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NBSIR 77-1250

Analysis of Housing Data

Collected in a Lead- Based

Paint Survey in Pittsburgh,

Pennsylvania

Part I

Douglas R. Shier

and

William G. Hall

Applied Mathematics Division

Institute for Basic Standards

National Bureau of Standards

Washington, D.C. 20234

Report Prepared for

Center for Building Technology

Institute for Applied Technology, NBS

March 1977

Issued May 1977

Sponsored by the

Office of Policy Development and Research

Department of Housing and Urban Development

Washington, D.C. 20410

NBSIR 77-1250

ANALYSIS OF HOUSING DATA

COLLECTED IN A LEAD-BASED

PAINT SURVEY IN PITTSBURGH,

PENNSYLVANIA

PART I

Douglas R. Shier

and

William G. Hall

Applied Mathematics Division

Institute for Basic Standards

National Bureau of Standards

Washington, D.C. 20234

Report Prepared for

Center for Building Technology

Institute for Applied Technology, NBS

March 1977

Issued May 1977

Sponsored by the

Office of Policy Development and Research

Department of Housing and Urban Development

Washington, D.C. 20410

v Niu o< S

U S. DEPARTMENT OF COMMERCE, Juanita M. Kreps, Secretary

Dr. Sidney Harman, Under Secretary

Jordan J. Baruch, Assistant Secretary for Science and Technology

NATIONAL BUREAU OF STANDARDS. Ernest Ambler, Acting Director

TABLE OF CONTENTS

Bage

List of Tables ii

List of Figures iii

Acknowledgement v

Abstract vi

1. Introduction ~\

2. Survey Design 5

2.1 Housing Selection Strategy 6

2.2 Important Characteristics in Survey design 7

2.3 Measurement of Lead Levels 9

3. Data Collection Procedures 11

4. Analysis of Housing Data 18

4.1 Housing-Delated Variables 20

4.2 Characteristics of the Sample 23

4.3 Housing Survey Results 28

4.4 Summary of Results 62

5. References 64

Appendix A: Instructions for Completing the Housing

Survey Form 66

Appendix B: Data Base Specifications 74

Appendix C: Table of Contents to Data Analyses

Performed 87

i
LIST OF TABLES

page

1. Percentage of Dwelling Units by Age Oategorv • 27

2. Percentage of Interior Surfaces Exceeding Fixed

Lead Levels 36

o 3. Average Lead Level Measures bv Room fpg/cm‘ ) 41

h. Percentage of Interior Surfaces in Pre 1^40 Units

Exceeding Fixed Lead Levels 42

5. Percentage of Rooms with Highest Reading Exceeding

Fixed Lead Levels 53

6. Percentage of DTT’s (Rooms) Having Surfaces in

Peeling or Bad Condition 54

O 7A. Average Value for DII Mean Reading (mg/cm ) 56

7B. Average Value for DU High Reading (mg/cm^) 57
LIST OF FIGURES

Page

1. Data Collection Form for Housing Inspections 13

2. PSE Questionnaire Form 17

3. Flow of Information 19

4. Percent of Sample by Census Tract Group 26

5. Histogram for Mean Trim Reading/DU in Pre 194Q Units 29

6. Cumulative Distribution for Mean Trim Reading/PTT

in Pre 1940 Units 32

7A. Cumulative Distributions for Highest Wall Reading

in Pre 1940 Units 33

7B. Cumulative Distributions for Highest Fall Reading

in 1940-1959 Units 34

8A. Cumulative Distributions for Dry Room Falls, by

Age Category 37

8B. Cumulative Distributions for Wet Room Falls, by

Age Category 38

8C. Cumulative Distributions for All Doors, by Age

Category 39

9A„ Cumulative Distributions for Walls in Pre 1940

Units, by Room Type 44

9B. Cumulative Distributions for Doors in Pre 1°40

Units, by Room Type 45

9C. Cumulative Distributions for Falls in 1

Q 40-195Q

Units, by Room Type 46

9D. Cumulative Distributions for Doors in IQAO-iQ^Q

Units, by Room Type 47

iii
page

9E. Cumulative Distributions for Falls in 1960-1Q75

Units, by Room Type 48

9F. Cumulative Distributions for Doors in 1960-1975

Units, by Room Type 49

IOA. Mean Trim vs. Lead Interval for Falls in Dry

Rooms, Pre 1940 Units 50

IOB. Mean Trim vs. Lead Interval for Falls in Fet

Rooms, Pre 194D Units 5?

IIA. Cumulative Distributions ('Pittsburgh and

Fashington) for Falls in Pre 1 Q 40 Units 58

IIB. Cumulative Distributions ('Pittsburgh and

Fashington) for Walls in 1Q4U-1959 Units 59

IIC. Cumulative Distributions (Pittsburgh and

Fashington) for Doors in Pre 1°40 Units 60

IID. Cumulative Distributions (Pittsburgh and

Washington) for Doors in 1040-1050 nn its 61
ACKNnFLFnOFMFVT

The authors would like to acknowledge the constructive and helpful

suggestions of Dr. Irwin H. Billick, Program Manager, Lead-Based Paint

Poisoning Prevention Research, Department of Housing and Urban Development.

Thanks are also expressed to Harvey F. Berger, Program Manager, Mousing

Technology Programs, National Bureau of Standards, for freauent and

valuable discussions during the preparation of this report.

v
ANALYSIS OF HOUSING DATA COLLECTED IN A LEAD-BASED

PAINT SURVEY IN PITTSBURGH, PENNSYLVANIA

Part I

Abstract

This report is a companion document to a previous report (NBSIR

76-1024) on blood lead levels of children tested during a lead-based

paint survey in Pittsburgh, Pennsylvania. The emphasis in this report

is on the methodology used and types of housing-related information

collected by the survey. Through the use of portable x-ray fluorescence

lead detectors, measurements were taken from a variety of surfaces within

rooms of the dwelling unit as well as at locations exterior to the unit.

Analyses of these x-ray fluorescence measurements established that older

housing units exhibit considerably greater lead levels than newer housing

units. In addition, wet rooms (kitchens and bathrooms) have higher

levels than other (dry) rooms, rooms with a poor surface/substrate

condition have higher levels than rooms with a good surface/substrate

condition, and trim surfaces (e.g., doors, windows, baseboards) have

higher levels than walls. Also, exterior surfaces show higher readings

than functionally similar interior surfaces. While the present report

concentrates on the housing aspect of the survey, subsequent processing

of the Pittsburgh data is under way to determine possible relationships

among blood lead levels, socioeconomic variables and housing-related

characteristics

.

Key Words: Children; data analysis; housing; lead paint: lead

poisoning; surveys; x-ray fluorescence.

vi
1. INTRODUCTION

This report describes the design, methodology, analysis and results

of a large-scale housing survey conducted in Pittsburgh, Pennsylvania.

The primary purpose of the survey was to assess (using a rather detailed

series of measurements on the sampled dwelling units) the extent,

magnitude and distribution of lead-bearing surfaces within the units.

In addition, selected measurements of lead levels were recorded for

exterior surfaces of the dwelling units.

The Department of Housing and Urban Development (HUD) has been

mandated by Title III of PL 91-695, the Lead-Based Paint Poisoning

Prevention Act of 1971, to determine the nature and extent of the

lead paint poisoning hazard to children throughout the nation. HUD

has also been directed to promote the development of lead detection

devices, and has been charged with assessing the performance and usefulness

of materials and systems for abatement of lead paint hazards.

The National Bureau of Standards (NBS) has provided technical

assistance to HUD in each of the above areas of responsibility. In

particular, the HUD sponsored housing survey detailed in this report

was performed in response to the first of these responsibilities.

In 1973, HUD requested that NBS develop a survey procedure to update

and refine its previous estimates [1]* of the number of dwelling units

containing lead-based paint. While housing surveys for quantitatively

assessing lead sources have been conducted in other cities [2, 3,

4, 5, 6], this survey is believed to be the first manor effort at

^Figures in brackets indicate references listed in Section 5 (pp. 64-65)

1
collecting substantial data on lead in housing in a systematic way.

In contrast to earlier surveys, the survey described here was a largescale, statistically designed effort aimed at characterizing (using

an extensive series of measurements) the lead levels in dwelling units

comprising an entire city, and not simply a high-risk target area.

Previous NBS reports [7, 8, 9] have dealt with other aspects of this

survey, including preliminary testing of the survey methodology.

The primary objectives of the survey were:

1) To determine the distribution of representative measures of lead paint

content with respect to dwelling type.

2) To determine the distribution of such measures, within dwelling type,

according to surface type, surface condition and room type.

3) To examine, using statistical techniques, relationships between

measures of lead levels in dwellings and blood lead levels of

children resident in those dwellings*.

A) To demonstrate a feasible methodology for collecting housing data and

to construct a data base for support of other specific tasks within the

NBS and HUD Lead Paint Research Programs.

There were, as well, a number of secondary objectives of the survey.

One was that of providing a "clean" data base of collected and derived

information to support future research and guide policymakers in the general

area of lead-associated hazards. Another secondary objective was to

explore, to the maximum extent practicable, possible relationships among

*Preliminary results of such statistical analyses have been previously

reported [8],

2
the data gathered and relevant Information collected from other sources.

The housing survey methodology developed by NBS included procedures

for sample construction, data collection and statistical analysis. The

methodology was pre-tested in Frederick, Maryland during the spring

of 1973. Procedures were then revised in light of this pre-test experience

and used during a field test in Washington, D.C. later in 1973 [7],

Further refinements were incorporated into the methodology, and computer

software for editing and analyzing the data was also developed.

The city selected to carry out the survey was to be typical of the

larger northeastern cities in terms of age, climate and demographic

characteristics. It was also desirable that the city have an appropriate

agency with the technical and institutional capabilities for operating in

both the housing and public health areas. The city eventually selected

for this survey was Pittsburgh, Pennsylvania, and the Allegheny County

Health Department (ACHD) was designated as the agency to perform the survey.

