Document d7D8J4b7y9xR2zaNO1mv2gj0

ASSESSMENT OF BLOOD LEAD LEVELS IN THE U.S.A. FROM NHANESII DATA John M Pierrarcl*, Charles 0 Pfeifer+ and Ronald D Snee+ ABSTRACT Changing demographics of the subject groups at the 64 sites sampled dur ing NHANESII accounts for Over half the apparent 5.61 ug/dl blood lead decrease from 1976 to i960. Site-specific gasoline lead exposure accounts for 0.51 ug/dl of the blood lead decrease, in agreement with the change expected due to the decrease of 0.32 ug/m3 in average air lead and the accepted range 1 ^ ^ 2 for blood lead response to air lead change. INTRODUCTION The U.S. Government's second National Health and Nutritional Examination Survey (NHANESII) was a cross-sectional study designed to assess national health status. Venous blood lead levels (BPb) were measured for 9,936 of the 20,333 examinees. Mobile caravan teams visited 64 sites in the eontinguous U.S.A. and Hawaii between 1976 and 1930. A preliminary analysis reported a 36.7% reduction in BPb over the four-year study period and noted that the decrease in BPb reflects the decrease in national use of lead in gasoline production (ref 1). Because the NHANESII sample was not selected to insure valid vithin-study time analyses, several categories of demographic variables were evaluated in the present study to examine their effect on the reported BPb decline. Three alternative measures of exposure to lead from gasoline were tested for their utility as indicators of BPb response. Finally, time was intro duced to represent all other time-related BPb effects that may be present. ADJUSTMENT FOR DEMOGRAPHICS The effect of changing site demographics on the BPb time trend was inves tigated by classifying each examinee in terms of 6 personal variables (P) describing race, sex, age and family income, 3 residence variables (R) describing degree of urbanization, and 6 caravan itinerary variables (I) describing season of the year and region of the U.S.A. These classifica tion variables assume a value of 1 if the descriptor applies to the exam inee, 0 otherwise. Means were computed for each site based on examinee records with a venous BPb, and the 64 site means further analyzed. Three BPb adjustments were evaluated corresponding to different selection sets of candidate explanatory terms for variation among site mean BPb's. The first set included the 6 P variables and their 15 two-way interactions; the second set added the.3 R variables to the first set; and, the third set added the 6 I variables to the second set, A weighted least squares stepwise regression procedure was applied to each full set of selection candidates. Weighting was by number of BPb values at each site* *E. I. du Pont de Nemours & Co., Inc., Wilmington, DE, USA, Petroleum Laboratory, + Engineering Department TEH 0532782 Terms were retained. If their significance with BPb satisfied the p <0.15 criterion. Adjusted site mean BPb's were obtained by adding the weighted site mean BPb to the residuals from the final regression model. Each adjusted set of values, along with the unadjusted BPb's, then was regressed on site mean examination date. Values of BPb were predicted at the first and last site mean examination date in NHANESII to evaluate the influence of dif ferential site demographics. The results of the time analyses on the unadjusted and adjusted site mean BPb's are given in Table 1. They illustrate the confounding inherent among BPb, site demographics and time during the study period. Each group of demographic variables was able to explain some of the time trend with terms from the third selection set reducing the unadjusted decrease by more than half. Table 1 Time Trend and Four Year Change of Blood Lead Unadjusted and Adjusted for Demographics Unadjusted Adjusted for P for P and R for P, R and 1 Time Trend Std. ug/dl/yr Error -1,43 0.18 -1.09 -0.74 -0.57 0.18 0.17 0.14 Remaining Four Year Decrease BPb. ug/dl % 5.61 32.7 4.29 2.92 2.26 26,0 18.4 14.5 ADJUSTMENT FOR GASOLINE LEAP AND DEMOGRAPHICS Gasoline lead (GPb) is the best documented of the identified sources of lead which include