soil, as the soil lead threshold increases, the number of newer homes
meeting the criteria for bare soil decreases faster than the older
homes.  In fact, practically no newer homes (1960-1998) have lead in
bare soil above 1,200 ppm, and less than 4 percent have soil lead above
400 ppm.  Thus, the data suggest that older homes have higher bare soil
lead levels than new homes.  Since the amount of lead added to
commercial residential paint declined from 1940 to 1980, these
observations are not unreasonable, and have been reported by others.

Table 6.2	Distribution of Maximum Bare Soil Sample Lead Concentration
by Construction Year (All Sampled Locations)

Bare Soil Lead Concentration	Number of HUs (000)a	Percent of HUs (%)b

	Before 1940	1940 - 1959	1960 – 1977	1978 - 1998	Before 1940	1940 -
1959	1960 - 1977	1978 - 1998

GEc 0 ppm	12,015	16,843	23,185	25,845	69%	82%	83%	87%

GE 20 ppm	12,015	15,404	17,345	10,350	69%	75%	62%	35%

GE 50 ppm	11,193	12,789	10,437	5,603	64%	62%	37%	19%

GE 200 ppm	7,243	6,073	1,793	190	41%	30%	6%	1%

GE 400 ppm	5,148	3,736	1,111	0	30%	18%	4%	0%

GE 1,200 ppm	3,386	2,886	0	0	19%	14%	0%	0%

GE 1,600 ppm	2,006	1,894	0	0	12%	9%	0%	0%

GE 2,000 ppm	1,320	1,804	0	0	8%	9%	0%	0%

GE 5,000 ppm	1,106	475	0	0	6%	2%	0%	0%

Missingd	145	0	0	0	1%	0%	0%	0%

No Bare Soil	4,313	2,762	4,613	3,724	25%	13%	17%	13%

No Soil 	1,003	939	95	205	6%	5%	0%	1%

Total	17,476	20,544	27,893	29,774	100%	100%	100%	100%

a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	All percentages are calculated with total housing units of that age as
the common denominator.

c	GE equals “greater than or equal to.”

d	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
soil” means that there was no soil on the property to sample.

Figure 6.2 presents a series of boxplots showing the distribution of
soil lead concentrations at each of the seven sample sites.  The last
two boxplots represent only the data collected during the supplemental
data collection from play areas.  As with paint lead and dust lead
loadings, soil lead concentrations are extremely skewed with over
three-fourths of the samples under 200 ppm, but some samples are well
above 1,000 ppm.

Table 6.3 presents selected parameters of the distributions of soil lead
concentrations by sample sites, corresponding to the first five boxplots
in Figure 6.2.  Table 6.3 also presents geometric means and standard
deviations.  As with the distributions of paint lead loadings and dust
lead loadings, the distribution of soil lead concentrations is
right-skewed.  Thus, a normal distribution would not be a suitable model
for the distribution.  A lognormal distribution would be a more suitable
distribution.  Appendix C includes a discussion of modeling these data.

Figure 6.2	Box Plots for Lead in Soil Samples by Sample Site

a 	The box in the box plot represents the middle 50 percent of the data;
the bottom of the box gives the 25th percentile; the top of the box
gives the 75th percentile, and the horizontal line inside the box gives
the median or 50th percentile.  The vertical lines extending from the
top and bottom of the box reach to the largest and smallest
observations, respectively, except for outliers.

b	“Wall 1”  refers to the main entrance wall and “Wall 2” refers
to the second, randomly-selected wall.

Table 6.3	Estimated Empirical Distribution Parameters of Soil Lead
Concentrations by Sample Site

	Main Entry	Wall 1 Dripline	Wall 2 Dripline	Wall 1 Midyard	Wall 2
Midyard

	ppm	ppm	ppm	ppm	ppm

Arithmetic Mean	234.8	242.9	404.1	87.3	123.4

Arithmetic Standard Deviation	1,094.4	817.6	1,612.7	194.7	360.4

Geometric Mean 	43.3	44.5	49.0	28.1	29.9

Geometric Standard Deviationa	5.6	5.8	6.8	4.3	4.9

25th Percentile	12.1	11.4	10.8	7.8	8.5

Median	40.2	38.8	40.3	27.0	29.1

75th  Percentile	133.4	130.7	165.4	76.3	74.2

90th Percentile	433.5	553.5	712.5	209.0	277.0

95th Percentile	1,005.8	1,110.8	1,444.5	411.3	538.8

Number of Samples	707	704	704	723	728

a	The geometric standard deviation is computed as exp(s), where s is the
arithmetic standard deviation of the natural logarithms of the
concentrations (see, e.g., Gilbert, R. O. (1987) Statistical Methods for
Environmental Pollution Monitoring, Van Nostrand Reinhold Company New
York).  For the calculations of the geometric mean and standard
deviation, zero and negative values were set to 5.

6.2	Association between Bare Soil Lead and Exterior Paint Condition

Table 6.4 and Figure 6.3 show the association between bare soil lead
concentration and the condition of the exterior LBP.  Higher bare soil
lead concentrations occur for homes with deteriorated LBP.  An estimated
56 percent ((8%) of homes with intact or minimally-deteriorated LBP have
bare soil lead above 20 ppm, while 73 percent ((19%) of  homes with
significantly deteriorated LBP have bare soil levels above 20 ppm.  Only
4 and 2 percent of homes free of significantly deteriorated LBP have
bare soil lead levels above 1,200 and 2,000 ppm, respectively, while 24
and 13 percent of homes with significantly deteriorated LBP have bare
soil lead levels above 1,200 and 2,000 ppm, respectively.

Table 6.4	Association Between Bare Soil Lead Concentration and Presence
of Significantly Deteriorated Exterior LBP (All Sampled Locations)

Bare Soil Lead	Housing Units without

Any Exterior LBPa,b	Housing Units without

Significantly Deteriorated Exterior LBPa,b	Housing Units with

Significantly Deteriorated Exterior LBPa,b

Percent	Lower

95% CIc	Upper

95% CI

Percent	Lower

95% CI	Upper

95% CI

Percent	Lower

95% CI	Upper

95% CI

GEd0 ppm	83%	78%	88%	83%	77%	88%	73%	55%	92%

GE 20 ppm	49%	41%	56%	56%	48%	63%	73%	54%	92%

GE 50 ppm	28%	20%	36%	38%	30%	47%	67%	51%	83%

GE 200 ppm	5%	1%	9%	13%	9%	17%	39%	19%	58%

GE 400 ppm	3%	0%	5%	8%	5%	11%	30%	11%	49%

GE 1,200 ppm	1%	0%	3%	4%	2%	7%	24%	7%	41%

GE 1,600 ppm	1%	0%	3%	2%	1%	4%	17%	4%	30%

GE 2,000 ppm	1%	0%	2%	2%	0%	4%	13%	2%	24%

GE 5,000 ppm	0%	0%	0%	1%	0%	2%	8%	0%	17%

Missinge	0%	0%	0%	30%	0%	0%	1%	0%	5%

No Bare Soil	14%	10%	19%	15%	11%	20%	22%	3%	41%

No Soil 	3%	0%	6%	2%	0%	4%	4%	0%	9%

Total 	100%

	100%

	100%

a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	The denominators for the percentages are 66,032,000 HUs without any
exterior LBP, 84,215,000 HUs without significantly deteriorated exterior
LBP, and 11,473,000 HUs with significantly deteriorated exterior LBP.

c	CI = 95% confidence interval for the estimated number or percent.

d	GE equals “greater than or equal to.”

e	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
soil” means that there was no soil on the property to sample. Figure
6.3	Association Between Lead in Bare Soil and Deteriorated Exterior
Lead-Based Paint

6.3	Prevalence of Bare Soil Lead in Children’s Play Areas

Table 6.5 presents the number and percentage of housing units with bare
soil lead in children’s play areas above selected concentration
thresholds: 0, 20, 50, 200, 400, 1,200, 1,600, 2,000, and 5,000 ppm.
Figure 6.4 presents the point estimates as a histogram.  An estimated 51
percent ((6%) of homes have bare soil lead levels in play areas above
the limit of detection. An estimated five percent ((3%) of homes with
play areas have soil lead levels above 400 ppm, while an estimated two
percent ((2%) of homes have play area soil lead levels above 2,000 ppm.

Where more than one soil sample was collected from children’s play
areas at a home, the maximum soil value for housing unit has been used
in Table 6.5.  The effect of using the average soil lead for each
housing unit would drive the distribution towards the lower thresholds,
i.e. more homes would have lower soil lead concentrations.

Figure 6.4	Distribution of Maximum Bare Play Area Soil Lead
Concentration

Table 6.5	Distribution of Maximum Soil Lead Concentrations in
Children’s Play Areas

	Number of HUs (000)a	Percent of HUs (%)b

	Bare Play Area Soil Lead

Estimate	Lower

95% CIc	Upper

95% CI

Estimate	Lower

95% CI	Upper

95% CI	HUs in Sample

	GEd0 ppm	76,404	69,826	82,982	80%	73%	87%	294

GE 20 ppm	49,019	42,946	55,092	51%	45%	58%	209

GE 50 ppm	28,878	25,828	31,929	30%	27%	33%	127

GE 200 ppm	10,849	7,899	13,800	11%	8%	14%	101

GE 400 ppm	4,856	2,096	7,616	5%	2%	8%	84

GE 1,200 ppm	2,493	458	4,529	3%	1%	5%	82

GE 1,600 ppm	2,078	92	4,063	2%	0%	4%	80

GE 2,000 ppm	1,777	0	3,871	2%	0%	4%	77

GE 5,000 ppm	380	0	1,231	0%	0%	1%	1

No play area	12,368	6,659	18,077	13%	7%	19%	53

Missinge	6,916	1,862	11,969	7%	2%	13%	23

Total	95,688

	100%

	375

a	“Housing units” are permanently occupied, noninstitutional
residential units in which children are permitted to live.

b	All percentages are calculated with total housing units (95,688) as
the denominator.

c	CI = 95% confidence interval for the estimated number or percent.

d	GE equals “greater than or equal to.”

e	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
soil” means that there was no soil on the property to sample.

Table 6.6 presents the number and percentage of housing units with bare
soil lead concentration in children’s play areas by selected
thresholds, by housing unit construction year.  In general, as the soil
lead threshold increases, the number of homes meeting the criteria
decreases as the housing unit age increases.  In fact, nearly all newer
homes (1960-1998) have bare play area soil lead below 400 ppm.  Thus,
the data suggest that older homes have higher bare play area soil lead
concentrations than new homes.  Since the amount of lead added to
commercial residential paint declined from 1940 to 1980, these
observations are not unreasonable, and have been reported by others.

Table 6.6	Distribution of Maximum Soil Lead Concentrations in
Children’s Play Areas, by Construction Year

	Number of HUs (000)a	Percent of HUs (%)b

Bare Soil Lead Concentration	Before 1940	1940 – 1959	1960 – 1977
1978 – 1998	Before 1940	1940 – 1959	1960 - 1977	1978 – 1998

GEc0 ppm	14,641	15,953	22,536	23,275	84%	78%	81%	78%

GE 20 ppm	14,552	13,074	13,238	8,155	83%	64%	48%	27%

GE 50 ppm	12,562	8,920	4,733	2,664	72%	43%	17%	9%

GE 200 ppm	6,508	2,804	320	1,217	37%	14%	1%	4%

GE 400 ppm	3,325	1,469	62	0	19%	7%	0%	0%

GE 1,200 ppm	1,498	995	0	0	9%	5%	0%	0%

GE 1,600 ppm	1,082	995	0	0	6%	5%	0%	0%

GE 2,000 ppm	872	905	0	0	5%	4%	0%	0%

GE 5,000 ppm	380	0	0	0	2%	0%	0%	0%

No Play Area	613	102	3,410	2,790	13%	22%	7%	13%

Missingd	2,222	4,489	1,947	3,710	4%	1%	12%	9%

Total	17,476	20,544	27,893	29,774	100%	100%	100%	100%

a	“Housing units” are permanently occupied, noninstitutional housing
units in which children are permitted to live.

b	All percentages are calculated with total housing units of that age as
the common denominator.

c	GE equals “greater than or equal to.”

d	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
bare soil” means that there was no bare soil in children’s play
areas on the property to sample.

Table 6.7 shows the association between bare play area soil lead
concentration and the condition of the exterior LBP.  Higher bare soil
lead concentrations occur in play areas for homes with significantly
deteriorated LBP.  An estimated 46 percent ((7%) of homes with intact or
minimally-deteriorated LBP have bare play area soil lead above 20 ppm,
while 89 percent ((11%) of homes with significantly deteriorated LBP
have bare soil levels above 20 ppm.  Only three percent ((3%) of homes
with intact or minimally-deteriorated LBP have bare play area soil lead
levels above 400 ppm, while 18 percent ((12%) of homes with
significantly deteriorated LBP have bare soil lead levels above 400 ppm.

Table 6.7	Association Between Bare Soil Lead Concentration and Presence
of Significantly Deteriorated Exterior LBP, in Children’s Play Areas

Bare Play Area Soil Lead	Housing Units without Significantly
Deteriorated Exterior LBP (%)a,b	Housing Units with Significantly
Deteriorated Exterior LBP (%)a,b

Estimate	Lower

95% CIc	Upper

95% CI

Estimate	Lower

95% CI	Upper

95% CI

GEd0 ppm	79%	71%	86%	90%	79%	100%

GE 20 ppm	46%	39%	53%	89%	77%	100%

GE 50 ppm	24%	20%	29%	73%	55%	91%

GE 200 ppm	8%	4%	12%	35%	17%	53%

GE 400 ppm	3%	1%	6%	18%	6%	30%

GE 1,200 ppm	1%	0%	3%	13%	2%	24%

GE 1,600 ppm	1%	0%	3%	11%	0%	23%

GE 2,000 ppm	1%	0%	2%	10%	0%	23%

GE 5,000 ppm	0%	0%	0%	3%	0%	11%

No Play Areas	14%	7%	20%	7%	0%	17%

Missinge	8%	2%	14%	3%	0%	7%

a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	Percentages are calculated with the number of HUs with and without
significantly deteriorated LBP, 11,472 and 84,216, respectively, as the
denominators.

c	CI = 95% confidence interval for the estimated number or percent.

d	GE equals “greater than or equal to.”

e	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
soil” means that there was no soil on the property to sample.

