates
under Section 31 not later than 30 days after the date on which an Act
making a regular appropriation for the applicable fiscal year is
enacted.\6\ On December 27, 2020, the President signed into law the
Consolidated Appropriations Act, 2021, which includes total
appropriations of $1,926,162,000 to the SEC for fiscal year 2021.
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    \6\ 15 U.S.C. 78ee(g).
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II. Fiscal Year 2021 Annual Adjustment to the Fee Rate

    The new fee rate is determined by (1) subtracting the sum of fees
estimated to be collected prior to the effective date of the new fee
rate \7\ and estimated assessments on security futures transactions to
be collected under Section 31(d) of the Exchange Act for all of fiscal
year 2021 \8\ from an amount equal to the regular appropriation to the
Commission for fiscal year 2021, and (2) dividing by the estimated
aggregate dollar amount of covered sales for the remainder of the
fiscal year following the effective date of the new fee rate.\9\
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    \7\ The sum of fees to be collected prior to the effective date
of the new fee rate is determined by applying the current fee rate
to the dollar amount of covered sales prior to the effective date of
the new fee rate. The exchanges and FINRA have provided data on the
dollar amount of covered sales through November, 2020. To calculate
the dollar amount of covered sales from December, 2020 to the
effective date of the new fee rate, the Commission is using the same
methodology it used in fiscal year 2020. This methodology is
described in Appendix A of this order.
    \8\ OneChicago, LLC, the only reporting entity for single stock
futures, ceased operations in September, 2020; its last R-31 report
was filed in October, 2020. Accordingly, the forecast for the
assessments for all of fiscal year 2021 for single stock futures is
the reported assessments on single stock futures from September,
2020 by OneChicago, LLC.
    \9\ To estimate the aggregate dollar amount of covered sales for
the remainder of fiscal year 2021 following the effective date of
the new fee rate, the Commission is using the same methodology it
used previously. This methodology is described in Appendix A of this
order.
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    As noted above, the Consolidated Appropriations Act, 2021, includes
total appropriations of $1,926,162,000 to the Commission for fiscal
year 2021.\10\ The

Commission estimates that it will collect $1,514,646,590 in fees for
the period prior to the effective date of the new fee rate and $494 in
assessments on round turn transactions in security futures products
during all of fiscal year 2021. Using the methodology described in
Appendix A, the Commission estimates that the aggregate dollar amount
of covered sales for the remainder of fiscal year 2021 to be
$81,081,356,203,186.
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    \10\ The President signed into law the ``Consolidated
Appropriations Act, 2021'' on December 27, 2020. This legislation
included an appropriation of $1,894,835,000 to the SEC for fiscal
year 2021 operations. The Act further directed that ``[i]n addition
to the foregoing appropriation, for move, replication, and related
costs associated with a replacement lease for the Commission's
District of Columbia headquarters, not to exceed $18,650,000, to
remain available until expended; and for move, replication, and
related costs associated with a replacement lease for the
Commission's San Francisco Regional Office facilities, not to exceed
$12,677,000, to remain available until expended.'' The sum of these
three amounts is $1,926,162,000. Finally, the Act further directed
that ``for purposes of calculating the fee rate under section 31(j)
. . . all amounts appropriated under this heading shall be deemed to
be the regular appropriation to the Commission for fiscal year
2021.''
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    The uniform adjusted rate is computed by dividing the residual fees
to be collected of $411,514,917 by the estimated aggregate dollar
amount of covered sales for the remainder of fiscal year 2021 of
$81,081,356,203,186; this results in a uniform adjusted rate for fiscal
year 2021 of $5.10 per million.\11\
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    \11\ Appendix A shows the process of calculating the fiscal year
2021 annual adjustment and includes the data used by the Commission
in making this adjustment.
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III. Effective Date of the Uniform Adjusted Rate

    Under Section 31(j)(4)(A) of the Exchange Act, the fiscal year 2021
annual adjustments to the fee rates applicable under Sections 31(b) and
(c) of the Exchange Act shall take effect on the later of October 1,
2020, or 60 days after the date on which a regular appropriation to the
Commission for fiscal year 2021 is enacted.\12\ The regular
appropriation to the Commission for fiscal year 2021 was enacted on
December 27, 2020, and accordingly, the new fee rates applicable under
Sections 31(b) and (c) of the Exchange Act will take effect on February
25, 2021.
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    \12\ 15 U.S.C. 78ee(j)(4)(A).
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IV. Conclusion

    Accordingly, pursuant to Section 31 of the Exchange Act,
    It is hereby ordered that the fee rates applicable under Sections
31(b) and (c) of the Exchange Act shall be $5.10 per $1,000,000
effective on February 25, 2021.