food, water, paint and dust. National GPb use has been claimed to explain the decrease in unadjusted BPb (ref 2), and so was eva luated as one GPb exposure variable. National GPb use (tonnes) was com puted from data by state on lead content and consumption of gasoline. To reflect site to site variation,- a GPb density (tonnes/rai^) for each site was computed by multiplying the relevant state GP use by the ratio of population in the site counties to state population, and dividing by land area of the site counties. The basis for this definition is the correla tion between population and gasoline use (ref 3). Subsite GPb density was calculated similarly but based on each BPb examinee's residence char acteristics, Applicable data permitted calculation of all 3 GPb exposures for 55 of the original 64 sites. Mean BPb's from the 55 sites were adjusted as before for 5 selection sets, each containing all of the P,R and I demographic terms and one of the GPb exposure variables or its logarithm. The adjusted BPb's then were regres sed bn site mean examination date. These results, along with the signifi cance levels of the GPb exposure terms, are given in Table 2, In all cases inclusion of a GPb term further reduced the BPb decrease from the 2.26 ug/dl unaccounted for by demographics. The remaining trend was con sistent for all but national GPb use. TEH 0532783 DUP050034053 Table 2 Time Trend and Four Tear Change of Blood Lead Adjusted for Demographics and Gasoline Lead Exposure GPb Exposure Variable Signif. Level P National 4 o.oooi Site Density 0.0001 Subsite Density 0.0311 Log (Site Density) 4 0.0001 Log (Subsite Density) 0.1076 Time Trend Std. ug/dl/yr Error -0.14 -0.44 -0.47 -0.52 -0.39 0.12 0.13 0.12 0.13 0.13 Remaining Four Tear Decrease BPb. ue/dl % 0.57 1.75 1.85 2.05 1.55 3.8 11.3 11.9 13.1 10.1 TIME-RELATED BLOOD LEAD EFFECTS In the absence of credible and suitable data on lead sources besides gaso line* a time variable, reflecting site mean examination date* was adopted as a surrogate for other time-related BPb effects. A stepwise regression procedure was used on each of 5 selection sets again containing the full set of demographic terms, one of the GPb exposure variables and the sur rogate* time. First* the model was forced to include both time and the GPb variable used; in companion analyses the selection of all terms was allowed to proceed solely on the basis of the inclusion criterion. As shown in Table 3* under both forced and unforced conditions the time vari able was significant for all cases* but only Site GPb Density retained significance. When time is taken into account as a surrogate for un quantified time-related BPb effects, national GPb use is no longer signi ficant. These results suggest other time-related BPb effects are present in NHANESII. Table 3 Significance Levels of Gasoline Lead Exposure and Time Terms in Models Including Demographics GPb Exposure Variable Forced______ GPb Signif. Level Time Signif. Level _____ enforced GPb Signif. Level Time Signif. Level National Site Density Subsite Density Log (Site Density) Log (Subsite Density) 0.8850 0.0022 0.6276 0.0019 0.7520 4 o.oooi 0.0001 0.0001 0.0001 0.0001 . NS 0,0022 NS 0.0019 NS 0.0001 0.0001 0.0001 0.0001 0.0001 NS = Not Selected, p> 0.15 TEH 0532784 DUP050034054 CONCLUSIONS This analysis has shown that many factors related to personal and resi dence characteristics and sampling itinerary significantly affect NHANESII BPb values, and can account for 3.35 ug/dl of the apparent decrease be tween 1976 and 1980. Of the GPb exposure variables only Site GPb Density and its logarithm had a significant effect on BPb in the presence of the time surrogate. The portion of the four-year decrease due to Site GPb Density was determined by the analysis to be 0,5 tig/dl. This is consis tent with the observed national average air lead decrease of 0.3 ug/m3 over the same period (ref 4), and the well-documented air lead/blood lead relationship (ref 5,6), Figure 1 shows the relative contributions to the four-year blood lead decrease. The unexplained portion of the BPb decrease, 1.75 ug/ dl, is