Pittsburgh is centrally located within the dense population belt defined

by the Great Lakes basin and the Northeast Corridor. It is a large older

city, but one which is sufficiently compact so as not to require excessive

travel times between inspected dwelling units. The ACHD is responsible

for both the housing and public health functions exercised by the city e

Furthermore, prior to the survey, in 1974, the ACHD had an ongoing lead

screening program, an experienced and able staff, and an enthusiastic desire

to carry out the survey. These characteristics, plus its relative proximity

to Washington (which made collaboration and liaison much easier) , served

to make Pittsburgh and the ACHD ideal for the conduct of this survey.

Approximately 4000 dwelling units were visited by two-person teams of

3
ACHD housing inspectors during the course of this survey (summer 1974 -

spring 1975). On the average, a single inspection team visited 5.6 units

per day. Roughly 3300 of these units received a complete inspection. If,

during inspection of a unit, children under seven years of age were

identified as residents, a medical technician team subsequently visited the

dwelling unit in order to collect additional socioeconomic data and a

blood sample for lead analysis. Such data were gathered from a total

of 456 children representing some 296 households out of 552 households

with children under seven. The resulting data base (incorporating

identification, housing data, blood lead results and socioeconomic data)

contains more than 2.5 million characters of information.

The remainder of this report is divided into three sections and three

appendices. Section 2 deals with design aspects of the survey and includes

a discussion of alternative measures for characterizing lead levels in the

dwelling unit as a whole (or in part). This section also discusses

important housing characteristics expected to be related to the presence

and amount of lead-based paint. Section 3 defines the data elements

collected during the housing inspections and the subsequent blood

collection effort. Quality control procedures relevant to the collection

and analysis of data are also discussed here, as well as the construction

of a "clean" data base using appropriate computer programs for data

editing. Section 4. reports the results of analyses performed to determine

the distribution of lead-based paint both within and among dwelling

units. A preliminary discussion of observed relationships between

children's blood lead levels and various measures of lead levels in

their dwelling units has been reported [8], and a more thorough analysis

4
is in preparation.

Appendix A describes the procedures used for completing the housing

inspection form, while Appendix B specifies the actual formats for

data elements comprising the data base. Appendix C provides a table

of contents to the various analyses performed using the data collected

in the housing survey.

The multiplicity of measurements taken and of additional data items

collected makes it impractical to present the results of all analyses

performed using the information in the data base. The salient results of

such analyses are, however, presented and discussed in this report

(which is Part I of a two-part document) . Additional detailed tables

(which are representative of the rather voluminous tabulations that

have in fact been made) are presented separately in Part II of this

document. The tables and figures used in Part I are for the most

part derived from the tabulations of Part II, supplemented by

information contained in another NBS report [7].

2. SURVEY DESIGN

This section begins by describing the strategy used to select those

dwelling units included in the Pittsburgh survey. The next portion of this

section discusses certain housing-related characteristics thought to be

relevant to the lead levels of surfaces in dwelling units. Such considerations were important in devising the contents of the housing inspection

form. In addition, the issue of how actually to aggregate the lead levels

found in dwelling units is addressed in the final portion of this section.

5
2.1 Housing Selection Strategy

The strategy used to select housing units for this survey was

based on the desire to obtain data characterizing the entire Pittsburgh

area, and not simply certain areas where high lead poisoning incidence

is suspected. For this reason, a' representative random sample of

the entire Pittsburgh area was needed. This was accomplished by drawing

a simple random sample from the Polk [10] city directory for Pittsburgh.

A sequence of computer-generated random numbers was used to perform

the sample selection, as described in [9].

The advantage of a simple random sample is that it carefully

balances the cost of performing the survey against the accuracy of

results required by the survey. That is, this procedure can achieve

quite accurate results, while still being much more efficient and much

less costly than a complete enumeration of the target population. Since

in a simple random sample, each unit has an equal likelihood of being

selected, this method is not expected to produce serious statistical

biases in one direction or the other.

In the present survey, a sample size of 4000 dwelling units was

chosen. This sample size was large enough to ensure the required

accuracy (within 5% at a 95% level of confidence) for each of a number

of subpopulations defined by housing age and occupancy class. The sample

size value is consistent with the calculations presented in [9], as

applied to these subpopulations. In addition, the sample size was large

enough to include sufficient information about various categories of

characteristics considered important in the survey. A discussion of

those characteristics follows.

6
;

2 . 2 Important Characteristics in Survey Design

The design of the survey form used in the housing inspections

was based upon housing-related characteristics believed to be important

in describing the potential lead-based paint hazard of a dwelling

unit. Any such potential hazard clearly depends on the lead levels

of various painted surfaces within the dwelling unit as well as the

accessibility of paint on these surfaces to a child. On the one hand,

the lead levels on surfaces in a dwelling unit are expected to depend

on the unit’s construction characteristics and the historical maintenance

(or decoration) practices to which the unit has been subjected. On

the other hand, the accessibility of paint on a surface is related

to its location (e.g., room type and surface type) and the condition

of the substrate (holes, cracks, etc.) or the paint film itself (cracked,

peeling, etc.).

The types of construction characteristics relevant to surface

lead levels deserve further amplification. In particular, the following

construction characteristics were thought likely to be important in

determining lead levels on surfaces.

(1) Age of Housing . The age of the units, measured in this survey using

the date of construction, was expected to be a reliable predictor for the

existence of lead-based paint. Indeed, the age of housing has often been

cited as a major determinant for the presence and amount of lead-based paint

[2, 3, 11, 12], and a careful analysis of this relationship is accordingly

one of the aims of this report. There are several objective reasons for

expecting such a relationship. First, the age of a unit is likely to be

7
a good observable Indicator (at least within construction and material

types) for the thickness of existing paint films [13]. A second reason

is related to the fact that paints marketed over the years have had

decreasing lead contents [13, 14]. This situation has resulted from

changes in paint technology and increased regulation of paint usage.

Prior to roughly 1940, better quality paints had high lead content

and were commonly used in dwelling units; in the era from 1940 to 1960,

evolving paint technology produced good paints containing less lead;

since 1960, there has been an intensive effort to reduce further the

lead content of paints.

(2) Construction Type and Materials . The type of construction used

in the dwelling unit (e.g., frame or concrete) as well as the type

of base material used certainly have an impact on the type of paint

used, if any. Units having construction types or base materials that

do not require painting, for either functional or aesthetic reasons,

are likely to have been painted less frequently than other units,

if at all.

(3) Occupancy Characteristics . Still another class of factors on which

lead levels may depend is related to the past or present occupants. These

variables include ownership status of the unit (owner-renter), income,

family composition, educational level and related socioeconomic indicators.

The survey conducted in Pittsburgh was only able to gather information

about present (and not past) occupants. However, because Pittsburgh

has a relatively stable population compared with cities of similar size

8
and demography, major differences are not expected to exist between the

characteristics of past and present occupants.

In addition to the lead levels of surfaces, the accessibility of such

surfaces to children is also an important factor in determining the

potential risk of lead-based paint ingestion. For example, a surface with

a peeling, powdering or flaking paint film or a deteriorating substrate

can cause whatever paint is present to be more immediately available than

a sound surface with a tightly adhered paint film. Similarly, a chewable

surface such as a door edge is more accessible to a child than a ceiling.

Accordingly, the housing inspection was designed to provide information

about the location and condition of various surfaces within the dwelling

unit. This location aspect is described both in terms of surface type

(walls, ceilings, windows, doors, etc.) and room usage (bathroom, kitchen,

etc.). The condition aspect is described by means of specific condition

codes developed to characterize the substrate as well as the surface of

interest. Since the condition of both substrate and surface will normally

deteriorate with the passage of time, the age of a unit may also serve as

a general indicator of condition.

2 . 3 Measurement of Lead Levels

The various characteristics just discussed are for the most part both

observable and quantifiable. For example, the age categories "Pre 1940”,

”1940-1959” and ”1960-1975” were used in the housing inspections. These

categories can be determined with reasonable accuracy (by householder's

knowledge or inspector's estimate), are compatible with classifications used

in Census Bureau housing publications, and correspond well to the eras in

9
which different paint technologies and usages were prevalent [13, 14].

Section 3 discusses in greater detail the actual contents of the housing

inspection form and the specific observations or measurements taken in

each dwelling unit.

One of the most important characteristics of a dwelling unit is a

description of the lead levels of various surfaces in the unit. The

measurement of lead levels in this study was made using a portable

x-ray fluorescence (XRF) lead detector. Characteristics of such devices

are described at greater length elsewhere [15, 16, 17]. Measurements,

in units of milligrams of lead per square centimeter, were taken at

various locations in each of several rooms within the dwelling as

well as at various locations exterior to the dwelling.

While the interpretation of any individual measurement on a specific

surface is straightforward, the aggregation of these individual measurements

into a measure of lead level for the entire dwelling is a more difficult

matter. There are several desirable properties that any such aggregated

measure should possess, namely:

1) The measure should be easily derivable from characteristics that

can be observed and quantified.

2) The measure should be conceptually simple and amenable to an

unambiguous interpretation.

3) The measure should take into consideration existing standards

which have been used by various political subdivisions in legislation

and in enforcement programs.

4) The measure should be amenable to various stratifications. In

practice this means that the measure should be defined by a continuous

10
variable (i.e., one assuming a continuum of values).

An aggregated measure which simply indicated that one dwelling unit

(on an overall basis) contains more than some specified level of lead*

while another does not, would not satisfy criterion 4 above. Such a

binary (YES-NO) measure would represent a great oversimplification and

could not be used to provide a gradation of dwelling units from "containing

more lead" to "containing less lead." In Fact, a number of alternative

continuous measures or statistics were used in describing the lead levels

in a dwelling unit (or possibly a room within the dwelling) : namely, the

highest lead level present, the mean lead level, the median lead level,

and the fraction of surfaces that exceed some specified level. The

highest lead level present was considered important both because it

is an estimate of the maximum possible lead level which can be associated

with a unit and because it is consistent with the language typical

of legislation and abatement policies [18, 19]. The other aggregated

measures were used because they also are reasonable quantifications of

the amount of lead present in a dwelling unit; in addition, they can accommodate the classification of surfaces according to a range of lead levels.

Since the specification of a fixed level in the last of these measures

is somewhat arbitrary, a sequence of fixed levels was actually used, thus

providing a series of distinct (but related) aggregated measures.