6.4	Prevalence of Soil Lead in the Rest of the Yard

Table 6.8 presents the number and percentage of housing units with soil
lead in the rest of the yard -- i.e., areas not identified as
children’s play areas -- above selected concentration thresholds: 0,
50, 200, 400, 1,200, 1,600, 2,000, and 5,000 ppm.  An estimated 75
percent ((6%) of homes have bare soil lead levels in the rest of the
yard above the limit of detection.  An estimated 10 percent ((4%) of
homes have soil lead levels above 1,200 ppm in the rest of the yard,
while an estimated 6 percent ((2%) of homes have soil lead levels above
2,000 ppm.

Table 6.8	Distribution of Maximum Soil Lead Concentrations in the Rest
of the Yard

Soil Lead Concentration	Number of HUs (000)a	Percent of HUs (%)b	HUs in
Sample

Estimate	Lower

95% CIc	Upper

95% CI

Estimate	Lower

95% CI	Upper

95% CI

	GEd 0 ppm	90,348	87,218	93,479	94%	91%	98%	323

GE 20 ppm	71,537	65,843	77,230	75%	69%	81%	258

GE 50 ppm	54,250	48,525	59,976	57%	51%	63%	162

GE 200 ppm	27,353	25,438	29,267	29%	27%	31%	116

GE 400 ppm	19,709	16,109	23,310	21%	17%	24%	70

GE 1,200 ppm	9,939	6,435	13,444	10%	7%	14%	53

GE 1,600 ppm	6,220	4,034	8,407	7%	4%	9%	49

GE 2,000 ppm	5,905	3,727	8,083	6%	4%	8%	38

GE 5,000 ppm	2,987	1,548	4,427	3%	2%	5%	17

No Soil/No Bare Soile	2,310	366	4,254	2%	0%	4%	9

Missinge	3,029	693	5,365	3%	1%	6%	12

Total	95,688

	100%

	375

a	“Housing units” are permanently occupied, noninstitutional
residential units in which children are permitted to live.

b	All percentages are calculated with total housing units (95,688) as
the denominator.

c	CI = 95% confidence interval for the estimated number or percent.

d	GE equals “greater than or equal to.”

e	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
soil” means that there was no soil in the rest of the yard to sample.
“No bare soil” means there was no bare soil in the rest of the yard.

Table 6.9 presents the number and percentage of housing units with soil
lead concentration in the rest of the yard by selected thresholds, and
by housing unit construction year.  In general, as the soil lead
threshold increases, the number of homes meeting the criteria decreases
as the housing unit age increases.  In fact, nearly all (91%) homes
built between 1960 and 1977 have bare soil lead concentrations below 400
ppm in the rest of the yard.

Table 6.9	Distribution of Maximum Soil Lead Concentrations in the Rest
of the Yard, by Construction Year

Bare Soil Lead Concentration	Number of HUs (000)a	Percent of HUs (%)b

	Before 1940	1940 - 1959	1960 - 1977	1978 - 1998	Before 1940	1940 –
1959	1960 - 1977	1978 – 1998

GEc0 ppm	15,858	19,372	26,950	28,168	91%	94%	97%	95%

GE 20 ppm	15,858	18,947	24,151	12,581	91%	92%	87%	42%

GE 50 ppm	15,350	17,492	13,509	7,900	88%	85%	48%	27%

GE 200 ppm	13,051	9,524	4,430	348	75%	46%	16%	1%

GE 400 ppm	11,255	5,960	2,410	84	64%	29%	9%	0%

GE 1,200 ppm	6,326	2,926	686	0	36%	14%	3%	0%

GE 1,600 ppm	4,245	1,289	686	0	24%	6%	3%	0%

GE 2,000 ppm	3,929	1,289	686	0	23%	6%	3%	0%

GE 5,000 ppm	1,891	865	231	0	11%	4%	1%	0%

No Soil/No Bare Soile	1,211	939	160	0	7%	5%	1%	0%

Missingd	407	233	783	1,606 	2%	1%	3%	5%

Total	17,476	20,544	27,893	29,774	100%	100%	100%	100%

a	“Housing units” are permanently occupied, noninstitutional housing
units in which children are permitted to live.

b	All percentages are calculated with total housing units of that age as
the common denominator.

c	GE equals “greater than or equal to.”

d	Missing means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).

e	“No soil” means that there was no soil in the rest of the yard to
sample.  “No bare soil” means there was no bare soil in the rest of
the yard.

6.5	Comparison of Prevalence of Soil Lead to the 1990 LBP Survey

Table 6.10 compares the prevalence of soil lead found in the NSLAH with
the prevalence of soil lead found in the 1990 LBP Survey.  The estimate
of homes reported for the NSLAH have been limited to those with 500 ppm
soil lead or greater and to homes built before 1980 for comparability to
the 1990 LBP Survey protocols and findings (see Appendix B for a
comparison of the protocols for the two studies).  Statistical
comparison shows no significant difference in the prevalence of soil
above or below 500 ppm in the two studies.

Table 6.10	Comparison of the Prevalence of Lead-Contaminated Bare Soil
in the NSLAH and the 1990 LBP Survey

	1990 LBP Survey

(pre-1980 HUs)	Current NSLAH

(pre-1980 HUs)

	Number

(000)	Percent

(%)	Number

(000)	Percent

and (CI) a (%)

HUs with Bare Soil Lead

Above 500 ppm	15,699	20%

	15,909	23%

(19-27%)

HUs with Bare Soil Lead

Equal to or Below 500 ppm	61,478	80%

	50,290	73%

(70-77%)

No Bare Soil	--	--	2,557	4%

Total	77,177	100%	68,756	100%

a CI = 95% confidence interval for the estimated percent.

7.  QUALITY OF THE NATIONAL SURVEY DATA

Chapter 7 examines the quality of the data and the resulting quality of
projected national estimates.  The greatest source of error (in the
statistical sense) in the NSLAH estimates is sampling error – as
discussed in Volume II, Chapter 2.  This chapter addresses two
additional important potential sources of error – nonresponse bias and
measurement bias – and discusses their effects on the national
estimates of the prevalence of lead-based paint (LBP), lead in dust, and
lead in soil.

The chapter concludes with a summary of the data collection quality
assurance activities, including results of telephone verification, field
team audits, field dust and soil quality control samples, laboratory
performance on dust and soil quality control samples, and paint testing
quality control.

7.1	Statistical Concepts and Terminology

There are two broad types of error in survey estimates: sampling error
and nonsampling error:

Sampling error:  Sampling error arises from surveying a random sample
rather than a complete census of all housing units (HUs).  It is a
function of the sample size and sample design.  Different samples of the
same size drawn using the same sample design will yield varying
estimates of the population parameters.  This variation about the true
population parameter is the sampling error.

Nonsampling error:  Nonsampling errors arise from a number of sources,
including differential response rates from different demographic groups,
types of HUs, and geographical areas; unknown differences between the
respondents and nonrespondents; differences between the sample frame and
the target population; some types of processing and data reduction
techniques; and classification bias due to measurement error inherent in
XRF and laboratory instrumentation and variation in a measured parameter
across a surface and among rooms.

Throughout the report, the term weight has been used in conjunction with
the sampled HUs, rooms, and surfaces.  It is important that these terms
be understood.

Housing Unit (HU) weight:  The HU weight is the number of HUs in the
target population that a single HU in the survey represents.  The weight
is calculated by taking the inverse of the probability of selection for
that unit.  Thus, if the probability of selection is 0.01, the sample
weight is 100.  With multi-stage samples, the overall probability of
selection is the product of the conditional probabilities of selection
at each stage.  HU weights for this survey reflect nonresponse
adjustments and post-stratification to the 1997 American Housing Survey
(AHS) housing unit totals by Census region, HU age category, and
presence of children under age 18.

Room weight:  The room weight is the number of rooms in the target
population that a single room in the survey represents.  Room weights
were determined by dividing the post-stratified HU weights by the
probability of room selection based on the inventory of all rooms in
each HU.  A nonresponse adjustment was then made to account for
noncompleted rooms. A room was only considered to be complete if some
environmental samples and data were collected in the room.

Component weight:  The component weight is the number of components in
the target population that a single component tested in the survey
represents.  For most lead samples, the component weight equaled the
nonresponse-adjusted room weight.  There were two exceptions: 1) XRF
measurements on windows and doors, and 2) window dust samples.  For
these components, a sample of one door or window per room was selected.
To complete component weights for these components, the
nonresponse-adjusted room weights were divided by the component
probability of selection, i.e., the inverse of the total number of doors
or windows in the room.

7.2	Potential for Nonresponse Bias

The objective of the nonresponse analysis was to estimate the potential
impact of survey nonresponse on the estimated prevalence of LBP in
housing.  To accomplish this, three analyses were conducted.  First, the
weighted distribution of the NSLAH sample was compared and found to be
comparable with the AHS and CPS (this analysis was presented in Chapter
2).  Second, an analysis of completion rates was performed to look for
correlates with nonresponse. Third, the survey estimates for the
“hard-to-recruit” and HUs that initially refused (proxies for the
nonrespondents) were compared with estimates from HUs that were
relatively easy to recruit and had no history of refusal.

7.2.1	Analysis of Completion and Response Rates

An analysis of completion rates was conducted for the entire sample of
1,984 fielded HUs.  The analysis looked at the relationship between
completion rates and factors such as age of housing, race, ethnicity,
geographic location, income, tenure, and presence of multi-family
housing.  Given that these data were generally not available at the
individual HU level for the noncompletes, data for the block group to
which the HU belonged was used for the entire sample, with the exception
of HU age.  The housing unit age reported by respondents was used when
available, which was the case for approximately one-half of the HUs.
The source of the block group data was the 1990 Census.  Completion
rates were also compared for HUs receiving an advance letter addressed
to "Current Resident" and HUs receiving a letter addressed to a
household member.

The completion rates for the analysis were calculated as the weighted
proportion of the HUs sampled that completed both screener and data
collection, or else were found to be ineligible.  Ineligibles were
considered to be screener completes in the sense that their eligibility
status was determined during the screener.  For a large proportion of
the sample (39%), eligibility could not be determined, usually because
contact could not be made.  Most nonresponse occurred at the screener
stage and resulted in unknown eligibility status.  Of the 1,984 HUs
sampled, 831 completed both the screener and data collection and 229
were found to be ineligible.  Of the remaining 924 that did not complete
the data collection, 149 were eligible and another 775 were of unknown
eligibility.  Thus, there were 1,060 completes and 924 noncompletes
overall. The overall unweighted completion rate for the survey was 53.4
percent; the overall weighted completion rate was 53.1 percent.

Formulas for unweighted screener and data collection completion rates
are given below, along with the eligibility rate, refusal rate, and
overall response rate.   The overall completion rate is calculated as
the product of the completion rate at each stage.

The overall response rate measures the response among eligible HUs.  The
number of eligible nonrespondents must be estimated because eligibility
cannot usually be established for households that don’t complete the
screener.  It is assumed that the eligibility rate among HUs whose
eligibility is unknown is the same as for HUs that did complete the
screener.  The eligibility rate among HUs that completed a screener was
81 percent.  The refusal rate is the rate of refusal among HUs where
contact was established.  (Numerous attempts were made to gain
cooperation.  Among respondents, two-thirds cooperated on the first or
second attempt.  While the average number of attempts to complete was
2.6, some housing units didn’t cooperate until the eleventh attempt.)
HUs that were vacant or couldn't be located, that had no one at home,
that were in a locked, gated community where access couldn't be gained,
or that couldn't otherwise be contacted were subtracted from the total
sample size of 1,984 in the denominator.  The overall response rate for
the survey was 51.7 percent.

Overall completion rates by Census Division and block group
characteristics such as race/ethnicity, housing age, and type of housing
are presented in Table 7.1.  Mean percents for several characteristics
by completion status are given in Table 7.2.  For housing age, the
predominant building age category for the block group was assigned to
the HU, except when HU age was available from survey respondents.  It is
important to keep in mind that (with the exception of HU age) the
characteristics apply only to the block group in which the HU is
located, and may not apply to the HU itself.  The associations between
completion status and these characteristics were tested using chi-square
and t-tests that take into account the HU weights and the survey design.

Significant associations were found between completion status and
percents Hispanic and African American, percent below the federal
poverty level, housing age, and tenure (see Table 7.2).  Different
completion rates for groups within a category cannot always be
explained, but could be due to factors such as the use of incentives,
attitudes of householders, etc.  In Table 7.1, the highest response
rates were found among HUs in block groups with 30 percent or more
Hispanic population, 30 percent or more in poverty, and in newer housing
(1978 or later).  The differences in response rates are substantial for
these characteristics, ranging from 9 to 14 percentage points or more
(possibly a function of the $200 incentive having greater value for
these households).  This means that if the lead outcome variables are
correlated with any of these characteristics (such as housing age), a
greater potential for nonresponse bias would exist had these
characteristics not been used in adjusting for nonresponse at the
screener and data collection stages.  Nonresponse adjustment factors
were calculated within cells defined by the block group percent of
low-income population, percent of Hispanic or African American
population, and percent of pre-1940 and pre-1960 housing.  In addition,
the nonresponse-adjusted HU weights were poststratified to 1997 AHS
housing unit totals by Census region, housing unit age, and presence of
a child under 18.  Use of the final adjusted weights in all analyses
therefore greatly reduces this potential bias in estimates for the
national housing stock.

The presence or absence of a household member name on the advance letter
was also significantly correlated with completion rates.  For HUs
located in higher income block groups (i.e. fewer than 30 percent of the
households are below the federal poverty level), the response rate for
HUs with a name on the advance letter was significantly lower (p = .01)
than for HUs receiving a letter addressed to "Current Resident" (48% vs.
56%).  For HUs located in lower income block groups (i.e. more than 30
percent of the households are below the federal poverty level), however,
the completion rates were not significantly different.