reflected by the time variable and may be due to improved sample handling over the course of the NHANESII study, effectiveness of numerous government programs to reduce lead intake through food, paint and water (ref 7), or other unquanti fied causes. REFERENCES 1. Centers for Disease Control, Morbidity and Morality Weekly Rep 30, 132 (1982) 2. New Scientist, 94, 570 (1982) 3. J M Pierrard et al. Vehicle Emissions Controls and Ambient Air Quality, SAE Australasia, Jubilee Year Conference, Melbourne (1977) 4. EPA Office of Air Quality Standards, National Trend in the Maximum Quarterly Average Lead Levels, 1970-1979 5. R D Snee, Int Arch Occup Environ Health 48, 219 (1981) 6. W Sinn, Int Arch Occup Environ Health 47, 93 (1980) and 48, (1981) 7. National Academy of Sciences, Lead In the Human Environment Washington, D.C, 1980) p. 477 DUP050034055 TEH 0532785 rvi i-vCfa'tCi'iii. J. r o-> NHANES II WEIGHT DECK (One record for each SP) V'vVJ^ Item Tape No, of Position Positions Source and Description Sample Number Deck Number Segment Number Serial Number Column Number Examination Status 1-Examined 2-Not Examined Age at Interview months(6-ll mos.) years(01-74 yrs.) Race 1-White 2-Black 3-Other Sex 1-kfele 2-Female Family Income Group 11-Under $1,000 (includ12-$1,000-1,999 ing 13-$2,000-2,999 14-$3,000-3,999 15-$4,000-4,999 16-$5,000-5,999 17-$6,000-6,999 18-$7,000-9,999 19-$10,000-14,999 20-$15,000-19,999 21-$20,000-24,999 22-$25,000-and over 88-Unknown Family Income Recode 1-5 6-8 9-12 13-14 15-16 17 18-19 20-21 22 23 24-25 26 5 3 4 2 2 1 2 2 1 1 2 PSU Number 27- 29 SMSA-NDNSMSA Code 30 1-In SMSA in central city 2-In SMSA not in central city 4-Not in SMSA 3 1 Deck 371, cols. 1-5 502 Deck 371, cols, 16-19 Deck 371, cols, 20-21 Deck 371, cols. 43-44 Deck 371, cols. 36 Deck 371, cols, 45-46 Deck 371, cols. 47-48 Deck 371, col. 56 Deck 371, col. 55 Deck 371, cols. 107-108 Recode Description 1 less tnan $6,000 2 $6,000-$9,999 3 $10,000-14,999 4 $15,000-24,999 5 $25,000 + 8 Unknown Deck 371, cols, 13-15 Deck 371, col. 12 TEH 0532786 DUP050034056 DECK 502 - CONTINUED * Iters Tape No, o Position Positions Source and Description Region code 31 1-Northeast 2-Midwest 3-South 4-West Medical History Interview Status 32 1-Completed 2-Not completed Education Group 33-34 00-None 21-28-Elementary grades(l-8) 31-34-High School (1-4) 41-45-College (1-5+) 88-Blank, but applicable Education level Recode* 35 1 1 2 1 l)Poverty-Nonpoverty Segment 2) PSU to Super Stratum Weight 3) Segment to PSJ Weight 4) Total Weight 5) Special Census Weight 6) Individual (HH) Sub- sampling Weight 7) Basie Weight 36 37-43 44-51 52-60 61-65 66-69 70-79 1 7 8 9 5 4 10 9) Nonresponse Adjustment Factor for Medical History Interview Persons 81-88 8 *Odd digit in segment ntBsber column (column 12) *Even digit in segment number column (column 12) Deck 371, col. 209 Deck 371, col. 208 Deck 371, cols. 62-63 Recode 1 2 3 4 5 9 Description Grade 5 or less Grades 6-11 Grade 12 1-4 yrs.college 4+ yrs.college Unknown 1* - nonpoverty 2* - poverty (xxx.xxxx) - Table 1 (xxxx.xxxx) - Table 1 (xxxxx.xxxx) - Product of (2)'(3) (x.xxxx) - Table 2,3,4 or 5 (x.xXx) (xxxxxx.xxxx)-Product of (4)' (5)*(6) (xx.xxxxxx) h TEH 0532787 DUP050034057 PECK 502 - CONTINUED Item Tape No. of Position Positions Source and Description 10) Medical History Inteviewed weight adjusted for nonresponse 11) Population Control Factor 12) Medical History Interview _ final Weight 13) Nonresponse Adjustment Factor for examined person*; 14) Examined weight adjusted for nonresponse 15) Population Control Factor 16) Examined Final Weight 17) Special Test Specific Weights A. GIT Sub-sampling Weight irCTT Basic Weight 89-96 97-103 104-109 110-117 118-125 126-132 133-138 139 140-149 2. GTT Nonresponse adjustment factor 3. GTT Basic Weight adjusted for nonresponse 4. GTT Population control factor 5. GTT Final Examined Weight ' B. Lead Sub-sampling Weight 1. Lead Basic Weight 150-157 158-165 166-172 173-178 179 180-189 2. Lead nonresponse adjustment factor 3. Lead Basic Weight adjusted for nonrespnse . 