3. DATA COLLECTION PROCEDURES

This section describes the various data elements gathered during

the dwelling unit inspection and the subsequent collection of blood samples

*Lead levels exceeding 2.0 mg Pb/cmz are considered by some health authorities to pose a potential "hazard."

11
samples together with socioeconomic information. Ouality control

procedures were instituted during all phases of the survey to ensure

the integrity of data collected. Such procedures are also briefly

discussed in this section.

As previously mentioned, the housing data were collected for

approximately 4000 dwelling units selected at random using a city

directory for Pittsburgh. Two-person teams of ACHD housing inspectors

collected these data during the course of inspecting both the interior

and exterior of a unit; such an inspection typically required 30-40

minutes to complete. If it was determined that a child aged six years

or less was resident in the unit, a subsequent medical technician

team from the ACHD was sent to obtain a blood sample and to gather

socioeconomic (as well as child-related) data.

The housing data collected consisted of observations (e.g., the

number and condition of surfaces) made by the team leader, lead level

measurements obtained on given surfaces using a portable XRF device, and

(for a limited number of items) responses from the occupant of the dwelling.

The team leader would record such information on the data collection form

(DCF), which is shown in Figure 1; the second member of the housing inspection

team assisted in operating the XRF device. All XRF readings were indicated

O as milligrams of lead per square centimeter (mg Pb/cm ) and a single

reading was obtained for each of a number of specified surfaces*.

Detailed instructions for performing this data collection, together with

*0f course, there is no assurance that a single XRF measurement will

fully characterize a given surface. Practical considerations, however,

precluded repeated measurements on the same surface.

12
13
explicit definitions of the individual data elements, appear in Appendix

A.

In general structure, the DCF consists of four sections: an identificat

section, an interior section, an exterior section and a glossary section.

Each of these sections has somewhat different characteristics and is describe

briefly below.

(1) Section I (IDENTIFICATION) contains information that is associated

with the dwelling unit as a whole. Also included here is information

pertinent to the identity of the inspection team, the date of inspection

and the particular XRF instrument used. More specifically, the dwelling

unit identifiers include a unique serial number, census tract, ZIP

code, and street address of the dwelling unit. All of these items

appear in the first line of this section. On the second line appear

the inspection team data: namely, the XRF serial number, XRF calibration

parameters, inspector identification and date. Such inspection team

data were used in internal management and quality control procedures.

The initial two fields of the third line are associated with XRF

readings taken on a reference standard test block (of known lead content)

prior to inspecting a unit. These readings were used by the inspection

team to determine if an on-site recalibration of the XRF device was

necessary. The remaining fields on this line are associated with the

dwelling unit and its occupants; into each field is entered a code

whose definition appears in the glossary section of the DCF. The fields

TYPE, XS and OC (representing construction type, exterior building

surface and occupancy class) are completed using the team leader’s

14
observations of the unit. Entries in the last six fields of this line

are based on information supplied by the occupant.

(2) Section II (INTERIOR) contains one line (lines 04 through 15) for each

room of the dwelling which was inspected; each such line follows the

same format. All fields except those designated by COND (condition)

or NUMBER contain XRF readings (in tenths of mg/cm ) for the surface

specified in the field heading. The field was left blank if the surface

did not exist or was unpainted, and an "X" was entered if the surface

was inaccessible to the inspection team. Each COND field is composed

of a three-character code (from the glossary section) indicating the

substrate material, substrate condition and surface condition for the

specified aggregate of surfaces. The NUMBER fields contain, respectively,

the number of windows and the number of doors present in the room.

Finally, line 17 contains the number of times the family moved during

the preceding six-year time period. Line 16 of the DCF was not used.

(3) Section III (EXTERIOR) follows the same general form as Section II

except that the XRF readings and condition codes refer to specified exterior

surfaces rather than interior surfaces. Moreover, for interior surfaces the

COND field is used to characterize all similar surfaces within a room

(e.g., all walls), while for exterior surfaces the COND field is associated

with one particular surface. In addition, line 18 contains three fields

that are used to record the number of rooms of the indicated types

which were present in the dwelling unit but could not be inspected.

15
(4) Section IV (GLOSSARY) contains definitions for the eleven codes used in

various lines of the data collection form.

In a separate follow-up collection of data (planned and conducted

by the ACHD) , blood samples and child-related data were obtained from

456 of 812 children identified as eligible for inclusion in the study.

The child-related data gathered during this visit included physiological,

sociological and environmental elements. Such data are subsequently

referred to as PSE data. The data elements collected on the PSE form

(see Figure 2) are defined clearly on the form itself. A subsequent

report will separately discuss and analyze the PSE data in relation

to the children's blood lead levels and the levels of lead detected

in their dwelling units.

At the end of each day, a supervisor reviewed the data collection

forms submitted by inspection teams in order to assure the consistency

and accuracy of data obtained during dwelling unit inspections. Where

information was missing or inconsistent, a follow-up data collection

effort was then initiated to regather those data items which could

be obtained by a telephone call or an exterior inspection of the unit.

The fact that a follow-up of missing data was instituted also served

to make the inspection teams more careful in collecting the data and in

producing a complete housing form. Additional quality control procedures

were used in the determination of children's blood lead levels, and

these are described in another NBS report [8],

Further validation and correction of the data base occurred as

information was keypunched and entered into a computer system. The

16
Figure 2 PSE Questionnaire Form

PSE Condition of Child

Serial Number ACHD Personnel

Date Census Tract Blood lead

1. Age of child (months)

2. Sibling rank

3. Height (inches)

4. Weight

5. Sex

6. Race

7. Time resident in unit (months)

8. Time resident in census tract (months)

9. Percent of waking hours child spends in house Less than 25% 25% - 50% 50% - 75% 75% or more

10. Does the child spend more than 25% of waking hours at a friend's or relatives?

Yes No If "yes" give census tract

11. Does child attend pre-school or day care? Yes No If "yes", Days/Week Hours/Day

Census Tract

12. Two favorite outdoor playing areas Surface Spot #1 Spot #2 Grass __

Dirt Census tract Pavement

13. Favorite indoor playing area

14. Evidence of pica nopossible

confirmed

15. Number of siblings under 6 7-11 12 or over

16. Family income 0 - 3,999

4,000 - 6,999

7,000 - 10,999

over 11,000

17. Work status Mother works Father works Both work _____

18. If both parents work, child is cared for by:

Siblings Adult relative Adult non-relative ________

Day care

19. Parental education level

Mo ther Father Highest level _____

achieved

cares not to answer

20. Origin of parents:

Mother Father Allegheny County

Outside Allegheny

21. Comments & observations (concerning child's development, behavior, supervision, etc)

22. Number of parents in household

23. Number of adults in household

17
general approach was to use multi-stage validation and correction procedures

The key procedure was a computer program that performed consistency

and validity checks on the data submitted. Entries from the DCF or

the PSE forms which were inconsistent or invalid were defaulted to

a "most likely" or "unknown" category, and the defaulted value was

then entered into the data base. Each field with a defaulted value

generated an appropriate error message; such error messages were used

in conjunction with the hard copy files for reconciliation and for

constructing required corrections. The final output of this process

was a "clean" data base that could be used for subsequent analyses.

The general flow of information is shown in Figure 3 together

with the appropriate quality control measures taken. In this figure,

a rectangle is used to indicate a physical operation; also, a circle

indicates a document file, while a triangle indicates a computer file.

Annotated flow lines are used to denote flow of the specified information.

An unlabelled flow line denotes access, while a dashed flow line indicates

a cycle change in the data base. Operations above the dashed line

were performed by the ACHD, and those below were performed by NBS.

4. ANALYSIS OF HOUSING DATA

In this section, attention is focused exclusively on characterizing

(in terms of measured lead levels) the dwelling units of the sampled

area. In particular, the relations of various housing characteristics

(such as age of structure) to the lead levels occurring in dwelling

units are investigated here. Furthermore, the distribution of leadbearing surfaces within a typical dwelling unit is also examined.

18
Figure 1

Flow of Infornation

19

Access Updates
Subsequent processing of the current data base will concentrate on

analyzing data items associated with the children for whom a blood sample

was taken. In such analyses, relationships among the blood lead determinations, socioeconomic variables and characteristics of the dwelling

units will be studied. A preliminary summary of relationships between

blood lead levels and certain housing/demographic characteristics has

already been reported [8],

4 .

1

Housing-Related Variables

Before proceeding to various analyses of the housing data, it will

be useful to identify and describe certain housing-related variables

whose influence is to be studied. Two types of general housing characteristics are most relevant here:

(1) Occupancy Class . A number of distinct (but not necessarily mutually

exclusive) occupancy classes have been considered in the analyses that

follow. These classes were specified in order to determine whether lead

distribution patterns are indeed different among the various occupancy

classes. Any such differences would be important to ascertain, since

governmental authority and responsibility can vary according to occupancy

class. Occupancy class can be defined by several descriptors: occupancy

status (owner-renter), mortgage type (VA-FHA-conventional) , number of

units within the building, and extent of governmental assistance (e.g.,

public or subsidized housing) . A large number of potential combinations

are thus possible, but for the analyses conducted here the following

ten categories were considered most relevant:

SINGLE FAMILY - OWNER OCCUPIED - FHA

20
SINGLE FAMILY - OWNER OCCUPIED

SINGLE FAMILY - RENTER OCCUPIED

SINGLE FAMILY

MULTIFAMILY - 2 to 4 UNITS /BUILDING

MULTIFAMILY - 5 or MORE UNITS /BUILDING

MULTIFAMILY (2 or MORE UNITS /BUILDING)

PUBLIC HOUSING - 2 to 4 UNITS /BUILDING

PUBLIC HOUSING - 5 or MORE UNITS/BUILDING

PUBLIC HOUSING

(2) Age of Unit . The age categories used here reflect distinguishable

eras of paint technology, can be accurately estimated, and are consistent

with age classifications used in Census Bureau housing publications.

The three dwelling unit age categories are: PRE 1940, 1940-1959 and

1960-1975.

In addition to the above characteristics (which distinguish one

dwelling unit from another) , certain other characteristics are pertinent

in describing the distribution of lead within a given dwelling unit.