    By the Commission.
Jill M. Peterson,
Assistant Secretary.

Appendix A

    This appendix provides the methodology for determining the
annual adjustment to the fee rates applicable under Sections 31(b)
and (c) of the Exchange Act for fiscal year 2021. Section 31 of the
Exchange Act requires the fee rates to be adjusted so that it is
reasonably likely that the Commission will collect aggregate fees
equal to its regular appropriation for fiscal year 2021.
    To make the adjustment, the Commission must project the
aggregate dollar amount of covered sales of securities on the
securities exchanges and certain over-the-counter (``OTC'') markets
over the course of the year. The fee rate equals the ratio of the
Commission's regular appropriation for fiscal year 2021 (less the
sum of fees to be collected during fiscal year 2021 prior to the
effective date of the new fee rate and aggregate assessments on
security futures transactions during all of fiscal year 2021) to the
estimated aggregate dollar amount of covered sales for the remainder
of the fiscal year following the effective date of the new fee rate.
    For 2021, the Commission has estimated the aggregate dollar
amount of covered sales by projecting forward the trend established
in the previous decade. More specifically, the dollar amount of
covered sales was forecasted for months subsequent to November 2020,
the last month for which the Commission has data on the dollar
volume of covered sales.\13\
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    \13\ To determine the availability of data, the Commission
compares the date of the appropriation with the date the transaction
data are due from the exchanges (10 business days after the end of
the month). If the business day following the date of the
appropriation is equal to or subsequent to the date the data are due
from the exchanges, the Commission uses these data. The
appropriation was signed on December 27, 2020. The first business
day after this date was December 28, 2020. Data for November 2020
were due from the exchanges on December 14, 2020. As a result, the
Commission used November 2020 and earlier data to forecast volume
for December 2020 and later months.
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    The following sections describe this process in detail.

A. Baseline Estimate of the Aggregate Dollar Amount of Covered
Sales for Fiscal Year 2021

    First, calculate the average daily dollar amount of covered
sales (``ADS'') for each month in the sample (February 2010-November
2020). The monthly total dollar amount of covered sales (exchange
plus certain OTC markets) is presented in column C of Table A.
    The model forecasts the monthly moving average of the average
daily dollar amount of covered sales. Each month's average daily
dollar amount of covered sales is calculated by dividing the total
covered sales for that month (column C of Table A) by the number of
trading days for that month (column B of Table A). These amounts are
shown in column D of Table A. The moving average will span the same
number of months required to be forecast for the remainder of the
fiscal year. The trailing moving average used in the forecast model
is presented in column E of Table A.
    To capture the recent trends in the monthly changes in the
moving averages, calculate the 1-month and 2-month lags of the
trailing moving average shown in column E in Table A. These amounts
are shown in columns F and G, respectively, of Table A.
    Next, model the monthly trailing moving average of ADS as
function of a constant term and the two lagged trailing moving
averages using the ordinary least squares technique.
    Use the estimated model to forecast the trailing moving average
of ADS of the first month after the last available monthly data.
Estimate the trailing moving average of the second month using the
forecasted value of the first month and the actual value of the
month before that. Similarly, estimate the trailing moving average
of the third month using the forecasted values of the two previous
months. Continue in this fashion until the end of the fiscal year.
    The estimate of the trailing moving average ADS for the last
applicable month in the fiscal year is a prediction of the moving
average for those months that need to be predicted. This estimate is
used as the predicted value of ADS for each month in the forecast
period; to obtain the forecast total covered sales for each month,
multiply the predicted ADS by the number of days in each month.
    The following is a more formal (mathematical) description of the
procedure:
    1. Begin with the monthly data for total dollar volume of
covered sales (column C). The sample spans ten years, from February
2010-November 2020.\14\ Divide each month's total dollar volume by
the number of trading days in that month (column B) to obtain the
average daily dollar volume (ADS, column D).
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    \14\ Because the model uses a two period lag in the 9-month
trailing moving average of average daily covered sales, ten
additional months of data are added to the table so that the model
is estimated with 120 observations.
---------------------------------------------------------------------------