4. Lead Population control factor 5. Lead Final Examined Weight 190-197 198-205 206-212 213-218 8 7 6 8 8 7 6 1 10 8 8 7 6 1 10 8 8 7 6 (xxxxxxx.x)-Product of (7)'(9) (x.xxxxxx) (xxxxxx)-Product of (10)*(11) (xx.xxxxxx) (xxxxxxx.x)-Product of (7)`(13) (x.xxxxxx) (xxxxxx)-Product of (14)*(15) 0 or 2 depending on sub-sampling (xxxxxx.xxxx)-Product of (7j* (17A) (xx.xxxxxx) (xxxxxxx.x)-Product of (17A1)` (17A2) (x.xxxxxx) (xxxxxx) - Product of (17A3)* (17A4) 0,1,or 2 depending on sub-sampling (xxxxxx.xxxx)-Product of (7)* (17B) (xx.xxxxxx) (xxxxxxx.x)-Product of (17B1)* (17B2) (xxxxxx)-Product of 17B3)* (17B4) s TEH 0532788 DUP050034058 DECK 502 - CONTINUED Item Tape No. of Position Positions Source and Description Carboxyhemoglobin Sub- sampling weight 219 1. Carboxyhemoglobin 220-229 Basic Weight 2. Carboxy - nonresponse 230-237 adjustment factor 3. Carboxy - Basic Weight 238-245 adjusted for nonresponse 4. Carboxy - Population 246-252 Control Factor 5, Carboxy - Final Examined 253-258 Weight Bile Acids Sub-sampling Weight 259 1. Bile Acids Basic 260-269 Weight 2. Bile Acids nonresponse 270-277 adjustment factor 3. Bile Acids Basic Weight 278-285 adjusted for nonresponse 4. Bile Acids population 286-292 control factor 5, Bile Acids Final 293-298 Examined Weight Pesticides Sub-sampling 299 Weight------ 1. Pesticides Basic Weight 300-309 2. Pesticide nonrespnse adjustment factor 310-317 3. Pesticide Basic Weight 318-325 adjusted for nonresponse 4. Pesticide Population 326-332 Control Factor 5. Pesticides Final 333-338 Examined Weight 1 10 S 8 7 6 1 10 8 8 7 6 1 10 8 8 7 6 0 or 2 depending on sub-sampli: (xxxxxx.xxxx)-Product o (7V (17C) (xx.xxxxxx) (xxxxxxx.x)-Product of (17C1)* C17C2) (x.xxxxxx) (xxxxxx)-Product of (17C3)* (17C4) 0 or 2 depending on sub-sampli] (xxxxxx.xxxx)-Product of (7J` (17D) (xx.xxxxxx) (xxxxxxx.x)-Product of (17D1)` (17D2) (x.xxxxxx) (xxxxxx)-Product of (17D3)* (17D4) 0, 1, or 2 depending on sub-sampling (xxxxxx.xxxx)-Product of (7)* (17E) (xx.xxxxxx) (xxxxxxx.x)-Product of (17E1)' (17E2) (x.xxxxxx) (xxxxxx)-Product of (17E3)' (17E4) TEH 0532789 DUP050034059 ATTACHMENT 2 Income Imputation Table for Examinees Whose Income is Not Known (To be used only for HANES II Weighting) Education Completed Grade 5 or less Grade 6-11 4 Yrs. of High School 1-4 Yrs. College 4 + Yrs. College Unknown Poverty Segment $6,000 6,000-9,999 10,000-14,999 15,000-24,999 25,000 + 6,000 NonPoverty Segment $6,000-9,999 10,000-14,999 15,000-24,999 25,000 + 25,000 + 6,000-9,999 N33851.02 -H TEH 0532790 DUP050034060 XTfTOtTnp TT i'lT J. i. INSTRUCTIONS FOR OBTAINING FINAL INTERVIEWED AND EXAMINED PERSON WEIGHTS I. Construct Deck 502 - HANES II Weight Deck (one record for each sample person - SP) according to the attached format. (Attachment 1) II. For each record enter in column 36 a poverty-nonpoverty segment code. If a record contains an odd digit (nonpoverty) in column 12, then enter a "l" in column 36. If a record contains an even digit (poverty) in column 12, then enter a "2" in column 36. f III. For each record enter in columns 37-43 the PSU to Super Stratum Weight (table 1) according to the PSU of each record. f IV. For each record enter in columns 44-51 the Segment to PSU weight (table 1) according to the poverty-nonpoverty segment code for each record, i.e. - if column 36 contains a "l", then enter in columns 44-51 the non-poverty/new construction segment to PSU weight; if column 36 contains a M2", then enter in columns 44-51 the poverty ' segment to PSU weight. V. For each record enter in columns 52-60 the product of item (2) . item (3).* *A11 products should be rounded to the indicated precision and not truncated. 