Response rates for the play areas sample were also calculated using the
above formula.  Weighted and unweighted response rates were examined in
the same manner, but given the smaller sample size the characteristics
were restricted to Census Region, building age category, and soil lead.
The national response rate for the play areas survey was 79.5 percent
weighted and 78.0 percent unweighted (higher than the national survey
since we were returning to previously willing HUs).  For each subset,
the response rate remained between 71 and 85 percent. None of the
response rate differences observed for the play areas survey were
statistically significant at the alpha = .10 level.

Table 7.1	Completion Rates by 1990 Census Block Group Characteristics

Unweighted	Weighted	P-Value for

	1990 Census

Block Group Characteristic	Number of HUs	Completion

Rate	Completion

Rate	Chi-square testa

	Census Division

	New England	102	52%	53%	0.42

	Middle Atlantic	289	53%	49%

East North Central	289	49%	46%

West North Central	181	55%	55%

South Atlantic	326	52%	53%

East South Central	144	53%	54%

West South Central	208	56%	58%

Mountain	136	57%	58%

Pacific	309	56%	57%

% Hispanic Population

	Less than 30% Hispanic	1832	52%	52%	0.005

	30% or more Hispanic	152	65%	65%

% African American Population

	Less than 30% African American	1731	52%	53%	0.08

	30% or more African American	253	60%	59%

% Population in Poverty

	Less than 30% in Poverty	1796	53%	52%	0.04

	30% or more in Poverty	188	60%	61%

% Multi-family Housing Units (5+)

	Less than 30% Multi-family HUs	1522	53%	53%	0.42

	30% or more Multi-family HUs	462	56%	55%

Age of Housing Unitb

	Pre-1940	456	48%	45%	<0.001

	1940 – 1959	363	59%	60%

1960 – 1977	806	47%	45%

1978 and later	359	70%	74%

a	Chi-square test between completion rate and housing characteristic -
takes into account the HU weights and sample design.

b	Reported HU age used when available for HUs completing screener.

Table 7.2	Mean Percents for Completed and Noncompleted Housing Units by
1990 Census Block Group Characteristics

1990 Census Block Group Characteristic	Mean of Characteristic	P-value
for t-test between completes and noncompletesa

	Completes	Noncompletes

	Percent HUs Pre-1940b	18%	25%	0.001

	Percent Population below Poverty Level	12%	11%	0.080

	Percent Multi-Family HUs (5+)	17%	16%	0.535

	Percent Multi-Family HUs (20+)	7%	7%	0.908

	Percent HUs Owned	63%	66%	0.042

	Percent Population: African American	11%	8%	0.006

	Percent Population: Hispanic	8%	5%	0.005

	a	The test takes into account the HU weights and sample design.

b	HU age reported by respondents was used when available for HUs
completing screener.

7.2.2	Comparison of “Hard-to-Recruit” Versus “Easy-to-Recruit”
HUs

Lead measurements were not available for the HUs whose occupants refused
to participate in the survey or who could not be contacted, so it is not
possible to know how their participation would have changed the
estimates of lead prevalence in housing.  However, if the HUs that
initially refused but later cooperated (or those HUs requiring several
attempts to complete the screener) are similar to the survey
nonrespondents, they may be considered as a proxy group for the
nonrespondents.  If they are significantly different, this may indicate
the likely direction of the nonresponse bias in the lead prevalence
estimates.

The initial refusals were compared with HUs with a history of no
refusal.  HUs requiring 4 or more attempts to complete the screener were
also compared with those requiring 3 or fewer attempts.  The number of
attempts was split at 3-4 for two reasons. Two-thirds of respondents
cooperated on the first or second attempt and the average number of
attempts to complete was 2.6.  The comparisons were made for four key
statistics and by the housing characteristics recorded by the
interviewer.  The statistics were 1) the presence of LBP anywhere in the
home, 2) the presence of deteriorated LBP anywhere in the home, 3)
presence of LBP hazard anywhere in the home, and 4) the presence of a
soil lead hazard.  The housing characteristics were the respondent's
race/ethnicity, household income, tenure, building age, and presence of
a child under 18.  Comparison of whether or not the household had
initially refused (or required more than three attempts to obtain a
completed screener) and these characteristics is presented in Table 7.3.

Table 7.3	Comparison of “Easy-to-Recruit” Respondents Versus
“Hard-to-Recruit” Respondents

National Survey Estimates	Initial Refusal

(%)	p-valuea	More than 3 Attempts to Complete Screener (%)	p-valuea

Presence of LBP anywhere in HU

Yes	9.2	0.60	17.3	0.67

No	10.0

15.1

	Presence of Significantly Deteriorated LBP  anywhere

Yes	6.0	0.05	12.8	0.29

No	10.4

16.7

	Presence of Significant LBP Hazard in HU

Yes	5.6	0.0007	15.8	0.84

No	11.6

16.5

	Presence of Soil-Lead Hazard

Yes	8.7	0.85	6.2	0.29

No	9.9

16.7

	Ethnicity

Hispanic	10.7	0.78	9.6	0.14

Non-Hispanic	9.7

16.8

	Race

White	10.2	0.38	16.9	0.12

African American	6.7

11.7

	Asian, Pacific Islander, Hawaiian, 	8.9

14.4

	American Indian, Other

Presence of Child under 18

Yes	9.9	0.85	15.1	0.31

No	9.5

16.6

	Year of Construction

Pre-1940	7.2	0.22	18.6	0.18

1940 – 1959	6.1

11.5

	1960 – 1977	12.1

13.3

	1978 or later	11.4

20.2

	Tenure (moved up to be w/hsg info)

Owned	11.2	0.03	15.8	0.15

Rented	6.3

16.8

	Type of Housing

Single-family	10.3	0.02	15.4	0.58

Multi-family	5.8

19.9

	Household Income

Less than $30,000	4.7	<0.0001	12.3	0.03

$30,000 or More	11.7

17.8

	Household Income

Less than $20,000	4.7	0.05	11.1	0.02

$20,000 - $39,999	6.8

15.6

	$40,000 - $59,999	10.9

16.8

	$60,000  and over	13.5

18.9

	Poverty

Below Poverty Level	4.6	0.003	9.9	0.005

At or Above Poverty Level	9.8

17.0

	a	Chi-square test of association between Ease of Recruitment and
Reported Housing Characteristics.

Table 7.3 shows that poorer households were much less likely to have an
initial refusal, and required fewer attempts to obtain a completed
screener.  This is consistent with earlier analysis showing higher
response rates for lower income households.  It could be that the
monetary incentive was more effective among lower income households in
improving response rates, or that higher income HUs were more difficult
to contact.

Table 7.3 also shows that households with LBP, significantly
deteriorated LBP, significant LBP hazard, or soil lead hazard were just
as likely to require more than three attempts to complete the screener
as those without these lead characteristics.  While households with LBP
or soil hazards were just as likely to initially refuse as other
households, those with significantly deteriorated LBP or LBP hazards
were significantly more likely to initially refuse than those without
these characteristics.  This could be due to the fact that more lower
income homes participated in the survey and lower income homes are more
likely to have these characteristics.

The nonresponse analysis shows that the households that responded were
more likely to be located in densely Hispanic and low income areas, and
to be renters as opposed to home owners.  They are also more likely to
live in newer housing (post-1977).

If the initial refusals who agreed to cooperate are representative of
nonrespondents, there would be a potential for bias in unweighted
estimated prevalence of HUs with deteriorated LBP or LBP hazards.  This
means that there would be a potential for bias in the estimated
prevalence of HUs with an LBP hazard.  However, this was partially
corrected by using race/ethnicity, low-income indicators, and building
age in making nonresponse adjustments to the HU weights.  The weighting
adjustments do not eliminate nonresponse bias completely, but they do
reduce it when variables that are correlated with both the response
rates and propensity to have a lead hazard are used in the nonresponse
adjustments.  Comparison of the nonresponse-adjusted and poststratified
weighted distribution of housing from the National Survey with the AHS
and CPS in Table 2.1 show that the weighted National Survey sample
matches the national housing distribution closely.  These results
suggest that there is probably not a serious nonresponse bias in the
weighted estimates of lead hazard prevalence.

Completion Rates in the Play Area Subsample

In the play area subsample, 40 of the 75 PSU’s were selected and all
previously completed homes were selected for revisiting.  There were 481
homes in the 40 PSU’s.  Table 7.4 displays the yield in this
subsample.  In the play area subsample, 78 percent of the homes were
completed, either with the collection of a play area soil sample, or the
determination that one was not necessary.

Table 7.4.	Completions in Play Area Subsample

Result	Number of HUs	Percent of HUs

Complete, no soil sample needed	178	37%

Complete, new soil sample collected	197	41%

Total completes	375	78%

No contact made with respondent	54	11%

Refusal	12	2%

Demolished	1	0%

Vacant	27	6%

Other	12	2%

Total Housing Units	481	100%

7.3	Quality of Field Data Collection and Analysis

Quality assurance was integrated into all components of the study,
including a defensible study design, experienced project personnel,
utilization of well-planned, detailed and tested protocols for all
aspects of data collection, thorough study-specific training of
experienced field staff, electronic sample and data management, and
ongoing communication between individuals responsible for each stage of
the study.  These procedures are described in detail in Volume II,
Chapter 6.

Four types of replicate sampling were conducted to estimate measurement
error:  replicate XRF testing of one random component per room,
replicate dust sampling of one surface per home, replicate soil sampling
at a different sample site at every third home, and replicate room
sampling at a subset of homes.  The analyses utilizing these replicate
data and resultant measurement error estimates are presented in Appendix
C.

This section summarizes the results of the various activities focussed
at ensuring quality of the field data collection and laboratory analysis
of the environmental samples.

7.3.1	Field Data Collection

A number of procedures were instituted to ensure quality of the field
data collection, including a manual edit of all data and samples by the
field team, review by the Field Supervisor upon return of the data to
Westat headquarters, and reconciliation of any errors with the field
team prior to submission of any samples to the laboratory.  In addition,
random telephone verification and field team audits were conducted; dust
sample material screens were analyzed; and dust blanks and spike samples
and blind soil reference samples were included in the sample stream.

	Telephone Verification of Data Collection

The Field Director contacted a random subsample of 82 (10%) households
by telephone to verify the team’s activities and conduct and to
validate selected information from the data forms.  No field problems
were identified by this process.

In addition to the random verification process, a number of respondents
and potential respondents utilized the toll-free phone number, or the
HUD phone number, to ask questions, verify the survey, and express
concerns.  All questions or concerns were answered or addressed by the
Field Director or HUD.

	Random Field Audits

The QA Officer or designee, and HUD and NIEHS representatives, conducted
random field audits at 31 households to verify that the protocols were
followed and data collection was accurate and complete.  In addition to
the field audits, the QA Officer conducted 17 telephone audits to
ascertain the team members’ understanding of the protocols, especially
when more than two months had elapsed between assignments.  Problems
noted during these audits were corrected directly with the individual
team members.  In addition, the results of audits were immediately
relayed to the Field Office.  As appropriate, all field staff were
notified by memo of any issues identified with the protocols.

	Lead Dust Wipe Sample Collection

Lead Dust Wipe Materials Screens

The purpose of a materials screen was to verify that the various
sampling supplies to be used in the field did not have lead
contamination.  Two screens were prepared and analyzed for every lot of
wipe materials and sample tubes before being used in the study.  The
analyses showed that all material screens had below 1.5 µg lead.

Field Blank Wipes

One field blank wipe was prepared for each HU at a specified random
sample location where another wipe sample was collected.  All field
blanks were below 50 µg lead/wipe, as specified in HUD Guidelines.
Most field blanks (98+% of all field blanks) had lead levels below the
detection limit for the analytical run (approximately 3.5 µg
lead/wipe).  Of 15 field blanks with lead values above 3.5 µg
lead/wipe, only one blank had more than 20 µg lead/wipe; this wipe had
43 µg lead and was collected in a home with elevated window sill and
trough lead dust levels.  Data from this home were used in the survey
since the blank was still below the 50 µg guideline.

Reference (Spike) Sample Dust Wipes

Reference wipe samples were made in advance of the fieldwork by placing
a known quantity of National Institute of Standards and Technology’s
Standard Reference Material (NIST SRM) 1579a on the same wipe material
used in the study.  The reference wipes were labeled like a regular
sample so that the laboratory was blinded to fact that these were
quality control samples.  The Field Office inserted one reference wipe
sample with each group of 50 samples before sending samples to the
laboratory.  A total of 206 reference wipes, ranging from 21 to 516 µg
lead/wipe, were submitted over the course of the study.  The average
reference sample recovery was 96% (range from 83% to 115%) with a
standard deviation of + 5.25 percent.  With a few exceptions, all sample
recoveries were within the HUD Guidelines acceptable range of 80 to 120
percent.  The laboratory was requested to re-analyze those batches with
values outside acceptable limits.  Recoveries were acceptable on the
second run (see Section 6.7 of Volume II) and the second set of data was
used for the entire batch of samples.

	Soil Quality Control Samples

Reference Soil Samples

Reference soil samples were purchased before the fieldwork began.  The
Field Office labeled and included one reference sample with each group
of samples from every three households (approximately one sample in
ten).  A total of 83 soil reference samples were submitted to the
laboratory.  The average recovery was 104% (range 84% to 121%) with a
standard deviation of + 8.04 percent.  Two analytical batches contained
a reference sample with a recovery of 121%, exceeding the control limits
of 80 to 100 percent.  The laboratory was requested to re-analyze these
batches.  Recoveries were acceptable on the second run (see Section 6.9,
Volume II) and the second set of data was used for the entire batch of
samples.

Two types of reference soil samples were used:  urban soil provided by
University of Cincinnati (640, 3,132, and 6,090 ppm lead), and NIST SRM
2709 (San Joacquin soil, 18.9 ppm lead) and SRM 2711 (Montana soil,
1,162 ppm lead).  It is interesting, but not unexpected, that the
average recovery of 89% for the NIST Montana soil was lower than the
average of 105% for the urban soils.  Lead in urban soils tends to be
from more leachable sources (i.e. paint, past automobile emissions,
industrial facilities).