    2. For each month t, calculate the 9-month trailing moving
average of ADS (shown in column E). For example, the value for
October, 2011 is the average of the 9 months ending in October,
2011, or February 2011 through October 2011 inclusive.
    3. Calculate the 1-month and 2-month lags of the trailing moving
average. For example, the 1-month lag of the 9-month trailing moving
average for October, 2011 is equal to the 9-month trailing moving
average for September, 2011. The 2-month lag of the 9-month trailing
moving average for October, 2011 is equal to the 9-month trailing
moving average for August 2011. These are shown in columns F and G.
    4. Estimate the model using ordinary least squares:

yt = [alpha] + [beta]1 yt-1 +
[beta]2 yt-2 + ut

    Where yt is the 9-month trailing moving average of
the average daily sales for month t, and yt-1 and
yt-2 are the 1-month and 2-month lags of yt,
and ut representing the error term for month t. The model
can be estimated using standard commercially available

software. The estimated parameter values are a = -3,106,716,928,
b1 = +1.574199, b2 = -0.560507. The root-mean
squared error (RMSE) of the regression is 6,022,194,076.
    5. The predicted value of the 9-month trailing moving average of
the last month to be forecast represents the final forecast of
covered sales for the entire prediction period. This value is shown
in column H. This represents the prediction for August of 2021. To
calculate this value from the model above, one needs the 1-month and
2-month lag of the 9-month trailing moving average ADS, i.e., the 9-
month trailing moving average for June and July. The 9-month
trailing moving average for July is obtained by using the 1-month
and 2-month lags for July, that is, the 9-month trailing moving
averages for June and May. To arrive at all the necessary inputs,
one begins with the first month to be forecast, in this case,
December 2020, and iterates predictions forward until the last month
is predicted. One then multiplies the final predicted 9-month
trailing moving average ADS by the number of days in each month to
arrive at the forecast total dollar amount of covered sales. This is
shown in column I.
    6. For example, for December 2020, using the a, b1,
and b2 parameter estimates shown above, along with the 1-
month and two-month lags in the 9-month trailing moving average ADS
(representing the 9-month trailing moving average ADS for November
and October 2020, respectively), one can estimate the forecast 9-
month trailing moving average ADS for December: -3,106,716,928 +
(1.574199 x 527,000,127,996) + (-0.560507 x 518,017,127,996) =
536,143,950,634.
    7. With the estimated 9-month trailing moving average ADS for
December 2020 calculated above, one can estimate the 9-month
trailing moving average ADS for January, 2021. The estimate obtained
from December becomes the 1-month lag for January, and the 1-month
lag used in the December forecast becomes the 2-month lag for the
January forecast. Thus, the predicted 9-month trailing moving
average ADS for January 2021 is calculated as: -3,106,716,928+
(1.574199 x 536,143,950,634) + (-0.560507 x 527,000,127,996) =
545,503,592,273.
    8. Using the forecasts for December and January, one can
estimate the value for February. Repeat this procedure for
subsequent months, until the estimate for August 2021 is obtained.
This value is 618,941,650,406.\15\ This value is then used to
calculate the final forecast total monthly covered sales for all 9
months from December 2020 through August 2021.
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    \15\ One obtains insignificantly different values using the
rounded parameter estimates shown above. The predicted ADS values
displayed above represents the full precision estimate.
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    9. To obtain the estimate of total monthly covered sales for
each month, multiply the number of trading days in the month, shown
in column B in Table A, by the final forecast 9-month trailing
moving average ADS, shown in column H of Table A. This product is
shown in column I of Table A, and these figures are used to
calculate the new fee rate.

B. Using the Forecasts From A To Calculate the New Fee Rate

    1. Use Table A to estimate fees collected for the period
September 1, 2020 through February 24, 2021. The projected aggregate
dollar amount of covered sales for this period is
$68,536,044,778,746. Actual and projected fee collections at the
current fee rate of $22.10 per million are $1,514,646,590.
    2. Estimate the amount of assessments on security futures
products collected from September 1, 2020 through August 31, 2021.
The only entity reporting assessable security futures products
ceased operations in September, 2020.\16\ Consequently, the
estimated amount of assessments on security futures products
collected from September 2020 through August 2021 is equal to the
amount already reported, which is $493.87.
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    \16\ OneChicago, LLC, the only reporting entity for single stock
futures, ceased operations in September, 2020; its last R-31 report
was filed in October, 2020. Accordingly, the forecast for the
assessments for all of fiscal year 2021 for single stock futures is
the reported assessments on single stock futures from September,
2020 by OneChicago, LLC.
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    3. Subtract the amounts $1,514,646,590 and $493.87 from the
target off-setting collection amount set by Congress of
$1,926,162,000, leaving $411,514,917 to be collected on dollar
volume for the period February 25, 2021 through August 31, 2021.
    4. Use Table A to estimate dollar volume for the period February
25, 2021 through August 31, 2021. The estimate is
$81,081,356,203,186. Finally, compute the fee rate required to
produce the additional $411,514,917 in revenue. This rate is
$411,514,917 divided by $81,081,356,203,186 or 0.00000507533.
    5. Round the result to the seventh decimal point, yielding a
rate of 0.0000051 (or $5.10 per million).
    This table summarizes the estimates of the aggregate dollar
amount of covered sales, by time period. The figures in this table
can be used to determine the new fee rate.