1 TEH 0532791 DUP050034061 For each record enter in columns 61-65 the special census weights (tables 2-5) according to the following: A. Table 2 - for each record containing the stand (columns 1-2), PSU, segment, and serial numbers listed, enter the weight given; B. Table 3 - for each record containing the stand (columns 1-2), PSU, and segment numbers listed, enter the weight given; C. Table 4 - for each record containing the stand, PSU, and segment numbers listed, enter the weight given; D. Table 5 - for each record containing the stand, PSU, and segment numbers listed, enter the weight "zero'1. Special Note 1: Under the segment number column "none" means that none of the segments in that stand and PSU should have a weight of zero. Special Note 2: For any stand, PSU, and segment number with a prior special weight entry, it should be overridden with the zero weight of table $. Special Note 5; For each record not containing one of the special Census weights from table 2, 3, 4, or 5 above, enter a weight of 1.0000 in columns 61-65. 2 TEH 0532792 DUP050034062 VTT. Pnr (53cb. record enter in columns 66-69 rhs indictdun1 household (UK) sub-sailing weight according to the following: A. If age equals 6 months - 5 years, i.e. if columns 18-19 equals 06-11 then enter 4/3 (1.333) in columns 66-69 or if columns 20-21 equals 01-05 then enter 4/3 (1.333) in columns 66-69; B. If age equals 6-59 years, i.e, if columns 20-21 equals 06-59 then enter 4.000 in columns 66-69; C. If age equals 60-74 years, i.e. if columns 20-21 equals 60-74 then enter 4/3 (1.333) in columns 66-69. VIII. For each record enter in columns 70-79 the basic weight to be calculated as follows: A. Multiply the weight in columns 52-60 by the weight in columns 6165 by the weight in columns 66-69, i.e. item 4 . item 5 . item 6 IX. Task 1 Obtain a distribution of the sums of the sample weights by sex, race, and age, i.e, summation of the basic weight (columns 70-79) by the sex, race, and age groups given in table 1. The sum of the weights for each of the cells should closely approximate the population estimates as of the mid-point of the survey provided to NCHS by Census. H TEH 0532793 DUP050034063 X. Adjustment for Nonresponse The procedure involves two levels of nonresponse adjustment: 1, Level 1 is for non-interviewed (non-completed medical history) persons; 2. Level 2 is for non-examined persons. The adjustments for each level should be made within each of the following age-income classes across stands or PSU's classified by SMSA, Non-SMSA within the 4 Census regions : Age of SP . _______ Under $6,000 $6,000 9,999 Family Income $10,000 * $15,000 - 14,999 24,999 __________ _ $25,000 + 6 mo. - 5 yrs. 6 - 59 yrs. 60 - 74 yrs. SMSA and Non-SMSA stands should be distributed by region as follows: Region Northeast Midwest South West SMSA - s4 Non-SMSA TEH 0532794 DUP050034064 A nonresponse factor should be calculated for 120 different age (3) by income (5) by region (4) by SMSA/Non-SMSA (2) classes: A. Example^ for confuting non-response adjustment factors for non- interviewed (non-completed medical history) persons. For stands classified as SMSA in the Northeast region for SP's 6 months - 5 years of age with family income less than $6,000 calculate the following: - 1. Sum the weights (i.e. the basic weight in columns 70-79) for all sample persons who are in the given age-income group for each stand classified as SMSA in the Northeast region, then sum across all stands classified as SMSA in tiie Northeast region, 2. Sum the weights (i.e. the basic weight in columns 70-79) for all sample persons for whom a medical history interview was completed (i.e. if column 32 equals 1) in the given ageincome group for each stand classified as SMSA in the Northeast region, then sum across all stands classified as SMSA in the Northeast region, 3. Obtain the ratio of (1) to (2) above and enter the result in columns 81-88 for each medical history interviewed sample person in the-given age-income, region-SMSA class. 5 TEH 0532795 DUP050034065 4. Repeat (1), (2), and (3) above for each of the remaining 119 ceils. Note: Unknown income should be imputed for weighting purposes from Attachment 2 using the SP's highest educational level attained. B. Example for computing non-response adjustment factors for nonexamined persons. Consider the same example as in CAD above and calculate the following: 1. The numerator is the same as for (AID above. 