7.3.2	Laboratory Quality Control Samples

Each laboratory provided quality assurance procedures during the
selection and qualification process.  These approved procedures
(outlined in the National Survey’s Protocol and Sample Design Report,
June, 1999) were adhered to for all study samples.  In general, the
laboratories performed instrumental and duplicate quality control
analyses, as required by ASTM E 1613-94 and the American Industrial
Hygiene Association’s Environmental Lead Laboratory Accreditation
Program (ELLAP) Quality Manual and Policies, to ensure that the original
calibration solutions were accurate, the instruments were properly
zeroed, instrumental drift was not excessive, and carryover between
samples did not occur.  These included duplicate injections of the same
sample, method blanks, and spiked samples at a minimum frequency of five
percent of the samples.

7.3.3	Laboratory Selection Quality Assurance

The laboratories used for analysis of dust and soil samples,
respectively, were recognized by the EPA under its National Lead
Laboratory Accreditation Program (NLLAP) for those analyses throughout
the laboratory qualification and performance phases of the National
Survey.  This recognition provided assurance of the quality of
laboratory performance of lead analyses and reporting.  In addition, the
laboratories were accredited by the American Industrial Hygiene
Association; this accreditation provided a separate assurance of the
quality of laboratory management and performance of environmental
analyses and reporting.

7.4	Paint Testing Quality Assurance

Calibration of the XRF analyzer was performed before and after testing
in every home.  In no case was the instrument used if the calibration
criteria were not met, i.e. the analyzer read 0.0 mg/m2 on the 0.0 film
and between 0.9 and 1.2 mg/m2 on both the front and back of the 1.0
film.  In addition, the average of three readings on the front of the
1.0 film was between 0.9 and 1.2 mg/m2.

APPENDIX A

Selected Additional Tables and Figures

Figure A.1	Prevalence of Significant LBP Hazards, Soil Lead Threshold
at 2,000 ppm and at 1,200 ppm

Table A.1	Prevalence of Housing Units with Significant Lead-Based Paint
(LBP) Hazards, by Selected Characteristics, for Alternative Soil Lead
Threshold of 2000 ppm

HUD Lead Safe Housing Rule:  Significant LBP Hazardsa

Characteristic	All HUs

(000)b	No. of HUs with Significant LBP Hazards (000)	Percent of HUs with
Significant LBP Hazards (%)c	HUs in Sample

Estimate	Lower

95% CId	Upper

95% CI	Estimate	Lower

95% CI	Upper

95% CI

	Total Occupied HUs 	95,688	25,517	20,410	30,623	27%	21%	32%	375

Region:

Northeast	19,290	8,260	5,904	10,616	43%	31%	55%	95

Midwest	22,083	7,606	5,691	9,521	34%	26%	43%	102

South	35,474	6,082	3,161	9,003	17%	9%	25%	111

West	18,841	3,569	1,003	6,135	19%	5%	33%	67

Construction Year:

1978-1998	29,774	425	0	1,222	1%	0%	4%	88

1960-1977	27,874	2,843	317	5,370	10%	1%	19%	111

1940-1959	20,564	10,501	7,996	13,006	51%	39%	63%	97

Before 1940	17,476	11,747	8,771	14,723	67%	50%	84%	79

Urbanization

MSA >= 2 million population	26,814	     6,793 	     4,978 	8,609	25%	19%
32%	276

MSA =< 2 million population	45,753	    10,232 	     8,171 	12,293	22%
18%	27%	417

Non-MSA	23,121	     7,001 	     3,848 	10,153	30%	17%	44%	138

One or More Children Under Age 6:

All HU ages	16,402	5,652	3,758	7,546	34%	23%	46%	83

HUs built 1978-1998	5,847	364	0	1,127	6%	0%	19%	25

HUs built 1960-1977	5,098	371	0	987	7%	0%	19%	20

HUs built 1940-1959	3,055	2,662	1,554	3,770	87%	51%	123%	22

HUs built before 1940	2,401	2,255	502	4,007	94%	21%	167%	16

Housing Unit Type:

Single family	82,651	23,204	17,794	28,614	28%	22%	35%	319

Multi-family	13,037	2,313	0	5,143	18%	0%	39%	56

Occupant Status:

Owner-occupied	62,232	16,013 	12,647	19,380	26%	20%	31%	254

Renter-occupied	29,074	9,503 	5,906	13,100	33%	20%	45%	119

Refusal/Don’t Knowe	381

	2

Household Income:

Less than $30,000/year	33,830	13,998	8,938	19,057	41%	26%	56%	145

Equal to or more than

  $30,000/year	56,111	10,060	7,151	12,970	18%	13%	23%	211

Refusal/Don’t Know	5,747

	19

One or More Children Under Age 6:

All Income Categories	16,402	5,652	3,758	7,546	34%	23%	46%	83

Less than $30,000/year	4,791	1,646	0	3,460	34%	0%	72%	28

Equal to or more than

  $30,000/year	11,236	4,006	1,797	6,214	36%	16%	55%	52

Refusal/Don’t Know	375

	3

Table A.1	Prevalence of Housing Units with Significant Lead-Based Paint
(LBP) Hazards, by Selected Characteristics, for Alternative Soil Lead
Threshold of 2000 ppm (continued)

HUD Lead Safe Housing Rule:  Significant LBP Hazardsa

Characteristic	All HUs

(000)b	No. of HUs with Significant LBP Hazards (000)	Percent of HUs with
Significant LBP Hazards (%)c	HUs in Sample

Estimate	Lower

95% CId	Upper

95% CI	Estimate	Lower

95% CI	Upper

95% CI

	Government Support:

Government support	4,809	822	10 	1,634	17%	0%	34%	25

No government support	86,070	23,571	19,114	28,028	27%	22%	33%	327

Refusal/Don’t Know	4,809

	23

Poverty:

In Poverty	13,221	5,053	2,542	7,565	38%	19%	57%	54

Not in Poverty	76,336	18,669	14,396	22,942	24%	19%	30%	300

Refusal/Don’t Know	6,130

	21

Race:

White	77,005	19,164	14,972	23,356	25%	19%	30%	285

African American	10,365	2,317	665	3,969	22%	6%	38%	45

Otherf	6,571	2,631	0	5,734	40%	0%	87%	35

Refusal/Don’t Know	1,746

	10

Ethnicity:

Hispanic/Latino	7,434	3,635	700	6,569	49%	9%	88%	31

Not Hispanic/Latino	87,008	20,841	16,734	24,948	24%	19%	29%	337

Refusal/Don’t Know	1,246

	7

a	Significant LBP hazard as defined in text and HUD Lead Safe Housing
Rule.

b	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

c	All percentages are calculated with the “All HUs” column in each
row used as the denominator.

d	CI = 95% confidence interval for the estimated number or percent.

e	Refusals and “don’t know” responses by survey respondents.

f	“Other” race includes Asian, American Indian or Alaskan Native,
Native Hawaiian or other Pacific Islander, and more than one race.

Table A.2	Prevalence of Significant Lead-Based Paint (LBP) Hazards by
Location in the Building, for Alternative Soil Lead Threshold of 2000
ppm

HUD Lead Safe Housing Rule:  Significant LBP Hazards

LBP Hazard Location	Number of HUsa (000)	Percent of HUsb	HUs in Sample

	Estimate	Lower

95% CIc	Upper

95% CI	Percent	Lower

95% CI	Upper

95% CI

	Interior only	10,861	6,865	14,857	11%	7%	16%	47

Both Interior and Exterior	7,965	4,891	11,040	8%	5%	12%	39

Exterior only	6,690	3,635	9,745	7%	4%	10%	29

Anywhere	25,517	20,440	30,594	27%	21%	32%	115

No Significant LBP Hazard	70,171	65,094	75,248	73%	68%	79%	260

Total HUs	95,688

	100%

	375

a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	All percentages are calculated with total housing units (95,688) as
the denominator.  Percentages may not total 100% due to rounding.

c	CI = 95% confidence interval for the estimated number or percent.

Table A.3	Prevalence of Significant Lead-Based Paint (LBP) Hazards in
Housing Units with a Child Under 6 Years of Age by Type of Hazard, for
Alternative Soil Lead Threshold of 2000 ppm

HUD Lead Safe Housing Rule: Significant LBP Hazards

Type of Hazard	Number of HUsa (000)	Percent of HUsb (%)

	Estimate	Lower

95% CIc	Upper

95% CI	Estimate	Lower

95% CI	Upper

95% CI

Significantly Deteriorated Lead Based Paint

All HUs	14,124	10,666	17,582	15%	11%	18%

HUs w/ Child Under 6	3,521	1,576	5,467	21%	10%	33%

Interior Lead Dust

All HUs	16,794	12,169	21,420	18%	13%	22%

HUs w/ Child Under 6	3,637	1,636	5,638	22%	10%	34%

Lead Contaminated Soil

All HUs	5,572	2,487	8,657	6%	3%	9%

HUs w/ Child Under 6	1,419	0	3,057	9%	0%	19%

Any LBP Hazard

All HUs	25,517	20,410	30,623	27%	21%	32%

HUs w/ Child Under 6	5,652	3,758	7,546	34%	23%	46%

a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	Percentages are calculated with total housing units (95,688) or with
housing units with a child under age 6 (19,577) as the denominator, or
as applicable.

c	CI = 95% confidence interval for the estimated number or percent.

Table A.4a	Distribution of Single Family Housing Units (SFHUs) with
Deteriorated or Significantly Deteriorated Paint, by Construction Year

Deteriorated Paint

Construction Year	Total SFHUs (000)a	Number of SFHUs with

Deteriorated Paint (000)	Percent of SFHUs with

Deteriorated Paint (%)b

Estimate	Lower 95% CIc	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

1978-1998	26,349	5,231	2,628	7,835	20%	10%	30%

1960-1977	22,657	7,992	5,573	10,410	35%	25%	46%

1940-1959	18,497	11,987	9,643	14,331	65%	52%	77%

Before 1940	15,148	11,518	10,049	12,986	76%	66%	86%

Total SFHUs	82,651	36,728	27,893	45,562	44%	34%	55%

Significantly Deteriorated Paint

Construction Year	Total SFHUs (000)	No. of SFHUs with Significantly
Deteriorated Paint (000)	Percent of SFHUs with Significantly
Deteriorated Paint (%)

Estimate	Lower 95% CI	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

1978-1998	26,349	3,403	1,629	5,176	13%	6%	20%

1960-1977	22,657	6,606	4,291	8,922	29%	19%	39%

1940-1959	18,497	9,426	7,240	11,611	51%	39%	63%

Before 1940	15,148	9,365	7,527	11,203	62%	50%	74%

Total SFHUs	82,651	28,800	20,686	36,913	35%	25%	45%

a	“Single family housing units” include permanently occupied,
noninstitutional single family housing units in which children are
permitted to live.

b	Percentages are calculated with total housing units (95,688) or with
housing units with a child under age 6 (19,577) as the denominator, or
as applicable.

c	CI = 95% confidence interval for the estimated number or percent.

Table A.4b	Distribution of Single Family Housing Units (SFHUs) with
Deteriorated or Significantly Deteriorated Unleaded Paint, by
Construction Year

Deteriorated Unleaded Paint

Construction Year	Total SFHUs (000)a	Number of SFHUs with

Deteriorated Unleaded Paint (000)	Percent of SFHUs with

Deteriorated Unleaded Paint (%)b

Estimate	Lower 95% CIc	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

1978-1998	26,349	5,149	2,525	7,773	20%	10%	29%

1960-1977	22,657	7,081	4,873	9,289	31%	22%	41%

1940-1959	18,497	5,748	4,076	7,420	31%	22%	40%

Before 1940	15,148	2,824	1,828	3,819	19%	12%	25%

Total SFHUs	82,651	20,802	13,303	28,301	25%	16%	34%

Significantly Deteriorated Unleaded Paint

Construction Year	Total SFHUs (000)2	No. of SFHUs with Significantly
Deteriorated Unleaded Paint (000)	Percent of SFHUs with Significantly
Deteriorated Unleaded Paint (%)1

Estimate	Lower 95% CI3	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

1978-1998	26,349	3,320	1,521	5,119	13%	6%	19%

1960-1977	22,657	5,997	3,752	8,241	26%	17%	36%

1940-1959	18,497	4,658	3,107	6,209	25%	17%	34%

Before 1940	15,148	2,250	1,274	3,225	15%	8%	21%

Total SFHUs	82,651	16,225	9,654	22,795	20%	12%	28%

a	“Single family housing units” include permanently occupied,
noninstitutional single family housing units in which children are
permitted to live.

b	Percentages are calculated with total housing units (95,688) or with
housing units with a child under age 6 (19,577) as the denominator, or
as applicable.

c	CI = 95% confidence interval for the estimated number or percent.

Table A.4c	Distribution of Single Family Housing Units (SFHUs) with
Deteriorated and Significantly Deteriorated Lead-Based Paint (LBP) by
Construction Year

Deteriorated LBP

Construction Year	Total SFHUs (000)2	Number of SFHUs with

Deteriorated LBP (000)	Percent of SFHUs with

Deteriorated LBP (%)1

Estimate	Lower 95% CI3	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

1978-1998	26,349	83	0	238	0%	0%	1%

1960-1977	22,657	910	242	1,579	4%	1%	7%

1940-1959	18,497	6,239	4,319	8,159	34%	23%	44%

Before 1940	15,148	8,694	7,107	10,281	57%	47%	68%

Total SFHUs	82,651	15,926	11,668	20,257	19%	14%	25%

Significantly Deteriorated LBP

Construction Year	Total SFHUs (000)2	No. of SFHUs with Significantly
Deteriorated LBP (000)	Percent of SFHUs with Significantly Deteriorated
LBP (%)1

Estimate	Lower 95% CI3	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

1978-1998	26,349	83	0	238	0%	0%	1%

1960-1977	22,657	610	97	1,122	3%	0%	5%

1940-1959	18,497	5,002	3,193	6,811	27%	17%	37%

Before 1940	15,148	7,115	5,605	8,626	47%	37%	57%

Total SFHUs	82,651	12,809	8,894	16,797	15%	11%	20%

a	“Single family housing units” include permanently occupied,
noninstitutional single family housing units in which children are
permitted to live.

b	Percentages are calculated with total housing units (95,688) or with
housing units with a child under age 6 (19,577) as the denominator, or
as applicable.

c	CI = 95% confidence interval for the estimated number or percent.