   Table A--Baseline Estimate of the Aggregate Dollar Amount of Sales
------------------------------------------------------------------------
                  Fee rate calculation
------------------------------------------------------------------------
a. Baseline estimate of the aggregate dollar amount of       $58,014,037
 sales, 09/01/2020 to 01/31/2021 ($Millions)............
b. Baseline estimate of the aggregate dollar amount of        10,522,008
 sales, 02/01/2021 to 02/24/2021 ($Millions)............
c. Baseline estimate of the aggregate dollar amount of         1,237,883
 sales, 02/25/2021 to 02/28/2021 ($Millions)............
d. Baseline estimate of the aggregate dollar amount of        79,843,473
 sales, 03/01/2021 to 08/31/2021 ($Millions)............
e. Estimated collections in assessments on security                0.026
 futures products in fiscal year 2021 ($Millions).......
f. Implied fee rate (($1,926,162,000 - $22.10*(a + b)-e)/            5.0
 (c + d)................................................
------------------------------------------------------------------------

----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                Number of
                                                  trading  Total dollar  amount of    Average daily dollar   9-Month trailing moving   1 Month lag of 9-month   2 Month lag of 9-month      Forecast 9-month      Forecast total dollar
                     Month                       days in             sales           amount of sales  (ADS)        average  ADS       trailing moving average  trailing moving average      trailing  moving         amount of sales
                                                  month                                                                                ADS                      ADS                 average  ADS
(A)                                                   (B)                      (C)                      (D)                      (E)                      (F)                      (G)                      (H)                      (I)
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Feb-10........................................         19       $4,969,848,578,023         $261,570,977,791  .......................  .......................  .......................  .......................  .......................
Mar-10........................................         23        5,563,529,823,621          241,892,601,027  .......................  .......................  .......................  .......................  .......................
Apr-10........................................         21        5,546,445,874,917          264,116,470,234  .......................  .......................  .......................  .......................  .......................
May-10........................................         20        7,260,430,376,294          363,021,518,815  .......................  .......................  .......................  .......................  .......................
Jun-10........................................         22        6,124,776,349,285          278,398,924,967  .......................  .......................  .......................  .......................  .......................
Jul-10........................................         21        5,058,242,097,334          240,868,671,302  .......................  .......................  .......................  .......................  .......................
Aug-10........................................         22        4,765,828,263,463          216,628,557,430  .......................  .......................  .......................  .......................  .......................
Sep-10........................................         21        4,640,722,344,586          220,986,778,314  .......................  .......................  .......................  .......................  .......................
Oct-10........................................         21        5,138,411,712,272          244,686,272,013         $259,130,085,766  .......................  .......................  .......................  .......................
Nov-10........................................         21        5,279,700,881,901          251,414,327,710          258,001,569,090         $259,130,085,766  .......................  .......................  .......................
Dec-10........................................         22        4,998,574,681,208          227,207,940,055          256,369,940,093          258,001,569,090         $259,130,085,766  .......................  .......................
Jan-11........................................         20        5,043,391,121,345          252,169,556,067          255,042,505,186          256,369,940,093          258,001,569,090  .......................  .......................
Feb-11........................................         19        5,114,631,590,581          269,191,136,346          244,616,907,134          255,042,505,186          256,369,940,093  .......................  .......................
Mar-11........................................         23        6,499,355,385,307          282,580,668,926          245,081,545,351          244,616,907,134          255,042,505,186  .......................  .......................
Apr-11........................................         20        4,975,954,868,765          248,797,743,438          245,962,553,367          245,081,545,351          244,616,907,134  .......................  .......................
May-11........................................         21        5,717,905,621,053          272,281,220,050          252,146,182,547          245,962,553,367          245,081,545,351  .......................  .......................
Jun-11........................................         22        5,820,079,494,414          264,549,067,928          256,986,436,948          252,146,182,547          245,962,553,367  .......................  .......................
Jul-11........................................         20        5,189,681,899,635          259,484,094,982          258,630,639,500          256,986,436,948          252,146,182,547  .......................  .......................
Aug-11........................................         23        8,720,566,877,109          379,155,081,613          272,824,056,601          258,630,639,500          256,986,436,948  .......................  .......................
Sep-11........................................         21        6,343,578,147,811          302,075,149,896          281,142,635,472          272,824,056,601          258,630,639,500  .......................  .......................
Oct-11........................................         21        6,163,272,963,688          293,489,188,747          285,733,705,770          281,142,635,472          272,824,056,601  .......................  .......................
Nov-11........................................         21        5,493,906,473,584          261,614,593,980          284,891,867,729          285,733,705,770          281,142,635,472  .......................  .......................
Dec-11........................................         21        5,017,867,255,600          238,946,059,790          280,043,577,825          284,891,867,729          285,733,705,770  .......................  .......................
Jan-12........................................         20        4,726,522,206,487          236,326,110,324          278,657,840,812          280,043,577,825          284,891,867,729  .......................  .......................
Feb-12........................................         20        5,011,862,514,132          250,593,125,707          276,248,052,552          278,657,840,812          280,043,577,825  .......................  .......................
Mar-12........................................         22        5,638,847,967,025          256,311,271,228          275,332,741,808          276,248,052,552          278,657,840,812  .......................  .......................