2. The denominator i$ the sum of the weights (i.e. the basic weight in columns 70-79) for all examined sample persons (i.e., if column 17 equals 1) in the given age-income group for each stand classified as SMSA in the Northeast region, then sum across all stands classified as SMSA in the Northeast region. 3. Obtain the ratio of (1) to (2) above and enter the result in Columns 110-117 for each examined sample person in the given age-income, region-SMSA class. 4. Repeat (1), (2), and (3D above for each of the remaining 119 cells. H6 TEH 0532796 DUP050034066 Note: unknown income should he imputed for weighting purposes from attachment 2 using the SP's highest educational level attained. XI. Task 2 Obtain a distribution of the nonresponse factors for examined persons (columns 110-1173 and for medical history interviewed persons (columns 81-88). XII. For each medical history interviewed SP record enter in columns 8996 the interviewed weight adjusted for nonresponse, i.e, multiply the basic weight in columns 70-79 (item 7) by the nonresponse adjustment factor for medical history interviewed persons in columns 81-88 (item 9). XIII. Task 3 Obtain a distribution of the nonresponse adjusted weights in columns 89-96 for poverty and nonpoverty persons according to the following size of the weights: < 3,000, 4,000, 5,000, 6,000 ... 60,000, Then sum all the weights and compare with the population estimate in table 1. XIV. For each examined SP record enter in columns 118-125 the examined weight adjusted for nonresponse, i.e, multiply the basic weight in columns 70-79 (item 7) by the nonresponse adjustment factor for examined persons in columns 110-117 (item 13), 7 TEH 0532797 DUP050034067 XV. Task 4 Obtain a distribution of the nonresponse adjusted weights in columns 118-125 for poverty and nonpoverty persons according to the following size of the weights: <3,000, 4,000, 5,000, 6,000 ... 60,000. Then sum all the weights and compare with the population estimate in table 1. XVI. Adjustment to Population Controls. Within each of the 76 cells defined below calculate the population control factor for medical history interviewed persons and for examined persons: Age group (6 months-1 yr. 1, 2, 3, 4, 5, 6, 7, 8-9, 10-11, 12-14, 15-17, 18-19, 20-24, 25-34, 35-44, 45-54, 55-64, 65-74) Sex and race group (male nonblack, male black, female nonblack, female black) Within a cell the population control factor is equal to the U.S. population estimate for that cell (table 1) divided by the sum of the weights adjusted for nonresponse, i.e. for medical history interviewed persons enter in columns 97-103 of each record in a given cell the results of dividing the U.S, population estimate for the cell by the sun of the weights in columns 89-96 for that cell; for s 8 TEH 0532798 DUP050034068 examined persons enter in columns 126-132 of each record in a. given cell the result of dividing the U.S. population estimate for the cell by the sum of the weights in columns 118-125 for that cell. XVII. Task 5 Print out the population control factor for each cell for medical history interviewed persons. XVIII. Task 6 Print out the population control factor for each cell for examined persons. ' . - XIX. Medical History Interview Final Weight For each medical history interviewed person record enter in columns 104-109 the product of columns 89-96 and 97-103, i.e. item 10 by item 11. This product is the final medical history interviewed person weight. XX. Task 7 Obtain a distribution of the above weights (columns 104-109) for poverty and nonpoverty persons according to the following size of the weights: < 3,000,-4,000,. 5,000 ... 100,000; list of weights > 100,000; and sum of final weights for the same cells as in table 1. H TEH 0532799 DUP050034069 XXI. ' Examined Final Weight For each examined person record enter in columns 133-138 the product of columns 118-125 and 126-132, i.e. item 14 by item 15. This product is the final examined person weight. XXII. Task 8 Obtain a distribution of the above weights (columns 133-1381 for poverty and nonpoverty persons according to the following size of the weights: <3,000, 4,000 , 5,000 ... 