Table A.5	Estimated Number of Housing Units with Lead-Based Paint on
Windows

	Number of Housing Units with LBP Windows (000)	HUs in Sample

HU Characteristic	Estimate	Lower 95% CI	Upper 95% CI

	All Housing Units	18,222	15,688	20,757	165

Construction Year:

1978-1998	290	0	711	2

1960-1977	2,092	1,251	2,933	20

1940-1959	4,733	3,202	6,264	41

Before 1940	11,108	9,298	12,917	102

Occupied by Children Under Age 6	2,826	1,661	3,991	32

Household in Poverty	3,547	2,324	4,771	36

Household in Poverty, Resident Children Under Age 6	569	169	969	7

Table A.6	Estimated Number of Windows with Lead-Based Paint and in
Housing Units with

		Lead-Based Paint on Windows

	Number of Windows with Lead-Based Paint (Average/HU)a	Number of Painted
Windows

(Average/HU)	Total Number of Windows (Average/HU)

HU Characteristic	Estimate	Lower 95% CI	Upper 95% CI	Estimate	Lower 95%
CI	Upper 95% CI	Estimate	Lower 95% CI	Upper 95% CI

All Housing Units	7.7	6.2	9.3	13.9	12.1	15.7	15.0	13.3	16.8

Construction Year:

	1978-1998	3.5	0.0	7.9	7.2	3.9	10.4	7.2	3.9	10.4

1960-1977	5.6	3.4	7.8	14.0	8.1	20.0	14.4	8.5	20.3

1940-1959	6.5	4.2	8.7	12.8	10.6	15.0	14.0	12.0	16.1

Before 1940	8.7	6.9	10.6	14.5	12.5	16.5	15.7	13.8	17.7

Occupied by Children Under Age 6	12.7	8.0	17.5	20.4	14.5	26.3	21.8	16.2
27.4

Household in Poverty	4.3	2.7	6.0	7.9	5.9	9.9	9.4	8.1	10.7

Household in Poverty, Resident Children Under Age 6	4.8	0.7	8.8	9.8	7.8
11.9	9.8	7.8	11.9

a Entries are average number of windows per housing units, averaged over
the housing units with LBP on windows.

Table A.7	Distribution of Maximum Soil Sample (Bare and Covered) Lead
Concentrations, All Sampled Locations

Bare Soil Lead	Number of HUs (000)a	Percent of HUs (%)b

Estimate	Lower

95% CIc	Upper

95% CI

Estimate	Lower

95% CI	Upper

95% CI

GEd0 ppm	93,111	91,090	95,131	97%	95%	99%

GE 20 ppm	74,621	68,764	80,478	78%	72%	84%

GE 50 ppm	56,266	49,840	62,693	59%	52%	66%

GE 200 ppm	29,234	28,240	30,228	31%	30%	32%

GE 400 ppm	20,390	17,032	23,748	21%	18%	25%

GE 1,200 ppm	11,145	7,580	14,709	12%	8%	15%

GE 1,600 ppm	7,426	5,289	9,563	8%	6%	10%

GE 2,000 ppm	6,809	4,535	9,084	7%	5%	10%

GE 5,000 ppm	2,987	1,548	4,427	3%	2%	5%

No Bare Soil	335	0	960	0%	0%	1%

No Soil	2,242	330	4,154	2%	0%	4%

Missinge	95,688

	a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	All percentages are calculated with total housing units (95,688) as
the denominator.

c	CI = 95% confidence interval for the estimated number or percent.

d	GE equals “greater than or equal to.”

e	“Missing” means that soil was present, but that no lead value is
available (either the sample was not collected, e.g. due to
inaccessibility or respondent refusal, or the laboratory did not submit
a value).  “No soil” means that there was no soil on the property to
sample.

Table A.8	Distribution of Maximum Soil Sample (Bare and Covered) Lead
Concentrations by Construction Year, All Sampled Locations

Soil Lead Concentration	Number of HUs (000)a	Percent of HUs (%)b

	Before 1940	1940 - 1959	1960 - 1977	1978 - 1998	Before 1940	1940 - 1959
1960 - 1977	1978 - 1998

GEc  0 ppm	16,328	19,605	27,608	29,569	93%	95%	99%	99%

GE 20 ppm	16,328	19,279	25,238	13,776	93%	94%	91%	46%

GE 50 ppm	15,820	17,670	14,092	8,684	91%	86%	51%	29%

GE 200 ppm	13,314	9,950	4,495	1,476	76%	48%	16%	5%

GE 400 ppm	11,613	6,283	2,410	84	67%	31%	9%	0%

GE 1,200 ppm	6,536	3,922	686	- 	37%	19%	3%	0%

GE 1,600 ppm	4,455	2,284	686	- 	26%	11%	3%	0%

GE 2,000 ppm	3,929	2,194	686	- 	23%	11%	3%	0%

GE 5,000 ppm	1,891	865	231	- 	11%	4%	1%	0%

Missingd	145	- 	190	- 	1%	0%	1%	0%

No soil 	1,003	939	95	205	6%	5%	0%	1%

Total	17,476	20,544	27,893	29,774	100%	100%	100%	100%

a	“Housing units” include permanently occupied, noninstitutional
housing units in which children are permitted to live.

b	All percentages are calculated with total housing units of that age as
the common denominator.

c	GE equals “greater than or equal to.”

d	“Missing” means that soil was present, but that no lead value is
available (usually due to inaccessibility or respondent refusal).  “No
soil” means that there was no soil on the property to sample.

APPENDIX B

Comparison of Protocols

for the

HUD 1990 Survey of Lead-Based Paint (LBP) in Housing

and the

HUD National Survey of Lead and Allergens in Housing

Comparison of Protocols for the HUD 1990 Survey of Lead-Based Paint
(LBP) in Housing

and the HUD National Survey of Lead and Allergens in Housing

Area

HUD National Survey of Lead-Based Paint in Housing

HUD National Survey of Lead and Allergens in Housing

Types/numbers of housing units selected for the survey and whose data
were available to the TSCA Section 403 risk analysis

284 housing units selected from occupied, permanent, non-institutional
housing in the 48 coterminous states built prior to 1980 and having the
potential for containing children.  (These units were all
privately-owned.  While publicly-owned units were also selected for the
survey, data for these units are not considered in this summary.)

831 housing units selected in a three-stage stratified random sample
from occupied, permanent, non-institutionalized housing having the
potential for containing children.  75 primary sampling units (PSUs).

Breakdown of selected units by year built

Pre-1940: 27%

1940-1959: 31%

1960-1979: 42%

Post-1979: 0%

Pre-1940: 18%

1940-1959: 22%

1960-1977: 29%

Post-1977: 31%

Dates of environmental sampling

November 1989 to March 1990

August 1998 to February 1999, and from July to August 1999

Selecting rooms for environmental sampling

Telephone household interview provided information on rooms. One room
was selected for sampling in each of the following strata:

Wet room -- rooms containing plumbing (e.g., kitchen, bathroom, laundry
room, utility room)

Dry room -- all rooms not classified as wet rooms

Main entryway (floor dust samples only)

Room Inventory Form from the Screening/Recruiting Questionnaire was used
to obtain information on rooms.  One room was randomly selected for
sampling in each of the following four strata:

Kitchen

Common living area (e.g., living room, den, family room)

Bedroom in which one or more children aged 17 years or younger regularly
slept, or any regularly-occupied bedroom if no such children lived in
the unit (occasionally, two such bedrooms were selected)

Other random room among the remaining rooms in the housing unit.  (Note:
 Two rooms were randomly selected from this stratum if the stratum
contained at least six rooms.)

Main entry (floor dust only)

Interior common area (multi-family dwellings, floor dust only)

Method of assigning sampling weights

Weights reflect the various stages of sampling.  Total of the sampling
weights equaled the estimated number of housing units with children
under age 7 years (13,912,000, as estimated by the 1987 AHS).  Total of
the sampling weights within a given census region equaled the estimated
number of units with children under age 7 years in the census region.

Weights reflect the various stages of sampling.  Total of the sampling
weights within a given census region equals the estimated number of
units in the census region.

Method for taking dust samples for lead analysis

Blue Nozzle vacuum (a few wipe samples were also collected).  Sampling
house dust for lead:  basic concepts and literature review. (1995). EPA
747-R-95-007.

Wipes, collected in accordance with ASTM E1728-95, Practice for the
field determination of settled dust samples using wipe sampling methods
for lead determination by atomic absorption spectrometry techniques.

Number and location of floor-dust samples per room

One sample from each selected room (location not dictated in the
protocol)

One sample from each selected room, generally taken from the center of
the largest open area of the room.

Window sill/trough dust sampling approach

A window was selected within each selected room according to a ranking
scheme.  Sampling was performed from both the sill and trough of the
selected window until enough dust was collected or until the entire sill
or trough was vacuumed.

Entire sill and trough sampled from a random window in the selected
room.  Trough definition included sliders.

Number and location of sill and trough dust samples per room

One sample from the sill and one sample from the trough of the selected
window in the selected wet room and dry room

One sample from the sill and one sample from the trough of the selected
window in each selected room

Method of analyzing dust samples

Graphite Furnace Atomic Absorption Spectroscopy (GFAA) (with EPA SW-846
digestion method)

Flame Atomic Absorption Spectrometry (FAAS) using NIOSH method 7082

Digestion method: modification of EPA SW-846 Method 3050 or ASTM ES
36-94 (hot-plate digestions utilizing nitric acid and/or perchloric acid
and/or hydrogen peroxide).  Method same as used in proficiency testing
within the Environmental Lead Laboratory Accreditation Program (ELLAP).

Soil sampling approach

One composite sample of up to 3 core samples (the latter two taken
within 20 inches of the first), each taken at a depth of 10 cm, was
collected at each of the following locations: entryway, drip-line, and
remote area (i.e., an area halfway between the unit and its property
boundary, or within 25 feet of the unit, whichever was less).

Two sides of the unit were selected for soil sampling: the side
containing the major entryway (Wall 1) and a second, randomly-selected
side (Wall 2).  Samples were collected from the top 0.5 inches of soil
at the following three sites:

Main entry - a single sample from Wall 1

Foundation/drip-line - one sample from each of Walls 1 and 2, each
sample being a composite of 3 core subsamples taken within 3 feet of the
foundation

Mid-yard area - one sample from each of Walls 1 and 2, each sample being
a composite of 3 core subsamples taken midway between the drip-line and
boundary of the housing unit property.

Play Area – one composite sample from bare soil under each unit of
fixed play equipment.

Soil samples were collected in accordance with core sampling procedures
based on ASTM E1727-95 (described in the HUD Guidelines and in EPA’s
Residential Sampling for Lead: Protocols for Leaded Dust and Soil
Sampling). Samples were collected from bare soil when possible.  If no
bare soil existed, samples were collected from covered surfaces if
possible.

Method of analyzing soil samples

ICP-AES (with SW-846 digestion method)

ICP-AES using NIOSH method 7082

Digestion method: modification of SW-846 Method 3050 or ASTM ES 36-94
(hot-plate digestions utilizing nitric acid and/or perchloric acid).
Method same as used in proficiency testing within the Environmental Lead
Laboratory Accreditation Program (ELLAP).

Handling dust-lead and soil-lead measurements below the detection limit

As log-transformed lead amounts are reported in the database,  only
positive measurements are represented.  No indication is given as to
when data may have been truncated due to being below detection limits.

The final results as reported by the instrument are recorded in the
database (i.e., not-detected results are not censored), along with
detection limits.

Method for taking paint-lead measurements

Spectrum analyzer XRF instrument (single 60-second spectrum reading
measurement using a 40 millicurie cobalt source).  Measurements were
adjusted to statistically correct for measurement bias.

Spectrum analyzer XRF analyzer (full-period readings with a 20-second
minimum in accordance with the applicable HUD-approved Performance
Characteristic Sheet .)

Approach to selecting interior painted components for paint-lead
measurements

Painted surfaces were categorized into the following four strata:

Walls/ceilings/floors

Metal substrate

Non-metal substrate

Other surfaces

Five painted components were selected randomly for testing in each of
the selected wet and dry rooms, one from each stratum along with a fifth
selected randomly from among all strata.  In addition, up to two
purposive measurements were taken from paint anywhere in the unit that
may be suspected to contain lead.

The following painted components were measured for lead in each selected
room:

All four major walls

Ceiling

Door of major entryway

Window selected for dust sampling

Baseboard

Floor

Up to two other painted surfaces:  Technician choice based on surfaces
containing deteriorated paint or friction areas.

Approach to selecting exterior painted components for paint-lead
measurements

Painted surfaces were categorized into the following four strata:

Wall (randomly-selected)

Metal substrate within the selected wall

Non-metal substrate within the selected wall

Other surfaces within the selected wall

Five painted components were selected randomly for testing from the side
of the unit containing the selected wall, one from each stratum along
with a fifth selected randomly from among all strata.  In addition, up
to two purposive measurements were taken from paint anywhere on the
exterior of the unit that may be suspected to contain lead.

Painted siding was measured for lead levels on each exterior wall.  In
addition, the following painted components were measured for lead on a
random wall:

Miscellaneous trim (2 measurements)

Window

Door of major entryway – wall independent.

Porch and railing – wall independent

Up to two other painted surfaces

APPENDIX C

Correcting for Classification Bias Due to Measurement Error

Correcting for Classification Bias Due to Measurement Error

Homes were classified as having LBP and lead hazards based on the XRF
readings of paint and the analysis of dust and soil samples.  Random
variation associated with instrument or laboratory measurement, sample
collection, and random selection of sampling locations, can induce a
classification bias resulting in a bias in the estimated prevalence of
HUs with LBP and lead hazards.  In addition, paint and dust measurements
were made in a sample of rooms – not all rooms.  Under this protocol,
it is possible for a home to have LBP or a LBP dust hazard in the
unsampled rooms and non-lead-based paint and/or no dust-lead hazard in
the sampled rooms.  Such HUs would be incorrectly classified as not
having LBP and/or LBP hazards (false negatives).  For this report,
measurement error refers to the combined effect of instrument or
laboratory measurement variation, sampling variation, spatial variation,
and the incomplete sampling of rooms on the important survey estimates.