Apr-12........................................         20        5,084,239,396,560          254,211,969,828          274,746,950,124          275,332,741,808          276,248,052,552  .......................  .......................
May-12........................................         22        5,611,638,053,374          255,074,456,972          260,960,214,052          274,746,950,124          275,332,741,808  .......................  .......................
Jun-12........................................         21        5,121,896,896,362          243,899,852,208          254,496,292,087          260,960,214,052          274,746,950,124  .......................  .......................
Jul-12........................................         21        4,567,519,314,374          217,500,919,732          246,053,151,085          254,496,292,087          260,960,214,052  .......................  .......................
Aug-12........................................         23        4,621,597,884,730          200,939,038,467          239,311,422,695          246,053,151,085          254,496,292,087  .......................  .......................
Sep-12........................................         19        4,598,499,962,682          242,026,313,825          239,653,673,143          239,311,422,695          246,053,151,085  .......................  .......................
Oct-12........................................         21        5,095,175,588,310          242,627,408,967          240,353,817,437          239,653,673,143          239,311,422,695  .......................  .......................
Nov-12........................................         21        4,547,882,974,292          216,565,855,919          236,573,009,683          240,353,817,437          239,653,673,143  .......................  .......................
Dec-12........................................         20        4,744,922,754,360          237,246,137,718          234,454,661,515          236,573,009,683          240,353,817,437  .......................  .......................
Jan-13........................................         21        5,079,603,817,496          241,885,896,071          233,085,097,764          234,454,661,515          236,573,009,683  .......................  .......................
Feb-13........................................         19        4,800,663,527,089          252,666,501,426          232,817,547,148          233,085,097,764          234,454,661,515  .......................  .......................
Mar-13........................................         20        4,917,701,839,870          245,885,091,993          233,038,129,346          232,817,547,148          233,085,097,764  .......................  .......................
Apr-13........................................         22        5,451,358,637,079          247,789,028,958          236,403,474,816          233,038,129,346          232,817,547,148  .......................  .......................
May-13........................................         22        5,681,788,831,869          258,263,128,721          242,772,818,178          236,403,474,816          233,038,129,346  .......................  .......................
Jun-13........................................         20        5,623,545,462,226          281,177,273,111          247,122,924,765          242,772,818,178          236,403,474,816  .......................  .......................
Jul-13........................................         22        5,083,861,509,754          231,084,614,080          245,840,392,000          247,122,924,765          242,772,818,178  .......................  .......................
Aug-13........................................         22        4,925,611,193,095          223,891,417,868          246,654,343,327          245,840,392,000          247,122,924,765  .......................  .......................
Sep-13........................................         20        4,959,197,626,713          247,959,881,336          247,844,759,285          246,654,343,327          245,840,392,000  .......................  .......................
Oct-13........................................         23        5,928,804,028,970          257,774,088,216          249,610,113,968          247,844,759,285          246,654,343,327  .......................  .......................
Nov-13........................................         20        5,182,024,612,049          259,101,230,602          250,325,083,876          249,610,113,968          247,844,759,285  .......................  .......................
Dec-13........................................         21        5,265,282,994,173          250,727,761,627          250,863,158,280          250,325,083,876          249,610,113,968  .......................  .......................
Jan-14........................................         21        5,808,700,114,288          276,604,767,347          254,064,906,990          250,863,158,280          250,325,083,876  .......................  .......................
Feb-14........................................         19        6,018,926,931,054          316,785,627,950          260,567,406,904          254,064,906,990          250,863,158,280  .......................  .......................
Mar-14........................................         21        6,068,617,342,988          288,981,778,238          261,434,574,140          260,567,406,904          254,064,906,990  .......................  .......................
Apr-14........................................         21        6,013,948,953,528          286,378,521,597          267,578,341,642          261,434,574,140          260,567,406,904  .......................  .......................
May-14........................................         21        5,265,594,447,318          250,742,592,729          270,561,805,516          267,578,341,642          261,434,574,140  .......................  .......................
Jun-14........................................         21        5,159,506,989,669          245,690,809,032          270,309,686,371          270,561,805,516          267,578,341,642  .......................  .......................
Jul-14........................................         22        5,364,099,567,460          243,822,707,612          268,759,532,970          270,309,686,371          270,561,805,516  .......................  .......................