100,000; list of weights > 100,000; anc. sum of final weights for the same cells as in table 1. XXIII. For each record enter in columns 139-338 special examined test specific weights according to the following: A.. GTT 1. % sample of persons 20-74 years, i.e. if columns 20-21 equals 20-74 and if columns 3-5 equals 600-799 or if columns 20-21 equals 20-74 and if columns 1-5 equals 4285042855 or 42857-42874, then enter in column 139 a weight of 2. For all other records enter a weight of zero in column 139. H10 TEH 0532800 DUP050034070 2. For each GTT sample person enter in columns 140-149 the product of columns 70-79 and column 139, i.e., item 7 by item 17A. 3. Adjustment for nonresponse The adjustment should be made within each of the following age-income classes across stands classified by SMSA, nonSMSA within the 4 Census regions: Age of SP 20-59 yrs. 60-74 yrs. Under $6,000 $6,000 9,999 Family Income $10,000 - $15,000 - 14,999 24,999 $25,000 + Region Northeast Midwest South West SMSA Non-SMSA 11s TEH 0532801 DUP050034071 4. A nonresponse factor should be calculated for 80 different age (2) by income (5) by region (4) by SlSA/non-SMSA (2) classes according to the following: a. Sum the GTT basic weights in columns 140-149 for each GTT sample person within each of the 30 cells defined above:. b. Sun the GTT basic weights in columns 140-149 for each examined (column 17 equals 1) GTT person within each of the 80 cells defined above. c. Obtain the ratio of (a) to (b) above for each of the 80 cells and enter the result in columns 150-157 for each (GTT examined person within a given age-income, regionSMSA cell . 5. For each examined GTT person enter in columns 158-165 the GTT 'basic weight adjusted for nonresponse, i.e., multiply the (ITT basic weight in columns 140-149 (item 17A1) by the GTT nonresponse adjustment factor in columns 150-157 (item 17A2). 6. Adjustment to .Population Controls Within each of the population estimation cells defined in XVI above starting with age 20-24 years calculate the 12s TEH 0532802 DUP050034072 population control factor for all examined GTT persons. Within a cell the pupulaxiuu control factor is equal co die U.S, population estimate for a given cell (table 1) divided by the sum of the GTt basic weights adjusted for nonresponse, i.e., for each examined GTT person enter in columns 166-172 of each record in a given cell the result of dividing the U.S. population estimate for a cell by the sum of the weights in columns 158-165 for a given cell. 7. ' Task 9 r Print out the population control factor for each cell. 8. GTT Final Examined Weight For each examined GTT person enter in columns 173-178 the product of columns 158-165 and 166-172, i.e., item 17A3 by 17A4. 9. Task 10 Obtain a distribution of the weights in columns 173-178 for poverty and nonpoverty persons according to the following size of weights < 3000, 4,000, 5,000.. ,100,000; list of weights >100,000; and sum of GTT final examined weights for the same cells as in table 1 beginning with age 20-24 years. 1$ TEH 0532803 DUP050034073 >___ . ............................................................................ 1. All persons 6 months - ,6 years and h sample of persons 7-74 years, i.e. if columns 18-19 equals 06-11 and columns 3-5 is less than or equal to 099 or if columns 20-21 equals 0102 and columns 3-5 is less than or equal to 099, then enter in column 179 a weight of 1; if columns 20-21 equals 03-06 S' and columns 3-5 equals 100-299, then enter in column 179 a weight of 1; if columns 20-21 equals 07-11 and columns 3-5 equals 101, 103, 105 ... 299 (odd numbers), then enter in column 179 a weight of 2; if columns 20-21 equals 12-74 and columns 3-5 equals 301, 303, 305...799 (odd numbers), then enter in column 179 a weight of 2. 2. For each lead sample person enter in columns 180-189 the product of columns 70-79 and column 179, i.e., item 7 by item 17B. 3. Adjustment for Nonresponse The adjustment should be made within each of the following age-income classes across stands classified by SMSA, nonSMSA within the 4 Census regions: 14 TEH 0532804 DUP050034074 ,- :--. - - Age of SP Under $6,000 $6,000 9,999 Family Income $10,000 - $15,000 - 14,999 24,999 $25,000 + 6 mo. - 5 yrs. 6 - 59 yrs. 60 - 74 yrs. . 