The specific procedures, equations, and justification for the
measurement error correction are presented in Appendix C of Volume II.
The findings for the measurement error analyses for paint, dust, and
soil are discussed below in Sections 7.3.1 through 7.3.3 below.  The
measurement error adjusted values (lead loading or concentration) have,
to the extent possible, the same distribution as the true lead loading
or lead concentration values, without the effect of measurement error.
The measurement error corrected values are a weighted average of the
observed measurements and predicted values from a regression model.
Calculating the weights requires modeling the magnitude of the
measurement error variance and the regression error variance.  Replicate
measurements were used to estimate the measurement error variance.

Note that this analysis used preliminary data from the main survey.  The
analysis did not include data from the follow-on play area survey.  In
addition, minor revisions or corrections to the data may have been made
since the analysis was performed.  As a result, summary statistics from
the measurement error analysis may not agree with those in other
sections of the report.  Nevertheless, the effects of measurement error
are expected to similar in the preliminary and final data.

C.1	Measurement Error - Paint XRF Measurements

XRF readings to measure paint lead loading were taken on painted
surfaces within the sampled rooms and on accessible exterior surfaces on
two sides of the building to assess the lead loading in paint.  The
measurement error adjustment procedures were first applied to the
interior XRF readings.  Because the measurement error adjusted XRF
values were very close to the original interior XRF readings, it was
considered unnecessary to apply a measurement error adjustment to the
exterior XRF readings.

For the measurement error analysis for paint lead measurements, the
objective was to determine the number and percentage of homes with LBP.
A surface with LBP is a surface with an average lead loading across the
surface of 1.0 mg/cm2 or greater when tested with an XRF analyzer.  The
instrument calculates its best internal estimate of the lead loading,
which it rounds to the nearest 0.1 mg/cm2 for display.  Therefore, to
classify surfaces in an equivalent manner, the error corrected XRF
readings were rounded to the nearest tenth unit for classifying
surfaces.  The classification of surfaces as having or not having LBP is
used to classify homes as having or not having LBP.

The measurement error adjustment procedure assumes that the distribution
of the true paint lead loading around the average for similar homes and
the distribution of the measurement error are normal.  This assumption
provided a relatively poor description of the XRF readings due to the
presence of many zero XRF readings and long tails in the XRF
distribution (the measurement error adjustment results are expected to
be sensitive values in the tails of the distribution).  As a result, the
measurement error adjustment for paint lead loadings should be
considered approximate, at best.  Additional research into the
measurement error of the XRF instrument and the distribution of paint
lead loading across components would be required to improve the
measurement error adjusted values.

Figure C.1, which shows a scatter plot of replicate XRF readings, helps
to illustrate the distribution of the XRF readings.  The original XRF
reading is on the horizontal axis and the replicate reading is on the
vertical axis.  Three situations occur. The first is where both XRF
readings are zero (72.3 percent of the replicate pairs) - these pairs
provide essentially no information about measurement error.  The second
case is where one of the two readings is zero (12.4 percent of the
replicate pairs) - these pairs fall on the axes.  Lastly, there is the
case where both XRF readings are non-zero (15.3 percent of the replicate
pairs) – these generally fall on the diagonal in Figure C.1. For these
points, the differences between the replicate XRF readings have an
approximately normal distribution as assumed by the measurement error
correction procedure.

The XRF variation among all surfaces within a home increases with the
average XRF reading within the home.  This suggests that the measurement
error will also increase with the paint lead loading on a component.
Surfaces with lead loading near zero will have relatively precise
measurements and we expect that large differences between replicate
readings when one reading is zero will be relatively rare.  However,
there are many surfaces for which one reading is zero and the other
paired reading is relatively large (may be due to two different parts of
a component having very different paint lead loadings).

Figure C.1	Original and Replicate XRF Readings on the Same Component

Note: The axes use the transformed scale used for analysis (see Equation
9 in Appendix C,  Volume II).

For the measurement error adjustment, homes in which all XRF readings
were zero or negative (162 HUs) were assumed to have no paint lead.  The
remaining homes were used in the measurement error analysis.  For those
homes, the model used to predict paint lead loadings had factors for
housing unit ID, room type, year of construction, and interactions of
year of construction by substrate, component, and percent deteriorated
paint.  A preliminary analysis suggested that the relationship between
paint deterioration and XRF reading was not linear.  To make the
relationship closer to linear, the cube of the percent deterioration was
used in the model.  A further analysis of the relationship would be
necessary to provide a better model.

The regression analysis predicts the approximate median of the interior
paint lead loading. Figure C.2 shows the relative median paint lead
loading estimated from regression, by construction year category and
component substrate.  Figure C.3 shows the relative differences in
median paint lead loading associated with combinations of construction
year and region of the country.  Figure C.4 and 7.5 shows the relative
differences in the median paint lead loading versus component type, room
type, component condition, metro status, presence of pets, overall home
cleanliness, and the number of days the air conditioning was used in the
last month. Because the assumptions behind the measurement error
analysis provide a poor description of the XRF measurements, the
patterns illustrated in Figures 7.2 to 7.5 should be considered
suggestive of, rather than descriptive of, patterns in the population.

Figure C.2	Predicted Relative Median Paint Lead Loading by Construction
Year of the Home and Substrate (based on regression model)

Figure C.2 shows that interior paint lead loadings are highest in the
oldest homes and lowest in the newest homes.  The patterns for paint
lead loading on specific substrates also generally decrease with the age
of the home.  The paint lead loadings are highest on wood surfaces in
the oldest homes.  For components with drywall, paneling, metal,
plaster, wallpaper, and wood substrates, the median paint lead loading
is low (less than 0.05 mg/cm2) for homes built since 1960.  However,
median paint lead loading on other substrates (such as brick, concrete,
stone, and vinyl) are higher for homes built in the 1960 to 1977 period.

Figure C.3 shows that the highest predicted median paint lead loading is
found in homes built before 1960 in the northeast US and in homes built
before 1940 in the southern US.

Figure C.3	Predicted Relative Median Paint Lead Loading by Construction
Year of the Home and Region (based on regression model)

Figure C.4 shows that higher paint lead loadings are generally found on
doors, window jambs and window sashes.  There are relatively small but
significant differences in the paint lead loading among rooms of
different types.  After accounting for other factors, paint lead
loadings are generally higher in children’s bedrooms and in kitchens.

Figure C.4	Predicted Relative Median Paint Lead Loading by Component
Type and Room Type (based on regression model)

Figure C.5 shows that higher paint lead loadings are generally found on
components that were judged to be in fair condition as opposed to intact
or poor condition.  However, relatively few surfaces were judged to be
in fair condition.  Small but significant differences were associated
with metro status (lower paint lead loading in non-MSAs), presence of
pets (lower in homes with pets), overall cleanliness, and days using air
conditioning in the last month.

Figure C.5	Predicted Relative Median Paint Lead Loading by Component
Condition, Metro Status, Presence of Pets, Overall Cleanliness, and Air
Condition Use in the Last Month (based on regression model)

As part of the exploratory analysis to identify the model for the data,
such additional variables as tenure and race were considered and not
found to be significant predictors.

The measurement error adjustment procedure identified approximately 30
percent of the XRF readings as outliers.  Outliers are those
measurements that are more than 2.5 standard deviations above or below
the mean of the non-outliers.  In this case, the measurement error
procedure makes a conservative adjustment.  The non-outlier data were
assumed to have a normal error distribution, however, the distribution
of the residuals had a tight distribution in the center and very long
tails, inconsistent with the normal distribution assumption.  The
resulting estimate of the error variance was very small, resulting in
almost no estimated effect of measurement error.  Using the measurement
error procedure in Appendix C (Volume II), the measurement error
adjusted paint lead loadings are essentially equal to the XRF readings.
Additional work would be required to develop a better model for the XRF
readings and other assumptions might provide a significantly different
assessment of the effects of measurement error.

The tentative results from the measurement error analysis are that the
interior XRF readings provide a reasonable measure of the paint lead
loading for many surfaces.  For the remaining surfaces that look like
outliers when judged relative to a normal distribution, the effect of
measurement error is difficult to assess.  We believe that similar
conclusions are likely to apply to exterior surfaces; however, no
measurement error adjustment was attempted for the exterior surfaces.

C.2	Measurement Error – Dust Lead Measurements

Dust samples were taken at all surveyed homes from the floor at the main
entrance and from the floors, window sills, and window troughs of the
sampled rooms.  Separate measurement error adjustments were performed
for the floor and window dust samples.

Floor Dust Lead Loading

The model for predicting floor dust lead loading included factors for
household ID (as a class variable), surface characteristics at the
sample location, and the interaction of the type of floor cover and year
of construction.  The measurement error adjustment procedures excluded
three percent of the floor dust measurements as outliers.  The
regression analysis predicts the approximate median of the floor dust
lead loading.

Figure C.6 shows the relative median floor dust lead loading estimated
from regression, by construction year category and type of floor cover
in the sampled room.  The predicted median floor dust lead loadings were
highest for the oldest homes and decrease for homes constructed more
recently.  The floor lead loading was generally higher in rooms with no
floor covering than in rooms with wall-to-wall carpets.  Rooms with some
floor covering had floor dust loadings similar to or somewhat greater
than in rooms with wall-to-wall carpets, and lower than rooms with no
floor covering.  The floor lead loadings for the unknown floor cover
category represent primarily the floor dust lead loadings for the main
entrance (94% of the data in the unknown category, as this information
was not recorded).  The dust lead loading at the main entrance was
similar to dust lead loading from other rooms that have no floor
covering.

Figure C.6	Predicted Relative Median Floor Dust Lead Loadings by
Construction Year Category and Floor Cover in the Sampled Room (based on
regression model)

Figure C.7 shows the relative median floor dust lead loading estimated
from regression, by home cleanliness, household income, and surface
sampled.  Dust lead loadings were on average higher in lower income
homes, and in homes that show no evidence of cleaning (a small minority
of all homes).  Dust lead loadings were also higher on hard surfaces
that were not smooth and cleanable (a small minority of all surfaces),
perhaps because these surfaces are more difficult to clean or perhaps
because they collect dust faster between cleanings.  Carpets had lower
lead loading than smooth and cleanable surfaces, using the wipe sampling
methods employed.

Figure C.7	Predicted Relative Median Floor Dust Lead Loadings by
Cleanliness, Household Income, and Surface Condition (based on
regression model)

As part of the exploratory analysis to identify the model for the data,
additional variables were considered and not found to be significant
predictors.  In particular, the type of room (bedroom, bathroom,
kitchen, etc.) and presence of pets were not significant.

Figure C.8 shows the cumulative distribution of the maximum floor dust
lead loading at homes.  The figure shows three cumulative distributions:

The maximum of the floor dust lead loading measurements at a home
(bottom thin black line).

The maximum measurement error adjusted floor dust lead loading across
the sampled rooms (top gray line).

The maximum measurement error adjusted floor dust lead loading across
all rooms, sampled and unsampled (middle thick black line).

The difference between the first (bottom thin black) and second (top
gray) curves shows the effect of the measurement error adjustment on the
classification of the measured surfaces.  The difference between the
second (top gray) and the third (middle thick black) curves illustrates
the effect of random selection of rooms on the classification of homes.
Measurement error tends to increase the number of homes, and incomplete
sampling of rooms tends to decrease the number of homes, classified as
having maximum floor dust lead loading above a selected value.  For the
floor data, these effects partially cancel out so that the number of
homes classified as having floor lead over a specified value using
either the maximum adjusted lead loading value or the maximum observed
measurements is similar.  The difference between the first (bottom thin
black) and the third (middle thick black) curves illustrates the
combined effect of doing both the measurement-error adjustment and
unsampled-room adjustment.

Using the measurement error corrected values, an estimated four percent
of homes (about 4 million homes) have floor dust lead loadings of 40
g/ft2 or more in one or more rooms.  This is about one percent fewer
homes than estimated using the actual floor dust measurements.

Figure C.8	Cumulative Distribution of the Maximum Floor Dust Lead
Loading for Homes

Window Dust Lead Loading

Window dust samples were taken from randomly selected windows in the
sampled rooms within surveyed homes.  For the measurement error
correction, one objective was to estimate the number of rooms having or
not having average window sill dust lead loading and average window
trough dust lead loading less than a selected value.  A second objective
was to estimate the number of homes with average room window sill and
window trough dust lead loading less than a selected value in all rooms.
 The first objective required estimating lead loadings for the missing
values and adjusting for measurement error.  The second objective also
required adjusting for the unknown lead loading in the unsampled rooms.

Scatter plots of the data showed that the log transformed window sill
and trough measurements are linearly related, with the ratio of the
trough to sill lead loading being roughly constant at about 11.  The
proximity of the sill to the trough suggests that the similar factors
may affect the lead loading at these two locations.  Therefore, the
analysis below used both the window sill and window trough dust lead
loadings in the same model for calculating the measurement error
adjustment.  Because the log transformation was used, the model assumes
that the same factors predict the relative sill and trough lead loadings
and that the ratio of the sill to trough lead loading was constant
across homes.  Although a separate measurement error adjustment could
have been performed separately for sill and trough measurements, this
combined approach was expected to provide a similar adjustment.  The
measurement error adjustment procedures excluded three percent of the
floor dust measurements as outliers.

Two models were fit to the data.  One was used for predicting window
dust lead loading in homes with at least one window lead loading
measurement.  A second model was used to predict window dust lead
loading for homes with no window dust lead loading measurements in the
data files.  The predictors in each model are presented in Table C.1.

Table C.1	Regression Model Used for Different Categories of Homes

Category of homes	Number of homes	Factors for predicting window dust
lead loading

I. Homes with no window dust samples	17	Sample location (sill or
trough), year of construction, tenure, race category of occupants,
overall household cleanliness as judged by the interviewer, and room
type.

II. Homes with at least one window dust sample	808	Sample location (sill
or trough), household ID (as a class variable), surface characteristics
at the sample location, whether the window has a vinyl mini-blind, and
room type.

Figure C.9 shows the relative differences in median window dust lead
loading associated with different levels of sample location (sill or
trough), year of construction, tenure, race category, overall household
cleanliness, surface characteristics, room type, and presence of vinyl
mini-blinds.