Aug-14........................................         21        5,075,332,147,677          241,682,483,223          266,824,116,595          268,759,532,970          270,309,686,371  .......................  .......................
Sep-14........................................         21        5,507,943,363,243          262,283,017,297          268,108,033,892          266,824,116,595          268,759,532,970  .......................  .......................
Oct-14........................................         23        7,796,638,035,879          338,984,262,430          275,039,088,901          268,108,033,892          266,824,116,595  .......................  .......................
Nov-14........................................         19        5,340,847,027,697          281,097,211,984          271,073,709,349          275,039,088,901          268,108,033,892  .......................  .......................
Dec-14........................................         22        6,559,110,068,128          298,141,366,733          272,091,441,404          271,073,709,349          275,039,088,901  .......................  .......................
Jan-15........................................         20        6,185,619,541,044          309,280,977,052          274,636,158,677          272,091,441,404          271,073,709,349  .......................  .......................
Feb-15........................................         19        5,723,523,235,641          301,238,065,034          280,246,766,711          274,636,158,677          272,091,441,404  .......................  .......................
Mar-15........................................         22        6,395,046,297,249          290,683,922,602          285,246,001,552          280,246,766,711          274,636,158,677  .......................  .......................
Apr-15........................................         21        5,625,548,298,004          267,883,252,286          287,919,395,405          285,246,001,552          280,246,766,711  .......................  .......................
May-15........................................         20        5,521,351,972,386          276,067,598,619          291,739,963,782          287,919,395,405          285,246,001,552  .......................  .......................
Jun-15........................................         22        6,005,521,460,806          272,978,248,218          292,928,322,773          291,739,963,782          287,919,395,405  .......................  .......................
Jul-15........................................         22        6,493,670,315,390          295,166,832,518          288,059,719,450          292,928,322,773          291,739,963,782  .......................  .......................
Aug-15........................................         21        6,963,901,249,270          331,614,345,203          293,672,734,252          288,059,719,450          292,928,322,773  .......................  .......................
Sep-15........................................         21        6,434,496,770,897          306,404,608,138          294,590,872,186          293,672,734,252          288,059,719,450  .......................  .......................
Oct-15........................................         22        6,592,594,708,082          299,663,395,822          293,522,252,049          294,590,872,186          293,672,734,252  .......................  .......................
Nov-15........................................         20        5,822,824,015,945          291,141,200,797          292,400,378,245          293,522,252,049          294,590,872,186  .......................  .......................
Dec-15........................................         22        6,384,337,478,801          290,197,158,127          292,346,293,303          292,400,378,245          293,522,252,049  .......................  .......................
Jan-16........................................         19        6,696,059,796,055          352,424,199,792          301,739,731,915          292,346,293,303          292,400,378,245  .......................  .......................
Feb-16........................................         20        6,659,878,908,747          332,993,945,437          308,064,881,562          301,739,731,915          292,346,293,303  .......................  .......................
Mar-16........................................         22        6,161,943,754,542          280,088,352,479          308,854,893,146          308,064,881,562          301,739,731,915  .......................  .......................
Apr-16........................................         21        5,541,076,988,322          263,860,808,968          305,376,446,085          308,854,893,146          308,064,881,562  .......................  .......................
May-16........................................         21        5,693,520,415,112          271,120,019,767          298,654,854,370          305,376,446,085          308,854,893,146  .......................  .......................
Jun-16........................................         22        6,317,212,852,759          287,146,038,762          296,515,013,328          298,654,854,370          305,376,446,085  .......................  .......................
Jul-16........................................         20        5,331,797,261,269          266,589,863,063          292,840,176,355          296,515,013,328          298,654,854,370  .......................  .......................
Aug-16........................................         23        5,635,976,607,786          245,042,461,208          287,718,094,178          292,840,176,355          296,515,013,328  .......................  .......................
Sep-16........................................         21        5,942,072,286,976          282,955,823,189          286,913,501,407          287,718,094,178          292,840,176,355  .......................  .......................
Oct-16........................................         21        5,460,906,573,682          260,043,170,175          276,648,942,561          286,913,501,407          287,718,094,178  .......................  .......................
Nov-16........................................         21        6,845,287,809,886          325,966,086,185          275,868,069,311          276,648,942,561          286,913,501,407  .......................  .......................
Dec-16........................................         21        6,208,579,880,985          295,646,660,999          277,596,770,257          275,868,069,311          276,648,942,561  .......................  .......................