Four variables appear reasonably important in specifying collections of

potential lead-bearing surfaces within the unit:

(1) Location . It is useful to distinguish those surfaces occurring

interior to the dwelling unit from those occurring exterior to the unit.

This distinction is considered important because of differing decoration/

maintenance practices, differences in types of paint applied, and differing degrees of exposure to various environmental sources of lead (e.g.,

industrial or automotive emissions) . The two general categories of

21
location considered here are denoted by INTERIOR and EXTERIOR.

(2) Room Type . This characteristic has been included since a pre-test

[7] for the present housing survey indicated different lead level

distributions according to room type. Moreover, paint usage and

decoration practices are expected to differ by room type. It has been

useful therefore to distinguish two general categories of rooms. WET

rooms include kitchens and bathrooms, while DRY rooms include all rooms

other than kitchens and bathrooms (e.g., bedrooms, living rooms, dining

rooms)

.

(3) Surface Type . The pre-test also indicated that differences in

lead levels exist with regard to surface type. More specifically, the

different surface types analyzed here are WALLS, DOORS, and WINDOWS. In

addition, the designation TRIM is used to signify the collection of

doors, windows, baseboards, radiators, cabinets and fireplaces; this aggregate collection of surfaces appears meaningful, inasmuch as similar decorating practices and paint types tend to be used for all such surfaces. It

is likely that surface type (as defined here) also plays an important

role in describing the degree of accessibility to available paint.

(4) Surface Condition . The condition of a surface also provides a means of

indicating accessibility. The categories used here are PEELING, BAD,

EITHER and BOTH. The PEELING designation means that the paint film

surface was peeling, flaking, blistering or powdering. BAD denotes a

surface which has a bad substrate regardless of the condition of the

22
surface; this category includes all imperfections except hairline cracks,

nail holes and the like. EITHER denotes surfaces that are either PEELING

or BAD or both, while BOTH indicates surfaces that are both PEELING and

BAD.

The above six variables are useful in specifying important characteristics of the dwelling unit. In conjunction with these variables, two

issues arise in choosing an aggregated measure to quantify the amount

of lead detected. First, it is important to specify the particular

aggregate of surfaces that is under consideration. For example, one

may wish to consider the collection of all surfaces in a dwelling unit ,

all surfaces in a room , or all surfaces of a specified surface type

(e.g., all walls within the unit). Second, once the collection of surfaces

(the level of aggregation) has been specified, it is then necessary to

decide which particular aggregated measure is to be used. For example,

it is possible to calculate either the mean, median or highest XRF

reading for the specified collection of surfaces. In the analyses that

follow, the influence of the six housing-related variables will be assessed

using appropriate aggregated measures defined on various collections of

surfaces

.

4.2 Characteristics of the Sample

It is important to emphasize that any inferences drawn from the

analyses in this report are based on a particular sample of dwelling

units from the city of Pittsburgh (census tracts 0101 through 3204)

together with the Mt. Oliver area (census tracts 4811 through 4813).

It is important, then, to indicate how closely the actual sample

23
of dwelling units obtained conforms to the underlying population of

all dwelling units in the Pittsburgh/Mt . Oliver area. In particular,

we will consider the closeness of representation of the collection of

inspected dwelling units , relative to the entire sampled area. In this

connection, an "inspected dwelling unit" is considered to be one in

which at least one XRF reading was obtained. Excluded, therefore, are

those dwelling units which did not exist (e.g., because of an error

in the city directory or demolition of the unit) , or units to which entry

could not be obtained for inspection purposes.

There are several reasons why the 3342 inspected dwelling units

may not be totally representative of the Pittsburgh (and Mt. Oliver)

area. First, any random sample is subject to chance fluctuations (or

"random errors") that are completely beyond the control of the investigator. Second, the fact that certain dwelling units could not be

inspected is a potential source of statistical bias, if the selected

(but uninspected) units differ markedly from selected (and inspected)

units. Third, there may be actual methodological biases present in

the selection of units for inspection.

An indication of how well the actual sample reflects the underlying population of dwelling units can be obtained by considering the

relative occurrences of census tracts in the sample. In particular,

the observed frequencies for census tracts in the sample can be compared

with appropriate figures* obtained in the 1970 Census of Population and

Housing [20]. Since the present study comprises some 190 individual

*These figures derive from Table H-l (all housing units) in [20],

24
census tracts, it is useful to define a smaller number of census tract

groups . Group 1 consists of all census tracts with leading two digits

01 or 02, group 2 consists of all census tracts with leading two digits

03 or 04, and so forth. In this way, 16 census groups are formed for

the city of Pittsburgh, and a seventeenth group is defined for the

Mt. Oliver area. Figure 4 presents a comparison of (1) the observed

relative frequencies for census tract groups in the Pittsburgh study,

and (2) the relative frequencies expected on the basis of the 1970

Census Bureau data (100% sample) . With the exception of census tract

groups 1, 4 and 11, the two "profiles" appear in close agreement; in

all three exceptional cases, the observed relative frequencies underestimate the 1970 census values. In light of the above-mentioned potential

sources of error inherent in the sampling process, the inspected units

appear to be generally representative of the underlying population.

Moreover, it should also be noted that 1970 census information (which

itself may be affected by various sources of error in collection)

,

is here being compared with a sample obtained in 1974-1975; that is,

the underlying housing stock may have undergone change (by census tract)

since 1970. When all these possible sources of error have been considered,

the general agreement between the two profiles in Figure 4 provides

confirmation of the survey's validity.

In addition, Table 1 permits a comparison between the sampled

dwelling units and the underlying housing population according to the

age of the structure. In this case, the percentages indicated for the

1970 census are estimates obtained from a 20% (and not a 100%) sample

and are thus themselves subject to random variation. When this addi25
Fipure 4

Percent

of

Sample

by

Census

Tract

Croup

CENSUS

TRACT

GROUP
TABLE 1

Percentage of Dwelling Units by Age Category

AGE CATEGORY NBS/HUD 1970 CENSUS

SURVEY INFORMATION*

Pre 1940 76.6 74.5

1940-1959 17.3 18.3

1960-1975 6.0 7.2

* Based on Table H-2 (20% Sample) , 1970 Census of Population and

Housing

27
tional source of variation is added to the previously mentioned sources,

the closeness of the percentages for the various age categories also

tends to confirm the survey's validity.

4 . 3 Housing Survey Results

The lead levels measured on specified aggregates of surfaces can

be characterized by a single quantity (such as the mean or median level)

or by several such quantities. However, before computing and interpreting

these statistical quantities, it is first useful to study the statistical

distributions associated with the lead levels. Indeed, the actual shape

of the underlying distributions will be important in deciding on the

appropriateness of certain characterizing quantities (e.g., mean,

median) and the validity of certain standard statistical tests. For

such reasons, and in order to understand better the observed variation

of lead levels, a preliminary study has been made of the statistical

distributions of XRF readings. This information can be expressed by

means of a frequency distribution (or histogram) , such as that illustrated

in Figure 5. For the purposes of this histogram, each dwelling unit

in the pre 1940 age category has been characterized by the mean XRF

reading taken from all measured interior trim in the dwelling unit.

The proportion of mean readings falling within each of the specified

lead level intervals has then been plotted on the vertical axis, yielding

the histogram displayed in Figure 5. Histograms have also been graphed

according to various dwelling unit age categories, surface types and

aggregate measures (mean, high reading), and in general they follow

shapes similar to that shown in Figure 5. That is, the distributions

28
Histogram

for

Mean

Trim

Reading/DU

in

Pre

1940

Units

OCN

CN

I

IVlOl dO %

CN

29

LEAD

LEVEL

(mg/cm
of lead levels are highly asymmetric, typically having a long tail

extending to the right. In virtually all cases considered, statistical

tests indicated definite non-normality for the lead level distributions;

thus, the bell-shaped normal distribution [21] does not appear to be

appropriate for describing the observed lead levels*. On the other

hand, both the lognormal and extreme value [21] distributions provide

a reasonable fit to such data.

Because of the calibration characteristics of the XRF instruments

used, it is possible to obtain negative XRF readings on a particular

surface; this possibility does in fact occur in Figure 5, since the

left-hand tail of the histogram extends to negative readings. One way

to remedy such a situation (inasmuch as true lead contents can never be

negative) is to set all negative mean readings in Figure 5 equal to

zero. If this procedure is followed, then the non-normality becomes

even more pronounced in the resulting frequency distributions.

In conclusion, then, it is not appropriate to use only summary

statistics (such as the mean) that are based on normality in analyzing

the present data. For this reason, several summary statistics — such

as the median and highest XRF reading in addition to the mean — will

be used throughout in presenting various analyses. Indeed, while the

sample mean is a good estimator for moderate-tailed distributions (as

the normal) , it is a poor one (compared to the sample median) for longtailed distributions [23]. It is more judicious, therefore, to base

*In fact, the distribution of individual readings must be highly nonnormal, since the Central Limit Theorem [22] guarantees that mean

readings conform more closely to normality than individual readings.

Since the mean readings (as in Figure 5) depart considerably from

normality, so must the individual readings.

30
any conclusions from this data set on analyses of several summary

statistics.

Another way of exhibiting these statistical distributions is in

the form of a cumulative distribution. For example, the histogram of

Figure 5 has been redrawn as the cumulative distribution of Figure 6

(with negative mean readings being treated as zero) . In the latter

figure, the proportion of observations exceeding a given abscissa

value (lead level) is plotted as the corresponding ordinate value;

for example. Figure 6 shows that approximately 77% of the observations

(mean trim readings) exceed 1.0 mg/cm^, while some 10% of the observations

exceed 7.5 mg/cm in pre 1940 dwelling units. Additional cumulative

distributions of this type are presented in Figures 7A and 7B.

Figure 7A indicates that if the highest XRF reading in pre 1940 dwelling

units is considered, about 62% of the dwellings have one or more interior

r\ walls with a lead level exceeding 2.0 mg/cm . If, instead, the highest

XRF reading in a room is considered, then about 21% of the rooms have

2 at least one wall exceeding 2.0 mg/cm , while about 13% of the interior

2 walls (surfaces) have at least one reading in excess of 2.0 mg/cm .