Figure C.9	Predicted Median Window Dust Lead Loading by Various Factors
(based on regression model)

The predicted median window dust lead loading is much higher in the
window trough than on the window sill.  Lead loading is highest for the
oldest homes and lower for homes constructed more recently.  The window
lead loading is generally higher for rented homes than in private owned
homes and higher in homes with African American residents and in homes
with residents of other races.  The small number of homes that have no
apparent indication of cleaning have higher window dust lead loadings
than homes that were classified as showing some evidence of cleaning or
appearing clean.  Although most rooms had similar window dust lead
loading measurements, measurements were somewhat higher in adult
bedrooms and “Other” rooms (rooms not classified as kitchen, living
room, or bedroom).  Samples from window surfaces that were not smooth
and cleanable had higher lead loading than samples from smooth and
cleanable surfaces.  Finally, windows with vinyl mini-blinds had
somewhat higher dust lead loading than windows without vinyl
mini-blinds.  Differences for other window coverings were not
statistically significant.

Figure C.10 shows the cumulative distribution of the maximum window sill
dust lead loading within homes.  The figure shows four cumulative
distributions:

The maximum of the window dust lead loading measurements within a home
(thin black line).

The maximum of the window dust lead loading measurements or predicted
values for missing data (also a thin black line).

The maximum measurement-error-adjusted window dust lead loading across
the sampled rooms (thick gray line).

The maximum measurement-error-adjusted window dust lead loading across
all rooms, sampled and unsampled (thick black line).

For various reasons, such surfaces being inaccessible, data were not
available for some window surfaces.  The first curve assumes that the
lead loading on all surfaces with missing data is negligible.  As a
result of the measurement error adjustment, predicted values are
available for all surfaces.  For surfaces with no data, the predicted
values were used.  The second curve, to the right of the first curve,
shows the cumulative distribution of the best estimate of the lead
loading on all window surfaces, i.e., the measurement on surfaces with
data and the predicted values on surfaces with no measurements.  The
predicted values are referred to as imputed values.  The imputation
generally affects the lower portion of the distribution.

The third curve shows the distribution of the measurement error adjusted
estimates.  Since measurement error will generally increase the maximum
within-home measurements, the effect of the measurement error correction
is to slightly reduce estimated maximum within-home window dust lead
loading.  The fourth curve shows the cumulative distribution of the
measurement error corrected measurements after accounting for the
incomplete sampling of rooms.  These values will be referred to as the
adjusted values.  The primary difference between the maximum of the
observed window sill dust lead loading measurements and the final
adjusted maximum in each home is due to the incomplete sampling of
rooms.

g/ft2 in at least one room.  This is about five percent more homes
than estimated using the actual measurements.  A predicted 22 percent of
homes (21 million homes) have a window trough dust lead loading of at
least 800 g/ft2 in at least one room.  This is about 20 percent more
than estimated using the actual measurements.

Figure C.10	Cumulative Distribution of the Maximum Within-Home Window
Sill Dust Lead Loading

Figure C.11 shows the cumulative distribution of the maximum window
trough dust lead loading within homes.  The figure shows four cumulative
distributions for the measurements (thin upper thin black line), the
measurements plus imputed values (lower thin black line), the
measurement error corrected values for the sampled rooms (gray line) and
the final adjusted values that account for the incomplete sampling of
rooms

Because there were many surfaces for which window trough data could not
be obtained, there are relatively large differences between the
distributions for the measurements and the measurements with imputed
values.  As with the window sill lead loading, the measurement error
adjustment for the available measurements makes only a small difference
compared to the effect of missing data and the incomplete sampling of
rooms.

Figure C.11	Cumulative Distribution of the Maximum Within-Home Window
Trough Dust Lead Loading

C.3	Measurement Error – Soil Lead Measurements

Soil samples were taken at all surveyed homes at the major entrance and
along the dripline and midyard of two sides of the home, if soil was
present.  For the soil measurement error correction, the objective was
to determine the number and percentage of homes with average soil lead
concentrations above a selected value at the three sample sites -
midyard, dripline, and main entrance.  Note that this analysis was
performed on preliminary data, before the play area survey samples were
collected.

Table C.2 describes the regression model used for different categories
of homes.

For Category I homes, there was no soil at any of the three sample
sites, and so no model was required.  This situation occurred if all
areas of the yard were covered with concrete, asphalt, or rock.  Also, a
specific sample site could have no soil if the site did not exist (for
example, the dripline and the property line coincided so that there was
no midyard sample site).

For Category II homes, at least one of the sample sites had soil, but
there were no soil lead measurements for the home.  This situation could
arise if the respondent denied permission to collect soil samples, or if
adverse conditions existed, such as an ongoing storm, frozen ground, the
presence of a dog, or large rocks mixed in with the soil. The
measurement error corrected soil lead concentrations are the predicted
values from the regression model.

For Category III homes, all soil measurements were equal to zero.  While
the sample detection limit was determined to be 20 ppm, the laboratory
provided an estimate of the soil lead for all samples with levels below
the detection limit.  However, negative laboratory estimates were
reported as zero. The measurement error corrected soil lead
concentrations are assumed to be less than the detection limit.

For Category IV homes, some or all of the soil measurements were equal
to a non-zero value (i.e., a value at or more than the detection limit).
 These values were used to predict soil lead concentrations for the
category IV and category II homes.

Table C.2	Regression Model Used for Different Categories of Homes

Category of homes	Number of homes	Model for measurement error corrected
soil concentrations

I. Homes with no soil at any sample site	45	Not applicable.

II. Homes with soil, but no soil measurements	8	Log transformed soil
lead concentration = a mean for each combination of construction year
category and soil sample location and a mean for each combination of
construction year category and region.

III. Homes with all soil lead measurements equal to zero (therefore no
within-home variation)	33	All measurements assumed to be less than the
detection limit.

IV. Homes with soil lead measurements, some or all of which are non-zero
745	Log transformed soil lead concentration = a mean for each
combination of construction year category and soil sample location, a
mean for each combination of construction year category and region, and
a mean for each home

The regression analysis predicts the approximate median of the soil lead
concentrations.   Figures C.12 and C.13 show the relative median soil
lead concentration for homes within each construction year category by
sample location and region.  As expected, older homes have higher soil
lead concentrations.  Concentrations are also higher on average in the
northeast region and lower in the western region of the country.  Soil
lead concentrations are higher on average at the dripline sample
location and lower at the midyard sample location.  The measurement
error adjustment procedures excluded three percent of the floor dust
measurements as outliers.

As part of the exploratory analysis to identify the model for the data,
additional variables were considered.  In particular, orientation of the
side of the building (north, east, south, or west) and ground cover
(bare soil, grass, ivy, moss, mulch, and other or unknown) were
examined.  Neither the side of the house on which the samples were taken
nor the ground cover was a significant predictor of soil lead
concentrations, after adjusting for the effects of year of construction,
region, and sample location.

Figure C.12	Predicted Relative Median Soil Lead Concentrations by
Construction Year Category and Sample Location (based on regression
model)

Figure C.13	Predicted Median Soil Lead Concentrations by Construction
Year Category and Region (based on regression model)

Figure C.14 shows the cumulative distribution of the maximum soil lead
concentration at homes.  The figure shows three cumulative
distributions:

The maximum of the soil lead measurements at a home (bottom thin black
line).

The maximum within each home of the average soil lead measurements at
the entrance, dripline, and midyard (middle gray line).

The maximum measurement error corrected soil lead measurements (top
thick black line).

Figure C.14	Cumulative Distribution of the Maximum Soil Lead
Concentration for All Homes

Note:  Play area soil sample results were not included in the analysis
for Figure C.14. Thus, data may vary slightly from that presented in
Chapter 6.

The difference between the first and second curves shows the effect of
taking replicate soil measurements (i.e. more than one sample for a
given sample location at a home).  As more measurements are taken, it is
more likely that a sample will be taken which has an unusually high
measurement (either due to laboratory variation or due to sampling a
small area with a locally high concentration).  The second curve is most
comparable to the third curve.  The difference between the second and
the third curve is due to the measurement error correction.  The fact
that the third (measurement error corrected) curve is to the left of the
other curve is because, after correcting for measurement error, the
percentage of homes judged to have soil lead concentrations above any
selected value is decreased.

Using the measurement error corrected values, an estimated 5.6 percent
of homes with soil (about 5.3 million homes) have soil lead
concentrations above 1,200 ppm in one or more of the sampling locations
(dripline, midyard, and main entrance).  This is about two million fewer
homes than estimated using the observed soil lead measurements.  Even
fewer homes have maximum soil lead concentrations over 1,200 ppm on bare
soil.

APPENDIX D

Calculation of Soil Related Estimates

Calculation of Soil Related Estimates

In the main survey, soil samples were collected near the main entrance,
along the drip line and in the mid-yard on the side of the house with
the main entrance, and along the dripline and in the mid-yard on a
second randomly selected side of the home.  In a follow-on survey of
children's play areas involving a subset of the homes in the main
survey, residents were asked where children play around the home.  If
there was play equipment at the home or soil samples were not previously
collected in children's play areas, additional soil samples were
collected at the home in a follow-up visit.  In the play area survey,
soil samples were collected from below play equipment and from areas
designated by the respondent as children's play areas.  The main survey
has data from 831 homes.  The follow-on survey has information on 375
homes.  Details of the survey procedures are described in the Design and
Methodology report.

The tables in this report are based on data from the 831 homes whenever
possible.  However, for estimates involving soil in children's play
areas, data was only available from 375 homes.  Therefore, estimates not
involving soil were based on the main survey data.  Estimates involving
only soil were based on the play area survey data.  For estimates that
involve both soil data and data from other locations, such as the number
of homes with significant lead-based paint (LBP) hazards, estimates from
the main survey were combined with estimates from the play area survey,
as described below.

To construct estimates of significant LBP hazards using as much of the
data as possible the following procedure was used.  Estimates of the
number of homes with significant LBP hazards due to paint, dust, and
soil sources other that play soil were calculated from the 831 homes
from the main survey.  Estimates of the number of homes with significant
LBP hazards due only to soil hazards in play areas were calculated from
the 375 homes in the play area survey.  These two estimates were added
together to obtain the combined estimate of the number of homes with
significant LBP hazards from any source.

For example, the estimated number of homes with a significant LBP hazard
is 24,026 thousand.  This is the sum of 23,312 thousand homes with paint
hazards, dust hazards, or soil lead hazards in non-play areas (based on
data from 831 homes) and 714 thousand homes with significant LBP hazards
in play areas only (based on data from 375 homes).

The variance of the combined estimate depends on the portion of the
estimate contributed by the two data sources, the variance of each
estimate, and the correlation between the estimates.  Calculation of the
variance of the combined estimate is difficult because the correlation
is difficult to estimate.  However, the estimate from the main survey
contributes 97% of the combined estimate.  As a result, the variance of
the combined estimate is primarily due to uncertainty in the estimate
from the main survey.  Therefore, the confidence intervals in the tables
involving lead hazards, are based on the confidence intervals calculated
from the main survey.  The resulting confidence interval will tend to
underestimate the true variance by a small amount.  Thus, the confidence
intervals for the number of homes are calculated as follows:

The confidence interval and estimate for the number of homes with
significant LBP hazards in all but play soil are calculated from the
main survey data.

The estimate for the number of additional homes with a significant LBP
hazards in only the play soil is calculated from the play survey data.

The estimate from the play survey data is added to the estimate from the
main survey to get the combined estimate, and

The estimate from the play survey data is added to the confidence limits
for the estimate from the main survey to approximate the confidence
limits for the combined estimate.

 Title 24 of the Code of Federal Regulations, Part 35 was issued
September 15, 1999 in Volume 64 of the Federal Register, pages
50140-50231, and became effective September 15, 2000. It implemented
sections 1012 and 1013 of the Residential Lead-Based Paint Hazard
Reduction Act of 1992, which is Title X of the Housing and Community
Development Act of 1992 (P.L. 102-550).  A copy is available on the
Internet at www.hud.gov/offices/lead.

 Issued January 5, 2001 in Volume 66 of the Federal Register, pages
1206-1240, and became effective on March 6, 2001.

 The 95 percent confidence intervals for the estimates are presented in
the main body of the report.

 President's Task Force on Environmental Health Risks and Safety Risks
to Children, 2000.  Eliminating Childhood Lead Poisoning: A Federal
Strategy Targeting Lead-Based Paint Hazards (Report and Appendix).
Washington, D.C.:U.S. Department of Housing and Urban Development and
U.S. Environmental Protection Agency.

 The de minimis levels for LBP deterioration are in Section 35.1350(d)
of the Lead Safe Housing Rule.  These levels are:  deterioration of more
than 20 square feet (exterior) or 2 square feet (interior) of LBP on
large surface area components (walls, doors) or deterioration of more
than 10% of the total surface area of interior small surface area
components types (window sills, baseboards, trim).  These are the same
levels used in the U.S. Environmental Protection Agency’s lead hazard
standards rule implementing the Toxic Substance Control Act’s Section
403.

 The floor and window sill dust lead loading thresholds are dust on
floors with greater than or equal to 40 µg/ft2 lead and dust on window
sills with greater than or equal to 250 µg/ft2 lead.  They are in the
HUD Lead Safe Housing rule and in the EPA Rule Identification of
Dangerous Levels of Lead; 40 CFR Part 745, January 5, 2001.

 The thresholds for bare, lead-contaminated soil are more than 9 square
feet of bare soil with a lead concentration greater than or equal to
1,200 ppm lead, or 400 ppm for bare soil in an area frequented by a
child under the age of 6 years.  These thresholds are in the HUD Lead
Safe Housing Rule.

 HUD 1539-LBP.  Guidelines for the Evaluation and Control of Lead-Based
Paint Hazards in Housing, Chapter 7.  U.S. Department of Housing and
Urban Development, Washington, D.C.

 ASTM E 1728-95. (1995b). Standard practice for the field collection of
settled dust samples using wipe sampling methods for lead determination
by atomic spectrometry techniques.  American Society for Testing and
Materials, West Conshohocken, PA.

 ASTM E 1727-95.  Standard practice for the field collection of soil
samples for lead determination by atomic spectrometry techniques.
American Society for Testing Materials, West Conshohocken, PA.

 National Academy of Sciences (1993).  Measuring lead exposure in
infants, children, and other sensitive populations.  National Academy
Press, Washington, DC.