Jan-17........................................         20        5,598,200,907,603          279,910,045,380          279,380,018,748          277,596,770,257          275,868,069,311  .......................  .......................
Feb-17........................................         19        5,443,426,609,533          286,496,137,344          281,088,476,256          279,380,018,748          277,596,770,257  .......................  .......................
Mar-17........................................         23        6,661,861,914,530          289,646,170,197          281,366,268,638          281,088,476,256          279,380,018,748  .......................  .......................
Apr-17........................................         19        5,116,714,033,499          269,300,738,605          281,667,477,031          281,366,268,638          281,088,476,256  .......................  .......................
May-17........................................         22        6,305,822,460,672          286,628,293,667          286,288,125,082          281,667,477,031          281,366,268,638  .......................  .......................
Jun-17........................................         22        6,854,993,097,601          311,590,595,346          289,469,766,433          286,288,125,082          281,667,477,031  .......................  .......................
Jul-17........................................         20        5,394,333,070,522          269,716,653,526          290,544,597,917          289,469,766,433          286,288,125,082  .......................  .......................
Aug-17........................................         23        6,206,204,906,864          269,834,995,951          284,307,810,113          290,544,597,917          289,469,766,433  .......................  .......................
Sep-17........................................         20        5,939,886,169,525          296,994,308,476          284,457,548,721          284,307,810,113          290,544,597,917  .......................  .......................
Oct-17........................................         22        6,134,529,538,894          278,842,251,768          284,338,904,987          284,457,548,721          284,307,810,113  .......................  .......................
Nov-17........................................         21        6,289,748,560,897          299,511,836,233          285,785,093,752          284,338,904,987          284,457,548,721  .......................  .......................
Dec-17........................................         20        6,672,181,323,001          333,609,066,150          290,669,859,969          285,785,093,752          284,338,904,987  .......................  .......................
Jan-18........................................         21        7,672,288,677,308          365,347,079,872          301,341,675,665          290,669,859,969          285,785,093,752  .......................  .......................
Feb-18........................................         19        8,725,420,462,639          459,232,655,928          320,519,938,139          301,341,675,665          290,669,859,969  .......................  .......................
Mar-18........................................         21        8,264,755,011,030          393,559,762,430          329,627,623,370          320,519,938,139          301,341,675,665  .......................  .......................
Apr-18........................................         21        7,490,308,402,446          356,681,352,497          339,290,367,701          329,627,623,370          320,519,938,139  .......................  .......................
May-18........................................         22        7,242,077,467,361          329,185,339,426          345,884,850,309          339,290,367,701          329,627,623,370  .......................  .......................
Jun-18........................................         21        7,936,783,802,579          377,942,085,837          354,879,047,793          345,884,850,309          339,290,367,701  .......................  .......................
Jul-18........................................         21        6,807,593,326,456          324,171,110,784          359,915,587,684          354,879,047,793          345,884,850,309  .......................  .......................
Aug-18........................................         23        7,363,115,477,823          320,135,455,558          362,207,100,942          359,915,587,684          354,879,047,793  .......................  .......................
Sep-18........................................         19        6,781,988,459,996          356,946,761,052          364,800,178,154          362,207,100,942          359,915,587,684  .......................  .......................
Oct-18........................................         23       10,133,514,482,168          440,587,586,181          373,160,234,410          364,800,178,154          362,207,100,942  .......................  .......................
Nov-18........................................         21        8,414,847,862,204          400,707,041,057          366,657,388,314          373,160,234,410          364,800,178,154  .......................  .......................
Dec-18........................................         19        9,075,221,733,736          477,643,249,144          375,999,997,948          366,657,388,314          373,160,234,410  .......................  .......................
Jan-19........................................         21        7,960,664,643,749          379,079,268,750          378,488,655,310          375,999,997,948          366,657,388,314  .......................  .......................
Feb-19........................................         19        6,676,391,653,247          351,389,034,381          380,955,732,527          378,488,655,310          375,999,997,948  .......................  .......................
Mar-19........................................         21        7,828,979,311,928          372,808,538,663          380,385,338,397          380,955,732,527          378,488,655,310  .......................  .......................
Apr-19........................................         21        6,907,923,076,080          328,948,717,909          380,916,183,633          380,385,338,397          380,955,732,527  .......................  .......................