\ This same type of relationship is demonstrated in Figure 7B for the

highest interior wall reading in 1940-1959 dwelling units. Similarly

shaped cumulative distributions result when considering either the mean

or the median lead measurement instead of the highest lead measurement.

These graphs clearly show the pronounced effect of the degree of aggregation upon the percent of readings exceeding some fixed level. Moreover, because the cumulative distribution for individual surfaces

follows the cumulative distribution for rooms much more closely than

31
Cumulative

Distribution

for

Mean

Trim

Reading/DU

in

Pre

1940

Units

OOOOOOOOOOO O0*C0rs«0 l0'^C0CN —

IVlOl JO %

32

LEAD

LEVEL

(mg/cm2)
Figure

7A

Distributions

for

Highest

Wall

Reading

in

Pre

1940

Units

u>

o

o

•ok

o

«>

o

't

o

cs

o

1V101 JO %

33

LEAD

LEVEL

(mg/cml
Figure

7B

Cumulative

Distributions

for

Highest

Wall

Reading

in

1940-1959

Units

LEAD

LEVEL

(mg/cm2)
the cumulative distribution for rooms follows that for dwelling units,

it is reasonable to conclude that there is much less variation of surface

readings within a room than among rooms in a dwelling unit. This conclusion is in fact borne out by further analyses of the data (not

presented here)

.

One of the general housing characteristics whose effect is to be

studied concerns the occupancy class of the dwelling unit, as defined

by occupancy status (owner-renter), the number of units per building,

and the extent of governmental assistance (public-private). Table 2

presents information on the percentage of various surfaces whose measured

lead levels exceed certain fixed levels, according to nine occupancy

class categories; such categories are consistent with classifications

used in Census Bureau housing publications. In essence, this table

provides an alternative representation for cumulative lead level distributions. By comparing the various columns of Table 2, it is seen that

(regardless of surface type) single-family housing and multifamily housing

are quite similar in terms of observed lead levels. On the other hand,

public housing exhibits noticeably lower lead levels than either singlefamily or multifamily housing. For single-family housing, there is no

substantial difference in lead levels between owner-occupied and renteroccupied housing, while for multifamily housing those buildings with

2-4 units show higher lead levels than buildings with 5 or more units.

Another important general housing characteristic is the age of

housing, defined previously in terms of three age categories. Figures

8A-8C show cumulative lead level distributions for certain surfaces,

according to these age categories. In particular, Figure 8A displays

35
TABLE 2 Percentage of Interior Surfaces Exceeding Fixed Lead Levels

Interior

Surface

SINGLE MULTI PUBLIC

Leve^

(mg/cm ) Owner Renter All 2-4 > 4 All 2-4 > 4 All*

Walls 0.5 37.7 38.2 38.2 41.4 35.2 38.1 33.3 33.8 33.5

1.0 20.1 20.7 20. 7 25.4 16.8 20.9 11.3 15.2 15.8

2.0 10.8 11.4 11.3 15.8 7.7 11.5 5.9 6.0 7.0 | 5.0 5.9 6.3 6.3 8.7 4.2 6.4 5.4 2.6 2.9

7.5 4.2 4.4 4.4 6.3 2.9 4.5 5.4 0.9 1.4

Windows 0.5 67.7 69.5 69.4 73.4 59.9 68.0 57.6 55.5

] 58.5

1.0 50.3 52.7 52.5 60.8 40.5 52.6 33.3 27.4 35.3

2.0 34.8 37.0 36.8 45.8 24.3 37.1 30.3 7.7 15.8 1

5.0 20.3 21.9 21.7 29.3 14.0 23.1 30.3 3.9 9.1

7.5 12.4 13.5 13.4 19.2 9.5 15.3 30. 3 3.4 6.3 1

1 Doors 0.5 73.4 74.6 74.5 78.8 66.5 72.9 82.5 64.6 69.8

1.0 53.3 55.2 55.0 65.1 40.1 53.2 56.1 36.1 43.9

2.0 33.0 34.9 34.8 47.7 17.4 33.2 31.6 9.8 16.0

j 5.0 21.6 22.8 22.7 35.5 9.7 23.2 22.8 2.1 7.0 ; 7.5 13.4 14.2 14.2 23.1 5.8 14.8 14.0 1.3 4.2

1

j *Note that this ALL category includes single family as well as multifamily units.
Cumulative

Distributions

for

Dry

Room

Walls,

by

Age

Category

lVlOi JO %

37

LEAD

LEVEL

(mg/cm2
Cumulative

Distributions

for

Wet

Room

Walls,

by

Age

Category

O

o

«oK

O

»o

o

o

CO

o

CN

to

O

to

IVlOl JO %

38

LEAD

LEVEL

(mg/cm^
Cumulative

Distribution

for

All

Doors,

by

Age

Category

IVlOl dO %

39

LEAD

LEVEL

(mg/cm2)
cumulative distributions for walls occurring in dry rooms, grouped

by the age categories: pre 1940, 1940-1959, 1960-1975. This figure

shows that pre 1940 units contain higher lead levels than 1940-1959

units, which in turn contain higher lead levels than 1960-1975 units.

This general observation of greater lead levels in older housing is also

borne out in Figure 8B (wet room walls) and Figure 8C (all doors).

The relationship of housing age to lead levels can likewise be

studied using aggregate measures such as the mean, median and highest

lead levels present in rooms of dwelling units. Table 3 gives the average

value for each of these measures over various subpopulations defined

by age category, occupancy class, room type and surface type. For every

combination of occupancy class, room type and surface type, and for each

of the three measures considered in Table 3, the measured lead levels

of pre 1940 dwelling units is the greatest, that of 1960-1975 units is

the least, and that of 1940-1959 units is intermediate between these two.

Typically, the pre 1940 units have lead levels which are three times those

of the 1940-1959 units and five times those of the 1960-1975 units. It

is also observed (see Table 4) that the pre 1940 public housing units

have substantially lower lead levels than the general pre 1940 housing

population.

In addition, Table 3 shows (as seen earlier) that single-family

and multifamily housing are generally similar in terms of measured

lead levels. However, in pre 1940 units the multifamily housing tends

to have somewhat higher lead levels than single-family housing, while

in 1960-1975 units single-family housing tends to have somewhat higher

lead levels than multifamily housing. It is also clear from Table 3

40
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unknown.
TABLE 4

Percentage of Interior Surfaces in Pre 1940 Units

Exceeding Fixed Lead Levels

DRY WET

Occupancy

Leve^

(mg/cm ) Walls Windows Doors Walls Windows Doors

Single 0.5 34.5 7.15 75.4 52.6 77.4 80.9

1.0 16.6 54.9 57.2 36.1 61.6 65.5

2.0 7.8 39.1 40.1 24.1 44.5 45.9

5.0 4.6 23.7 26.9 13.1 25.2 29.8

7.5 3.2 14.7 16.5 9.2 15.5 19.1

1 Multi 0.5 35.9 70.6 74.5 53.1 77.1 80.5

1.0 17.7 49.9 44.1 37.3 63.2 65.7

2.0 8.8 41.3 40.5 26.2 46.6 48.5

5.0 4.5 26.2 30.8 15.7 29.1 33.4

7.5 3.0 17.0 19.6 12.0 20.0 22.1

Public 0.5 33.4 64.0 70.1 43.7 68.4

I 68.3

1.0 15.7 43.9 43.4 24.6 41.0 41.3

2.0 8.2 23.0 21.2 12.3 18.8 19.8

5.0 3.4 13.8 12.8 6.1 8.5 10.3

7.5 1.7 7.9 8.0 3.6 7.7 7.1

I

All 0.5 34.8 71.4 75.3 52.7 77.3 80.8

1.0 16.9 55.2 57.3 36.3 61.9 65.5

2.0 8.0 39.6 40.4 24.6 44.9 46.4

j 5.0 4.6 24.2 27.8 13.7 26.0 30.6

7.5 3.2 15.1 17.2 9.8 16.4 19.8

42
that lead levels in wet rooms are consistently higher than lead levels

in dry rooms, especially for the wall readings. This difference between

wet rooms and dry rooms can alternatively be seen in the cumulative

distributions graphed in Figures 9A-9F for various age categories and

surface types.

The cumulative distributions of Figures 9A-9F also indicate that

(within any age category) surface type is important in explaining variation

in lead levels. This effect can also be clearly seen in Table 2, where

the windows and doors appear distinctly different from walls in terms

of the percentage of surfaces exceeding certain fixed lead levels.

This observed difference between windows (doors) and walls holds across

all occupancy classes for all fixed lead levels. In Table 3, a marked

difference between walls and trim (doors, windows, baseboards, radiators,

cabinets and fireplaces) is likewise evident: trim surfaces exhibit substantially higher lead levels than do walls, for all indicated combinations

of occupancy class, room type and age category. In addition, Table 3

indicates that within each age category, dry room walls have the lowest

lead levels of any surface type, followed by wet room walls, dry room

trim, and wet room trim. These differences by surface and room type

are much more pronounced in pre 1940 housing than in the newer units.

Alternatively, the variation in lead levels by surface type can

also be calculated using rooms of the dwelling unit. For example.

Figure 10A shows in pre 1940 dry rooms the mean trim lead level for all

rooms having a mean wall lead level lying within specified intervals.

Thus, although some 70.7% of the rooms have a mean wall lead level lying

between 0.0 and 0.5 mg/cm , the trim surfaces within the same rooms

43
Cumulative

Distributions

for

Walls

in

Pre

1940

Units,

by

Room

1VJLOJL dO %

44

ii

LEAD

LEVEL

(mg/cm2
Cumulative

Distribution

for

Doors

in

pre

1940

Units,

by

Room

T

o

o

±

o

o

IVlOl JO %

45

LEAD

LEVEL

(mg/cm2)
Cumulative

Distributions

for

Walls

in

1940-1950

Units,

by

Room

IViOi JO %

46

LEAD

LEVEL

(mg/cm2)
o

d

*oK

O

u->

O

NT

O

O

iqCNO

<N

<q

O

<qO

LEAD

LEVEL

(mg/cm2)
Cumulative

Distributions

for

Walls

in

1960-1975

Units,

by

Room

O

IVlOi JO %

4R

LEAD

LEVEL

(mg/cm2)
Cumulative

Distributions

for

Doors

In

1960-1975

Units,

by

Room

lVlOl do %

49

LEAD

LEVEL

(mg/cm2)
Mean

Trim

vs.