 Bornschein, R., Hammond, P.B., Dietrich, et al.  (1985a).  The
Cincinnati prospective study of low-level lead exposure and its effects
on child development: Protocol and status report.  Environ. Res.
38:4-18.

 Bornschein, R., Succop, P., Dietrich, et al.  (1985b).  The influence
of social and environmental factors on dust lead, hand lead, and blood
lead levels in young children.  Environ. Res. 38:108-118.

 In Title X of the Housing and Community Development Act of 1992 (P.L.
102-550), the term “lead-based paint hazard” means any condition
that causes exposure to lead from lead-contaminated dust,
lead-contaminated soil, lead-contaminated paint that is deteriorated or
present in accessible surfaces, friction surfaces, or impact surfaces
that would result in adverse human health effects as established by the
appropriate Federal agency.

 Clark, S., Bornschein, R., Succop, P., et al. (1985).  Conditions and
type of housing as an indicator of potential environmental lead exposure
and pediatric blood lead levels. Environ. Res. 38, pp. 46-53.

 Centers for Disease Control and Prevention (1991).  Preventing Lead
Poisoning in Young Children. Centers for Disease Control and Prevention,
U.S. Department of Health and Human Services, Atlanta, GA.

 Lanphear, B.P., et al. (1995).  The Relation of Lead-Contaminated House
Dust and Blood Lead Levels Among Urban Children, Final Report. Report to
the U.S. Department of Housing and Urban Development.

 A PSU is a metropolitan statistical area (MSA), county, or cluster of
counties that have a minimum population of 15,000 and do not cross
Census region boundaries.

 Throughout the volume, the concepts of lead loading and lead
concentration are used.  Lead in paint and dust are reported as loadings
(mass of lead per unit area of surface), while lead in soil is reported
as a concentration (mass of lead per unit mass of soil).  For paint,
lead loading is the number of milligrams of lead per square centimeter
of painted surface (mg/cm2). For dust, lead loading is the number of
micrograms of lead per square foot of wiped surface ((g/ft2).  Soil is
reported as the number of micrograms of lead per gram of soil ((g/g),
equivalent to parts per million (ppm).

 A PSU is a metropolitan statistical area (MSA), county, or cluster of
counties that have a minimum population of 15,000 and do not cross
Census region boundaries.

 Cross comparisons of two variables, e.g., Region by Construction Year
and Poverty by Urbanization, result in cells containing 30 or fewer HUs.
 Caution is recommended in the interpretation of these results.

 While we were most interested in children under the age of six years
for lead, we were also interested in all children up to age 18 for
allergen exposures. Comparative data from the AHS are only available for
children under age 18 in the household.  For the same reason,
post-stratification for this survey was based on children under age 18.

 If AHS or CPS data are not listed in Table 2.1, e.g., for Government
Support, they were not available in these sources.

 Family size includes all related people living in a housing unit.
Household size includes all people living the housing unit, whether or
not they are related to each other.  Thus household size tends to be
larger than family size. The 1999 CPS reports an average household size
of 3.17 and an average family size of 2.62.

 American Housing Survey 1997, Appendix D,
http://www.census.gov/hhes/www.housing/ahs/meth.html.

 The cut-off used with survey data was actually metropolitan statistical
areas (MSAs) of 2,100,000 while the available CPS cut-off is 2,500,000.
This difference in definitions explains the slight discrepancy in the
findings.

 Intact LBP present on accessible surfaces, friction surfaces, or impact
surfaces were not included in the definition of LBP hazard for the
estimates presented in this report because this information was not
specifically collected for each component.

 Window trough dust is not considered in the definition of a LBP hazard
under the HUD Lead Safe Housing Rule.

 All confidence intervals are at the 95% level for the estimated number
or percent.

  In the interpretation of the data by housing unit age, it is important
to keep the source of the data in mind.  Residents were asked the year
their home was constructed.  If a resident could not report the exact
year, he/she was asked to report the construction year in ranges:
1978-1998, 1960-1977, 1946-1959, 1940-1945, and 1939 or before.  Over
40% of respondents provided the construction year of their home in this
secondary manner.  For the purposes of the data analyses in this report,
the midpoints of the ranges were assigned as the year of construction,
viz., 1988, 1968, 1953, 1943, and 1922, respectively.  The year 1922 is
not the midpoint of the pre-1940 range; it is the median construction
year for pre-1940 housing, according to the 1995 AHS.  For these
reasons, housing unit age is reported in the four ranges given in Table
3.1; finer breakdowns should be interpreted cautiously.

 A respondent was considered to be engaged in a lead-related occupation
if they worked on any of the following activities in the previous six
months:  building demolition, paint removal (including sanding or
scraping), plumbing, sandblasting, battery manufacturing or salvage
work, explosive or ammunition work, foundry work, glass work, lead
smelter work, oil refinery work, car radiator repair, making or splicing
cable, work at a firing range or police work, welding or torch cutting,
or other lead-related industry work.

 A respondent was counted as engaged in a potentially lead-related
activity at home if they had participated in any of the following
activities in the previous six months:  make bullets or fishing sinkers,
paint cars or bicycles, reload bullets, target shoot, hunt, remove paint
from any part of the house, remove paint from furniture, sand or paint
any part of the house, solder pipes or metal, solder electronic parts,
use artists’ paint (jewelry, pictures), work with stained glass, or
work with pottery or glazes.  However, painting and renovation work on
homes built after 1978 were excluded from these estimates.

 NCLSH (1998).  Evaluation of the HUD Lead-Based Paint Hazard Control
Grant Program, Fifth Interim Report, March 1998, Prepared for the U.S.
Department of Housing and Urban Development by the National Center for
Lead-Safe Housing.

 All confidence intervals are at the 95% level for the estimated number
or percent.

 In the interpretation of the data by housing unit age, it is important
to keep the source of the data in mind.  Residents were asked the year
their home was constructed.  If a resident could not report the exact
year, he/she was asked to report the construction year in ranges:
1978-1998, 1960-1977, 1946-1959, 1940-1945, and 1939 or before.  Over
40% of respondents provided the construction year of their home in this
secondary manner.  For the purposes of the data analyses in this report,
the midpoints of the ranges were assigned as the year of construction,
viz., 1988, 1968, 1953, 1943, and 1922, respectively.  The year 1922 is
not the midpoint of the pre-1940 range; it is the median construction
year for pre-1940 housing, according to the 1995 AHS.  For these
reasons, housing unit age is reported in most tables in the four ranges
given in Table 3.1; finer breakdowns should be interpreted cautiously.

 The XRF analyzer used for the study corrected for substrate
interferences, but any actual lead in the substrate would be measured.

 It should be noted that the 1 percent of homes built in 1978-1998 with
a maximum paint lead loading above 10.0 mg/cm2 may be a result of
respondent error in reporting the date of home construction.  The year
reported by the respondent was never overridden.

 A comparison of the protocols for the two surveys is presented in
Appendix B.

 For comparison, a room 10 feet by 12 feet with an 8 foot ceiling has a
wall area of 352 square feet and a combined wall, ceiling and floor area
of 592 square feet.

 The maximum lead dust loading on any surface tested (floor, window
sill, and window trough) in the home was used to determine whether a
dust lead hazard existed.

 All confidence intervals are at the 95 percent level for the estimated
number or percent.

 The average analytical detection limit for each wipe sample was 3.5 (g.
 While detection limits for each surface are area dependent, this
corresponds to a detection limit of 3.5 (g/ft2 for a one square foot
floor sample, 7 (g/ft2 for a typical 3 inch by 24 inch sill sample, or 8
(g/ft2 for a typical 1 inch by 18 inch trough sample.

 From Table 5.2a, the percent of homes with sill dust loadings above 250
 µg/ft2 equals [100% (all homes) - 82% (homes with lead in sill dust
below 250 (g/ft2) - 2% (homes with missing data) - 2% (homes with no
sills)] = 14%.

 For averaging floor samples, only carpeted floor samples and uncarpeted
floor samples were combined for the respective average (carpeted or
uncarpeted).

 The regression modeling also suggested that homes with no evidence of
cleaning had higher floor and window dust lead loadings (see Figure C.7
and Figure C.9).  Higher window dust lead loadings were suggested for
rented homes as compared to owned homes, surfaces that were not smooth
and cleanable as compared to smooth surfaces, and windows with vinyl
mini-blinds as compared to those without vinyl mini-blinds (see Figure
C.9).

 Dust lead loading data is presented in box plot form.  Each box plot
shows a univariate data distribution, for example, the dust samples
collected from a specific location (e.g., entrance floor). The box in
the box plot represents the middle 50 percent of the data; the bottom of
the box gives the 25th percentile; the top of the box gives the 75th
percentile, and the horizontal line inside the box gives the median or
50th percentile.  The vertical lines extending from the top and bottom
of the box reach to the largest and smallest observations, respectively,
except for outliers.

 The sample limit of detection for this study was determined to be 20
ppm by testing four distinct soil types from among the study samples in
accordance with EPA SW 840 Method 3050 procedures.

 All confidence intervals are at the 95 percent level for the estimated
number or percentage.

  Even fewer homes will have greater than 9 square feet of bare soil
above 400 ppm or 2,000 ppm (soil lead hazard as specified in the Lead
Safe Housing Rule).

 Francek, M.  (1992.)  Soil lead levels in a small town environment: A
case study from Mt. Pleasant, Michigan.  Environmental Pollution 76. pp.
251-257.

 Soil lead concentration data is presented in box plot form.  Each box
plot shows a univariate data distribution, for example, the soil samples
collected from a specific location (e.g., main entry). The box in the
box plot represents the middle 50 percent of the data; the bottom of the
box gives the 25th percentile; the top of the box gives the 75th
percentile; and the horizontal line inside the box gives the median or
50th percentile.  The vertical lines extending from the top and bottom
of the box reach to the largest and smallest observations, respectively,
except for outliers.

 The sample limit of detection for this study was determined to be 20
ppm by testing four distinct soil types from among the study samples in
accordance with EPA Method 3050 procedures.

 Francek, M.  (1992.)  Soil lead levels in a small town environment: A
case study from Mt. Pleasant, Michigan.  Environmental Pollution 76. pp.
251-257.

 The sample limit of detection for this study was determined to be 20
ppm by testing four distinct soil types from among the study samples in
accordance with EPA Method 3050 procedures.

 At the time the 1990 LBP survey was conducted, 500 ppm was the
guideline in EPA's Interim Guidance on Establishing Soil Lead Cleanup
Levels at Superfand Sites, September 7, 1989 (OSWER Directive
#9355-4-02).

 Another source of error in the survey is response bias, i.e., how
correct was the information provided by the respondents?  Significant
information obtained from respondents included year of construction (HU
age) and age of children.  These data were not verified by other means
and are thus associated with an unknown amount of error.  However, the
overall distribution of HU age and age of children reported by survey
respondents were consistent with study expectations (see Volume II,
Chapter 2), indicating no systematic bias in these responses.

 In the data collection completion rate, the ineligible cases are
included in both numerator and denominator.  If the ineligible cases are
not included, the data collection completion rate drops from 90 to 88
percent.

 EPA’s National Lead Laboratory Accreditation Program (NLLAP) requires
wipes to be used in the field to have less than 5 (g lead/wipe.

 Personal communication with Sandy Roda, Director, Hematology and
Environmental Laboratory, University of Cincinnati.

 Rounding to the nearest tenth unit for classifying surfaces is
equivalent to classifying a surfaces as having LBP if the average lead
loading across the surface is 0.95 or greater.

 Whatever the explanation for the pattern in the data, the patterns are
not consistent with the assumptions behind the measurement error
adjustment.  Since no consistent pattern was found that would provide a
better model, the measurement error adjustment as described in Appendix
C (Volume II) was applied to the data.  The results provide one estimate
of the effect of measurement error on the assessment of the number of
homes with LBP.  However, other assumptions or other modeling approaches
may provide very different estimates of the magnitude of the effect of
measurement error.

 Care should be taken when comparing these data to tables presented in
Chapter 4. For example, a home was included in Table 4.1 if any one
component had LBP.  Values plotted in Figures 7.2 through 7.5 represent
the predicted median paint loadings in the home (i.e., for all
components).  Thus, while Table 4.1 shows that 53% of homes in the
Midwest have LBP, Figure C.3 shows that the median lead loading for all
components is lowest for homes in the Midwest.  This could be due to
there being fewer components with LBP or the lead content of individual
components could be lower in Midwest homes.

 These results suggest that cleaning activity will generally affect dust
lead loading.

 The average of the available midyard and average of available dripline
samples were used for the measurement error analysis, regardless of
which side of the house they were collected.  That is, separate
assessments were not made for midyard and dripline areas on each side of
the home.

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

ES- PAGE   x

WESTAT		October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	1-  PAGE  6 	October 31, 2002

WESTAT	2-  PAGE  6 	October 31, 2002

WESTAT	3-  PAGE  4 	October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	4-  PAGE  17 	October 31, 2002

WESTAT	5-  PAGE  22 	October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

 PAGE

WESTAT	6-  PAGE  14 	October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

7- PAGE   14

WESTAT		October 31, 2002

7- PAGE   1

WESTAT		January 9, 2001

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	A-  PAGE  10 	October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	B-  PAGE  1 	October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	B-  PAGE  5 	October 31, 2002

WESTAT	B-  PAGE  2 	April 18, 2001

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	C-  PAGE  1 	October 31, 2002

National Survey of Lead	Final Report, Vol. I

and Allergens in Housing	Analysis of Lead Hazards

WESTAT	D-  PAGE  2 	October 14, 2002

0

200

400

600

800

1000

1200

Window sill

Window trough

1750-1939

1940-1959

1960-1977

1978-1998

Privately owned

Publically owned

Rented

   African American

Other/Unknown

White

Appears clean

 Some evidence of cleaning

No evidence of cleaning

Unknown

Adult bedroom

Bathroom

Child bedroom

Kitchen

Living room

Other

Unknown

Smooth and cleanable

Not smooth/cleanable

No vinyl mini-blinds

Vinyl mini-blinds

Unknown

Relative Median Dust Lead Loading,



g/ft

2

 (see text)

Sample

location

Construction

date

Tenure

Race

 category

Overall Household

Cleanliness

Room type

Sample

surface

Vinyl mini-

blinds