May-19........................................         22        7,895,053,976,747          358,866,089,852          385,219,587,443          380,916,183,633          380,385,338,397  .......................  .......................
Jun-19........................................         20        7,070,583,442,058          353,529,172,103          384,839,855,338          385,219,587,443          380,916,183,633  .......................  .......................
Jul-19........................................         22        6,792,811,319,721          308,764,150,896          370,192,806,973          384,839,855,338          385,219,587,443  .......................  .......................
Aug-19........................................         22        8,059,527,400,976          366,342,154,590          366,374,486,254          370,192,806,973          384,839,855,338  .......................  .......................
Sep-19........................................         20        6,958,132,871,506          347,906,643,575          351,959,307,858          366,374,486,254          370,192,806,973  .......................  .......................
Oct-19........................................         23        7,235,982,824,882          314,607,948,908          344,795,827,875          351,959,307,858          366,374,486,254  .......................  .......................
Nov-19........................................         20        6,784,888,230,209          339,244,411,510          343,446,425,334          344,795,827,875          351,959,307,858  .......................  .......................
Dec-19........................................         21        7,252,856,724,647          345,374,129,745          340,398,157,677          343,446,425,334          344,795,827,875  .......................  .......................
Jan-20........................................         21        8,178,172,797,805          389,436,799,895          347,119,055,675          340,398,157,677          343,446,425,334  .......................  .......................
Feb-20........................................         19        8,951,554,790,521          471,134,462,659          359,593,319,320          347,119,055,675          340,398,157,677  .......................  .......................
Mar-20........................................         22       16,218,726,536,159          737,214,842,553          402,225,060,481          359,593,319,320          347,119,055,675  .......................  .......................
Apr-20........................................         21       10,289,596,902,933          489,980,804,902          422,360,244,260          402,225,060,481          359,593,319,320  .......................  .......................
May-20........................................         20        9,435,524,799,540          471,776,239,977          434,075,142,636          422,360,244,260          402,225,060,481  .......................  .......................
Jun-20........................................         22       12,093,857,552,130          549,720,797,824          456,498,937,553          434,075,142,636          422,360,244,260  .......................  .......................
Jul-20........................................         22       10,355,334,352,448          470,697,016,020          473,842,167,232          456,498,937,553          434,075,142,636  .......................  .......................
Aug-20........................................         21        9,763,364,099,611          464,922,099,981          487,806,354,840          473,842,167,232          456,498,937,553  .......................  .......................
Sep-20........................................         21       11,545,568,415,944          549,788,972,188          510,519,115,111          487,806,354,840          473,842,167,232  .......................  .......................
Oct-20........................................         22       10,052,383,756,890          456,926,534,404          518,017,974,501          510,519,115,111          487,806,354,840  .......................  .......................
Nov-20........................................         20       11,039,476,882,364          551,973,844,118          527,000,127,996          518,017,974,501          510,519,115,111  .......................  .......................
Dec-20........................................         22  .......................  .......................  .......................          527,000,127,996          518,017,974,501         $618,941,650,406      $13,616,716,308,932
Jan-21........................................         19  .......................  .......................  .......................  .......................          527,000,127,996          618,941,650,406       11,759,891,357,714
Feb-21........................................         19  .......................  .......................  .......................  .......................  .......................          618,941,650,406       11,759,891,357,714

Mar-21........................................         23  .......................  .......................  .......................  .......................  .......................          618,941,650,406       14,235,657,959,338
Apr-21........................................         21  .......................  .......................  .......................  .......................  .......................          618,941,650,406       12,997,774,658,526
May-21........................................         20  .......................  .......................  .......................  .......................  .......................          618,941,650,406       12,378,833,008,120
Jun-21........................................         22  .......................  .......................  .......................  .......................  .......................          618,941,650,406       13,616,716,308,932
Jul-21........................................         21  .......................  .......................  .......................  .......................  .......................          618,941,650,406       12,997,774,658,526
Aug-21........................................         22  .......................  .......................  .......................  .......................  .......................          618,941,650,406       13,616,716,308,932
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[GRAPHIC] [TIFF OMITTED] TN22JA21.008

[FR Doc. 2021-01341 Filed 1-21-21; 8:45 am]
BILLING CODE 8011-01-P