Lead

Interval

for

Walls

in

Dry

Rooms,

Pre

1940

Units

O

I

o

o

6? tS7 o &

toO

CO

CN o CO

O' z<• Z —

J

1 IS <

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CtL

ko

vO«»£

£ £

$ E

1801) %ll

(9Pl) %n

b*l

%s>

fesrO %9>l

1

1680/4

. %

^ 1 1

CN

o

oo o

K

O

-O O

>o Oro OCN

( z uo/6uj) wiUl NV3W

50

LEAD

INTERVAL

-

MEAN

WALLS

(mg/cm
2 have a mean of 3.0 mg/cm . Note that the number of rooms having a mean

lead level within the specified interval is shown in parentheses immediately beneath the percentage of rooms within the interval. This figure

2

indicates that at mean wall lead levels less than 5.0 mg/cm (including

95.2% of all rooms), the mean trim lead levels can be substantially

greater than the mean wall levels. A similar relationship is observed

in Figure 10B, which pertains to pre 1940 wet rooms.

Another factor which has been considered in analyzing the present

data on lead levels is the condition of the surface. Recall that a

PEELING surface indicates one on which the paint film is peeling,

flaking, blistering or powdering. A BAD surface is one whose substrate

contains imperfections (apart from hairline cracks, nail holes, etc.).

Since a condition code was assigned to a room (and not to individual

surfaces within a room) , it is appropriate to assess the effect of condition on lead levels using aggregate measures for rooms. In particular,

Table 5 displays the percentage of rooms whose highest lead level

exceeds certain fixed lead levels, classified by whether the surface

condition is PEELING or BAD or both (P/B) , or whether it is neither

PEELING nor BAD (i.e., GOOD). Thus, 62.9% of all pre 1940 dry rooms

1 with walls in GOOD condition have their highest wall reading in the room

i 2 exceeding 0.5 mg/cm . For virtually all combinations of surface type,

room type and age category, rooms with a PEELING/BAD condition code

| show greater lead levels than rooms with a GOOD condition code.

Furthermore, Table 6 indicates that for each of the indicated surface

types about 25% of all dwelling units can be classified as having at

least one room in PEELING or BAD condition (P/B) . Approximately

51

;
Figure

10B

Mean

Trim

vs.

Lead

Interval

for

Walls

in

Wet

Rooms,

Pre

1940

Units

(^uid/6uj) wiai NV3W

I

LEAD

INTERVAL

-

MEAN

WALLS

(mg/cm
TABLE 5

Percentage of Rooms with Highest Reading

Exceeding Fixed Lead Levels

Age

WALLS WINDOWS

DRY WET DRY WET

Leve^

(mg/cm ) P/B* Good P/B Good P/B Good P/B Good

Pre 1940 0.5 68.2 62.9 86.2 77.7 83.9 68.8 85.7 75.0

1.0 38.8 31.8 67.3 54.1 70.4 52.0 74.2 59.2

2.0 19.6 12.0 46.8 34.9 55.7 36.0 57.2 42.4

5.0 12.0 6.7 33.0 19.3 36.6 21.6 35.3 24.4

7.5 8.3 4.6 25.1 14.0 22.4 13.6 24.9 15.1

1940-1959 0.5 46.9 56.6 79.5 66.4 66.2 43.6 62.5 44.4

1.0 21.9 23.5 46.2 36.4 41.2 22.3 46.9 25.7

2.0 15.6 4.8 33.3 14.9 22.1 9.0 28.1 11.4

5.0 9.4 2.0 23.1 7.6 11.8 3.7 25.0 5.9

7.5 6.3 1.2 12.8 5.5 5.9 2.1 15.6 4.0

1960-1975 0.5 57.1 48.8 60.0 53.8 36.4 37.3 75.0 40.9

1.0 14.3 15.8 40.0 22.7 27.3 17.7 75.0 22.7

2.0 0.0 2.0 40.0 5.6 18.2 4.4 75.0 10.9

5.0 0.0 0.3 20.0 1.0 0.0 1.6 50.0 4.5

7.5 0.0 0.0 0.0 0.8 0.0 0.4 0.0 1.8

*P/B = PEELING or BAD or BOTH

j

53
TABLE 6

Percentage of DU's (Rooms) Having Surfaces

in Peeling or Bad Condition

WALLS

DU * ROOMS

WINDOWS

DU ROOMS

DOORS

DU ROOMS

Pre 1940 32.2 13.8 29.2 15.3 27.4 14.8

1940 - 1959 10.0 3.1 12.8 6.5 9.4 4.2 i

1960 - 1975 2.5 1.1 8.1 4.0 6.1 2.7 i

All 26.5 11.2 26.3 13.9 23.0 12.3

*The abbreviation "DU" is used here and subsequently to indicate

"dwelling unit".

54
12-13% of the rooms in all dwelling units have surfaces considered in

PEELING or BAD condition. As this table also shows, these percentages

are highest for pre 1940 units, intermediate for 1940-1959 units and

lowest for 1960-1975 units.

In all the analyses presented so far, attention has focused on the

interior surfaces of the dwelling unit. Lead level readings were also

taken at specified locations on the exterior of the unit, and these

data are now presented. Tables 7A-7B permit a comparison of lead levels

detected on exterior surfaces with those found on interior surfaces.

In these tables, each dwelling unit has been characterized by a mean

(or high) reading for all surfaces and classified according to age

category, surface type, room type and location (interior /exterior )

.

As Tables 7A and 7B indicate, exterior surfaces show considerably higher

lead levels than interior surfaces, regardless of age category, surface

type or room type. Moreover, this difference between exterior and

interior lead levels is greater for walls than for trim. In addition,

lead levels found on exterior surfaces are seen to vary according to

the age of housing, with the pre 1940 units displaying greater levels

(by surface type) than 1940-1959 units, which in turn show greater

levels than 1960-1975 units.

Figures 11A-11D compare some of the cumulative distributions from

the present Pittsburgh study with those obtained from the Washington, D.C.

pre-test [7], Since the Washington data (also based on a simple random

sample) represent only about 100 dwelling units, it is not clear how

well such data characterize the housing population of that city.

However, in most instances the distributions for Pittsburgh and Washington

55
TABLE 7

A

Average Value for DU Mean Reading (mg /cm )

AGE SURFACE DRY

INTERIOR

WET ALL

EXTERIOR

ALL

Pre 1940

Walls .89 2.46 1.33 10.22

Trim 3.55 3.77 3.58 6.07

All 1.97 3.05 2.26 6.45

1940 - 1959

Walls .38 .77 .49 4.75

Trim 1.14 1.36 1.22 2.51

All .57 .96 .68 2.54

1960 - 1975

Walls .21 .27 .21 1.37

Trim .76 .89 .79 2.14

All .31 .47 .34 2.11

All

Walls .75 2.03 1.11 9.72

Trim 3.01 3.24 3.04 5.33

All 1.62 2.54 1.87 5.63

56
TABLE 7B

Average Value for DU High Reading (mg/ cm )

AGE SURFACE DRY

INTERIOR

WET ALL

EXTERIOR

ALL

Pre 1940

Walls 3.22 4.90 5.67 11.04

Trim 8.35 7.29 9.96 11.32

All 8.80 8.32 11.11 12.65

1940. - 1959

Walls 1.46 1.75 2.09 5.41

Trim 2.48 2.51 3.13 3.85

All 2.61 2.69 3.43 4.12

1960 - 1975

Walls .83 .78 1.04 1.37

Trim 1.46 1.63 1.85 2.79

All 1.46 1.57 1.88 2.81

All

Walls 2.76 4.09 4.76 10.50

Trim 7.03 6.24 8.40 9.74

All 7.26 6.96 9.21 10.86

57
Figure

11A

Cumulative

Distributions

(Pittsburgh

and

Washington)

for.

Interior

Walls

in

Pre

1940

Units

Oo

»os!o

»opW0

CO

<o010

01

*oO

>qO

IViOl JO %

58

LEAD

LEVEL

(mg/cm2)
Cumulative

Distributions

(Pittsburgh

and

Washington)

for

Interior

Walls

in

1940

-

195 *

Units

IViOl do %

59

LEAD

LEVEL

(mg/cm?
Cumulative

Distributions

(Pittsburgh

and

Washington)

for

Interior

Doors

in

Pre

1940

Units

WJLOi dO %

60

LEAD

LEVEL

(mg/cm2)
Cumulative

Distributions

(Pittsburgh

and

Washington)

Cor

Interior

Doors

In

1940-1959

Units

IVIOi dO %

61

LEAD

LEVEL

(mg/cm^)
follow quite similar shapes. Figures 11A-11B suggest that there is

very little difference in the wall lead levels for the two cities;

the most pronounced difference occurs for doors in pre 1940 units, as

shown in Figure 11C.

4.4 Summary of Results

This section has presented various analyses of the Pittsburgh

study data, performed in order to understand better the relation of

certain housing characteristics to measured lead levels in the dwelling

unit. Further analyses, in addition to those already described here,

have also been conducted using data from the Pittsburgh study. A table

of contents to all these analyses — those presented here and in a

companion report [8], and those which have not been reported — can

be found in Appendix C.

The major conclusions to be drawn from the analyses given here are

now briefly summarized:

1. OCCUPANCY CLASS - No substantial differences in lead levels

are observed among the various occupancy classes, except that public

housing tends to show lower lead levels.

2. AGE - Measurable lead levels (e.g., in excess of 2.0 mg/cm )

are present in all dwelling unit age categories, and even in a significant

number of newer units. However, lead levels show a pronounced

variation by the age of the unit, with the highest lead levels observed

in older dwelling units.

3. ROOM TYPE - Wet rooms exhibit considerably greater lead levels

than do dry rooms.

62
I

I!

4. SURFACE TYPE - Lead levels found on trim (e.g., doors, windows

and baseboards) are markedly greater than those found on walls.