'Si Region ' ' ' ' Northeast Midwest South West : - v SMSA Non-SMSA 4. A nonresponse factor should be calculated for 120 different age (3) by income (5) by region (4) by SMSA/non-SMSA (2) classes according to the following: a. Sum the lead basic weights in columns 180-189 for each lead sample person within each of the 120 cells defined above. 15 TEH 0532005 DUP050034075 b. Sum tiie lead basic weights in columns 180-189 for each examined (column 17 equals 1) lead person within each of the 120 cells defined above. c. Obtain the ratio of (a) to (b) above for each of the 120 cells and enter the result in columns 190-197 for each lead examined person, 5. For each examined lead person enter in columns 198-205 the lead basic weight adjusted for nonresponse, i.e., multiply the lead basic weight in columns 180-189 (item 17B1) by the lead nonresponse adjustment factor iri columns 190-197 (item 17B2). 6. Adjustment to Population Controls Within each of the population estimation cells defined in XVI above calculate the population control factor for all examined lead persons. Within a cell the population control factor is equal to the U.S. population estimate for a given cell (table 1) divided by the sum of the lead basic weights adjusted for nonresponse, i.e., for each examined lead person enter in columns 206-212 of each record in a given cell the result of dividing the U.S. population estimate for a cell by the sum of the weights in columns 198-205 for a given cell, s 16 TEH 0532806 DUP050034076 TABLE 1. MIANES I I Popolation Estimates by Sex, Race, and Age a t Interview its*attoi-ssstsi^! O'Oo n o o n o o io c o o ui.o r^iflocors .OtOJOHi .tOOiN^WtolOe-trctsrtgMsoNO>O* C<30OtoppigQc-oUis)* to r^r-p> pP g NHf\Wfrt.'a^tNH.wooe^rt^irtebN iO ro --* I*sj eg rs> t\} pg ra rg to P os t/i to Cl *tS* <N J ,r* O NOON!NN Wnf NlMrtWNHK)t1op \---------- ---- ---------- ---------------------------- ------ - ---------- - - vp co a> o co o^nciooocoouct nwH NVOO^OtOrjNtn*o^-*ssO.OOONCKMrtlrt *c jp N N N ,N N ^ W .ee d Cp N so O S> 00 ^ AAflfkliAltAttAAAikMai.ttAit >P^-KVOtKIH WHUIOOOHNNp- CO oo to < > P*. 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HMftHHHHNtOtO UVX).iftAAA.AAAAAAAM A A ' A .A * OOVOOCOi/l CSJ tOr-('pt-lOsl*9*OOvr^P^*tJ*,0*VLO^J-p.C30 to s <2 * -r n to Nto to rt o sr *^w to n o h to o )OONCOONOiifi O >tf r-S CO ro UO O O to A A A .A .* A A A A A A A ' A A A A A eg CO V f-4 O O to to eg CO HObtOOlAO^NN I vS HOUNWflOQMNOON fsl tf tOOOHOCl p 00 V5 tO (O M) h> it t0 P tO .00 t0 HON A A A A A A A A A A .. A. A A^AAA.A aT 1 e-t *H < tO tO l/> \ tO P |/J eH t-l p P 2 o> s H 1-H5Of r^egtPmOo-o4iNpevgifpitNoPNio*UPto)PitooPt.oPNrrg>t>oOi^Acroitoo e0g0 A to 00A pin to v h AAAAAA AAAAAAAAAAA icsnrcto*ttcooHtpoieoagwtc-fo* pPo.t'eOog <lTO-4 reNgt-tNionhiNo.oi'oot*oo-rotro>rt00f to rt >s s>u lAVMAtOnMWMMtfl I s* WV*WWfcMtlhb Wt-4 t v*<t4MdjSoojai<>ad>dr3tcoi : in in u> <n tn a >. x >. >> >* >. >s >* >. >* IS w g^4 I<4a M a Q>)**-t^et-p-.ptp****-^-'**'^ ; >s 0^ >s9X 9X.0>S0XOt HoX tHgImHIHoo.INOSitOm1 tmtWl mSmO* mSt tH.Nf|,),(M0P>HHiHHNNtO4tLO TEH 0532807 DUP050034077 7. Task 11 Print out the population control factor for each cell 8, Lead Final Examined Weight For each examined lead person enter in columns 213-218 the product of columns 198-205 and 206-212, i.e., item 17B3 by item 17B4. 9. Task 12 Obtain a distribution of the weights in columns 213-218 for poverty and nonpoverty persons according to the following size of tile weights: < 3,000, 4,000, 5,000 ...100,000; list of weights > 100,000; and sum of lead final examined weights for the same cells as in table 1. C. QVBBQXyHBtoGLOBIN 1. h sample of persons 3-74 years, i.e. if columns 20-21 equals 03-74 and columns 3-5 equals 100, 102, 104 ...798 (even numbers between 100-798), then enter in column 219 a weight of 2. For all other records enter a weight of zero in column 219. 2. For each carboxyhemoglobin sample person enter in column 220-229 the product of columns 70-79 and column 219 i.e. item 7 by item 17C. H 17 TEH 0532808 DUP050034078