5. CONDITION - Lead levels detected in rooms having a bad substrate

or a peeling paint film are somewhat greater than those levels detected

in rooms having a good substrate and a tightly adhered paint film.

6. LOCATION - Lead levels for exterior surfaces are considerably

greater than those found on interior surfaces of a dwelling unit;

these exterior lead levels vary consistently by the age category of the

unit

.

7. COMPARISON WITH WASHINGTON - The levels of lead found on walls

are quite similar for both Pittsburgh and Washington, D.C.

In addition, the analyses conducted here have been based on consideration of several summary statistics, rather than on any one single

statistical measure. This practice appears warranted for the present

data set, inasmuch as pronounced departures from normality are observed

in the statistical distributions of lead levels.

63
5. REFERENCES

[1] Gilsinn, J., "Estimates of the Nature and Extent of Lead Paint

Poisoning in the United States," Technical Note 746, National

Bureau of Standards, December 1972.

[2] Laurer, G.R. , et al., "The Distribution of Lead Paint in New York

City Tenement Buildings," American Journal of Public Health,

Vol. 63, No. 2, pp. 163-168, 1973.

[3] Jamison, C.S., "Lead Paint Danger to Pre-Schoolers in Houston,

Texas," thesis (Master of Public Health), University of Texas,

School of Public Health at Houston, June 1971.

[4] McAllister, J.J. and H.H. Tilson, "Multnomah County Oregon Lead

Poisoning Project Report," June 1974.

[5] "Childhood Lead Poisoning Control Project for New Mexico," Two

Year Summary Report, New Mexico Environmental Improvement Agency,

Santa Fe, New Mexico, 1976.

[6] "Childhood Lead Poisoning: A Summary Report of a Survey for Undue

Lead Absorption and Lead-Based Paint Hazard in 27 Cities," DHEW

Publication No. (HSM) 73-10002, September 1972.

[7] Hall, W. , Ayers, T. and D. Doxey, "Survey Plans and Data Collection

and Analysis Methodologies: Results of a Pre-Survey for the

Magnitude and Extent of the Lead Based Paint Hazard in Housing,"

NBSIR 74-426, National Bureau of Standards, January 1974.

[8] Urban, W. , "Statistical Analysis of Blood Lead Levels of Children

Surveyed in Pittsburgh, Pennsylvania: Analytical Methodology and

Summary Results," NBSIR 76-1024, National Bureau of Standards,

April 1976.

[9] Hall, W. and L. Slovic, "Survey Manual for Estimating the Incidence

of Lead Paint in Housing," Technical Note 921, National Bureau of

Standards, September 1976.

[10] "Polk Directory for Pittsburgh, Pennsylvania," R.L. Polk and

Company, 1974.

[11] "Lead-Based Paint Poisoning," Hearing before the Subcommittee on Health of the Committee on Labor and Public Welfare, United States

Senate, 91st Congress, Second Session, November 23, 1970.

[12] New York State Sanitary Code, Part 67 (Lead Poisoning Control),

Section 67.3-(b), added 1970.

[13] Godette, M. , Post, M. and R. Higgons, "Preparation of Standard

Lead Bearing Samples," Report 10631, National Bureau of Standards,

November 1971.

64
[14] Clark, E. , Waksman, D. and D. Hattis, "Identification of Potential

Building Material Sources of Lead Poisoning," Report 10632,

National Bureau of Standards, November 1971.

[15] Rasberry, S., "Investigation of Portable X-ray Fluorescence

Analyzers for Determining Lead on Painted Surfaces," Applied

Spectroscopy, Vol. 27, No. 2, pp. 102-108, 1973.

[16] Spurgeon, J. , "Response Characteristics of a Portable X-ray

Fluorescence Lead Detector: Detection of Lead in Paint,"

NBSIR 73-231, National Bureau of Standards, June 1973.

[17] Kaplan, E.H., et al. , "Portable X-ray Fluorescence Instruments

for the Analysis of Lead in Paints," Public Health Reports,

Vol. 90, pp. 223-230, May-June 1975.

[18] Massachusetts Lead Poisoning Regulations, Department of Public

Health, Sections 4.05 and 5.1, 1975.

[19] New Jersey State Sanitary Code, Chapter 13 (Lead Poisoning),

Section 2.3, July 1972.

[20] Census of Population and Housing: 1970, Census Tracts, Final

Report PHC(1)-162, Pittsburgh, Pa. SMSA, U.S. Bureau of the Census,

May 1972.

[21] Johnson, N.L. and S. Kotz, Continuous Univariate Distributions,

Vols. 1 and 2, Houghton Mifflin Co., Boston, 1970.

[22] Feller, W. , An Introduction to Probability Theory and Its

Applications, Vol. I, John Wiley and Sons, New York, 1968.

[23] Filliben, J. J. , "Techniques for Tail Length Analysis," Proceedings

of the Eighteenth Conference on the Design of Experiments in

Army Research Development and Testing, Part 2, ARO Report 73-2,

pp. 425-450, 1973.
APPENDIX A

INSTRUCTIONS FOR COMPLETING THE HOUSING SURVEY FOEM

The Data Collection Form (NBS-744) , hereafter called the DCF, is

the sole reporting instrument for the housing portion of the survey.

Hence there are several different types of data appearing on the DCF.

Some of the data elements will have been entered prior to the inspector’s

receipt of the DCF; others will be transcribed from the XRF log book;

the remainder will be collected on-site for the individual dwelling

unit.

In the description of the data elements, the term "field" is used

to denote a sequence of characters or digits which are treated as an

entity. The designation "DU" is used as an abbreviation for "dwelling

unit.

The DCF consists of 19 lines, each pre-numbered in the field CODE.

The field SERIAL NUMBER forms the unique identification for the DCF.

Generally, if the entity defined by a line of the DCF does not exist

(a one story DU, for example, would have no stairway), that line is

left completely blank when the data are collected. The position of

the relevant (or non-blank) characters within a field is immaterial;

e.g., AA1 is considered identical to A1A or 1AA, but the characters

must be successive (a field such as 1A2 is meaningless whereas A12

and 12A are meaningful and equivalent)*. Decimal points are ignored in

entering XRF readings; a decimal point is automatically generated during

*Here, "A" is used to indicate a blank character in a field.

66
subsequent processing. No particular convention must be observed to

avoid ambiguity of l's and I's or 0's and o’s.

The right hand side (RHS) of the DCF contains a comprehensive list

of the codes required in the body of the form.

When the inspection is completed, lines 1, 2, 3, and one or more

of the lines from 4 to 19 will have been filled out. If the DU did not

exist (resulting from an error in the city directory) , only line 1 will

be filled out. If the DU exists but could not be inspected, lines 1 and

3 will be filled out.

Section I - IDENTIFICATION

Line 01 - This line is not the responsibility of the inspector. All the

fields here except "V" will be filled out before the inspector

receives the form. The field "V" will be filled out, if necessary, by the supervisor after the form is returned.

SERIAL NUMBER - The arbitrarily assigned unique identifying number for

the dwelling unit. It must be numeric.

TRACT - The census tract in which the DU lies.

BLOCK - The census block in which the DU lies. (This field was not used

in the Pittsburgh housing survey.)

ZIP CODE - The postal ZIP CODE of the DU mailing address.

V - The visitation code which is entered after the DCF is returned. If

an inspection has been made, this field is left blank; otherwise this field describes the reason the inspection could not

be made. The codes used are listed in I - Visitation on the

RHS. The text accompanying the codes is self-explanatory;

note, however, that codes 3 and 6 are different.

67
STREET NAME and NUMBER - Self-explanatory. This field is used only by

the inspector for locating the DU. This information has been

dropped in the subsequent construction of the data base, in

keeping with privacy requirements.

Line 02 - These data are collected daily and copied onto the DCF from

the XRF log book. This information relates to the day of

inspection rather than the specific DU.

XRF SERIAL - The three-character numeric serial number of the particular

XRF instrument used.

TEST BLOCK - The XRF reading obtained from the painted panel (medium lead

content) test block included with each instrument. This

reading is taken after the instrument has been calibrated.

ZERO READING - The reading obtained from the non-leaded wood block

included with each instrument. This reading is taken during

calibration of the instrument.

ZERO VERNIER - The zero vernier (dial) setting corresponding to the zero

reading.

CALIBRATE READING - The reading obtained from the lead-foil-on-wood

block included with the instrument. This reading is taken

during calibration of the instrument.

CALIBRATE VERNIER - The vernier setting corresponding to the calibrate

reading.

PEAK READING - The reading obtained from the lead-foil-on-wood block

included with each instrument. This reading is taken during

calibration of the instrument.

PEAK VERNIER - The vernier setting corresponding to the peak reading.

68
INSPECTORS - The initials of both members of the inspecting team.

DATE/MONTH - Conventional numeric code (1-12) for month of year.

DATE/DAY - Conventional numeric code (1-31) for day of month.

Line 03 - This line is completed on-site. The fields YEAR through

CHILD require the active participation of the householder.

SEQ - Indicates the sequence in which the DU was inspected that day

(first, second, third, etc.). Do not include DU's which were

visited but not inspected.

TEST BLOCK- The average of five on-site XRF readings taken on the

(medium lead) painted panel test block included with the

instrument.

TYPE - Coded according to II—Type of Construction—on the RHS. If

the type is mixed, enter the code for the predominant type.

XS - The material of the exterior according to III—Outside Surface of

Building—on the RHS. If the surface is mixed, enter the predominant type code.

OC - Coded according to IV—Occupancy—on the RHS. For multi-unit

buildings a mailbox count is a convenient way of ascertaining

the number of units.

YEAR - Coded according to V—Year Built—on the RHS. This will be

obtained from the householder if possible; otherwise it is

to be estimated by the inspector.

OWNER - Coded according to VI—Owner/Renter—on the RHS.

MORT - Coded according to VII—Mortgage—on the RHS.

PUBLIC - Coded according to VIII—Public Housing—on the RHS. Public

housing denotes those units which are operated by some agency

69
of government whether federal, state, or local.

SUB - The subsidized housing code from IX’—Subsidized’—on the RHS.

Subsidized housing denotes units for which at least a portion

of the rent is paid by some federal, state, or local government

agency.

CHILD - The number of children, age 6 and under, resident in the DU.

Section II - INTERIOR

This section of the DCF includes lines 4 through 17. Each of

these lines has the same format; the pre-printed CODE field identifies

the room type.

No attempt is to be made to move furniture, pictures, etc. or to

stand on anything in order to obtain readings.

Walls and Ceilings

COND - The material and condition of the walls, ceilings, etc. This

information consists of a three-character field in which one

character is a material code according to XI (a) of the RHS

(V is used to indicate any surface of synthetic or plastic

material such as laminated plastic, etc.); one character is

a base or substrate condition code according to XI (b) of

the RHS and the third character is a surface condition code

according to XI (c) of the RHS. The order in which these

characters appear is immaterial. The code P2Q, for example,

is equivalent to PQ2, 2PQ, or QP2.

These codes are assigned to the room in general, rather than to

each specific surface. If the surfaces are mixed, the code

70
which most nearly characterizes the room at a height of four

feet or less should be entered.

Base condition codes are described using an estimate of the magnitude of work involved if redecoration were considered:

1. If no work is required.

2. If minor work is required (small cracks, but no deep

or large holes)

.

3. If major work is required (large cracks, deep or

large holes, structural defects).

Since COND reflects the general condition of the room, it is best

to complete this field after the room inspection has been

completed

.

WALL 1, WALL 2, WALL 3, WALL 4, and CEILING - Each of these fields

contains an XRF reading taken on the indicated surface. The

walls are numbered clockwise beginning with the wall to the left

of the entry. The wall reading should be taken at any point

less than four feet from the floor if such a point is accessible.

The ceiling reading is to be taken only if it is possible to

do so by standing on the floor or stairs; do not stand on

furniture or counter tops, etc. If the wall is inaccessible

enter an "X" in the field; if the surface does not exist (as

in a three-walled room, for example) leave the reading field

blank. If the ceiling is inaccessible, the CEILING field

may be left blank instead of entering an "X"; subsequent editing

procedures assume that a ceiling exists for each room, and

thus a blank and an "X" are equivalent for this particular

71
field

.

Trim

COND - Similar to the COND field for walls and ceilings, this field

contains a general condition code for all trim within the

room (i.e., windows, doors and baseboards).

WINDOW NUMBER - Enter the number of windows in the room ("0" if none)

.

WINDOW READING - Enter the XRF reading obtained from a window frame

or sill; if possible this reading should be taken from a

vertical surface within four feet of the floor.

DOOR NUMBER - Enter the number of doors in the room ("0" if none)

.

DOOR READING - Enter the XRF reading from any point of a door’s

surface which is within four feet of the floor. If the door

is of variable thickness, take this reading from the thick

part of the door to avoid the problem of detecting lead on

the back surface of the door.

BASEBOARD - Enter the XRF reading from an accessible part of the baseboard from any convenient wall of the room. If the baseboard

is inaccessible enter an "X"; if there is no baseboard leave

this field blank.

Other

FLOOR - Enter an XRF reading only if the floor is a painted one.

RADIATOR, CABINET, FIREPLACE - Enter XRF readings for each of these

which exist; leave the field blank for each non-existent

entity.

Line 17 - COND - is a numeric field containing the number of moves the

72
family has made in the preceding six years.

Section III - EXTERIOR

The exterior section differs from the interior section in that there

is a condition code associated with each XRF reading taken. Criteria for

each condition code are, however, the same as for the interior section.

Readings are to be made only if the designated areas are painted. As

with the interior readings, the XRF readings should be taken from a

point at a height of four feet or less.

WALL - An outside wall which is typical of the predominant exterior

surface of the dwelling unit.

PORCH - The floor of the porch.

DOOR - An exterior door. If the door is of variable thickness, this

reading is taken from the thick portion.

WINDOW - A window frame or sill.

RAILING - The porch or stair railing.

FENCE - The fence.

GARAGE - The garage wall.

EXCLUDED ROOMS - Enter here the number of rooms of the indicated types

which were not inspected.

73
APPENDIX B

DATA BASE SPECIFICATIONS

There are three files currently maintained which can be made available* to interested researchers. The first, and by far the largest of

these, MAST16, contains all housing and child data which were collected.

The second file, BLF014, contains all child data and the housing data

for those units where child data are present. A third file, BLMI14,

contains data for housing units in which there was at least one child

for which no child data were collected.

The files have almost identical specifications; BLF014 and BLM114

are actually subfiles which were extracted from MAST16. All files are

completely "processible" ; that is, all records are of proper length and

format, and all data fields are of the indicated form and have values

within the specified range.

File Format and Structure

The files have no labels and each is terminated by a file mark

preceded by a sentinel record; the sentinel is a record with "999999" in

the first field. The file elements are basically images of the lines

present on the data collection form (DCF) with the serial number from

line 1 replacing the leading blanks from lines 2, 3, 16, 17 and the indicated room names from the other lines. In addition a "pointer" is used

to indicate the successor line type, and an image of the psycho-socioenvironmental (PSE) form is included where available for each child.

*Data tapes for these files can be obtained from the Lead-Based Paint

Program, Housing & Urban Development, Washington, D.C. 20410.

74
These lines are sorted in ascending order* on a two-part key consisting

of the serial number and the line type; the line type indicates the room

type for the housing data. The formatted PSE line for each child is

assigned a line number from 20 - 29: 20 for the first child tested,

21 for the second child tested, up to 27 for the eighth child tested.

These child line numbers were assigned as the data were received and

are not in order by age or sex. The comments by the blood collection

team (a portion of the PSE form without fixed formats) are included as

lines 30 - 39 in free form text.

In each of the files, a sequence of lines having the same serial

number and including all lines present through line 19 defines a dwelling

unit. Line numbers which are 20 or greater indicate that child data

have been included.

Line Formats

The description of the line contents and formats are keyed to the

definitions and formats appearing on the DCF. For each of the files

there are different acceptable combinations of lines.

*Some arithmetic is involved to transform the serial numbers as they exist

in the file into true numeric sort. The serial numbers were assigned such

that the first four digits of the serial number correspond to the last four

digits of the census tract in which the unit is located and the last two

digits were index numbers. More than the 99 units thus allowed for were

inspected in some census tracts. The indices for units 100-199 in these

tracts were formed by adding 5 to the leading position of the serial

number and using the last two digits of the index in the index portion of

the serial number. This causes no ambiguity in identification since the

only permissible characters in the first position of the serial number

are 0-4. To illustrate th/e method for sorting the serial numbers into

order, let each, character of the serial number be denoted by the letters

a through f; then a-b-c-d-e-f is a typical input serial number. If a>4,

set g=a-5 and h=l; otherwise, set g=a and h=0. Then the data can be

placed in ascending order by sorting on the key g-b-c-d-h-e-f

.

75
For MAST16, acceptable sequences, are:

(1) Line 1 only (if the dwelling unit does not exist)

.

(2) Lines 1 and 3 only (if the dwelling unit exists, was observable

but the inspection was not performed)

.

(3) Lines 1, 2, 3 and at least one line from among lines 4-19.

A line for each PSE form submitted is included; these are

numbered sequentially beginning with 20 for the first child.

If at least one line from among 20 - 29 appears, there may be

one or more comment lines beginning at line 30 and terminating

(after a sequence of consecutive line numbers) at any line

through line 39. The totality of these lines represent dwelling

units on which inspections were performed.

For BLF014, the acceptable sequences are the same as for (3) of

MAST16, except that exactly one line from among lines 20 - 29 appears.

In BLF014, there are duplicate dwelling units; the housing data are

duplicated for each child after the first. The criterion for generation

into this subfile is that a file entry was extracted from MAST16 for

each child about whom PSE data were collected.

BLMI14 has the same acceptable sequences as (3) for MAST16. The

criterion for generation into this subfile is that an entry was extracted

from MAST16 for each dwelling in which the number of children represented

by PSE data was less than the number of children indicated on the DCF.

The format of each of the possible line types is identical for

each of the three files. Each field is right-adjusted. The format and

definitions of variables are given below on a line-by-line basis keyed

to the DCF. In what follows, RHS is used to denote the right hand side

76
of the DCF, where definitions for the codes appear.

LINE 1 - Identification Line - FORTRAN Format (16, 12, 16, 3X, 15, II,

216,

Field

Field

Field

Field

Field

!

Field

Field

Field

Field

Field

Field

Field

Field

4A6, 212).

1 - DU serial number (16)

.

2 - Line type number (12), set equal to 1.

3 - Census tract (16); either greater than 30100 and less

than 33299, or greater than 54810 and less than 54814.

4 - Zip code (15); if not reported, this field contains 0.

5 - Visit code (II) as defined in RHS-I. This has the

value 0 if the inspection was performed.

6 - Census tract (16)

.

7 - DU serial number within tract (16)

.

8 - A* A* A* (A6)

.

9 - A* A* A* (A6)

.

10- A* A* A* (A6)

.

11- A* A* A* (A6)

.

12 - Batch number (12) - This field was used as part of

the quality control procedures in the creation and

updating of the file. It is the index of the last

cycle in which the line was changed. If no changes

have been made, it is the index of the cycle in which

the line was inserted into the file. Batch number

appears in every line of each file.

13- Successor index (12) - This is simply the index of the

next line type which appears in the file. For the

last line of the file this index is 99. This field

77
appears in every line of the file.

LINE 2 - XRF Calibration and Identification Line - FORTRAN Format (16,

12, 813, 2A3, 213, 15X, 212).

Field 1 - DU serial number (16).

Field 2 - Line type number (12), set equal to 2.

Field 3 - XRF serial number (13)

.

Field 4 - Test block reading (13) - The XRF reading for the

medium lead test block, taken during the daily calibration process.

Field 5 - Zero reading (13) - The XRF reading from the non-lead

test block, taken during the daily calibration process.

Field 6 - Zero vernier (13) - The setting of the zero vernier

scale after calibration.

Field 7 - Calibration reading (13) - The XRF reading from the

lead block taken during the daily calibration process.

Field 8 - Calibrate vernier (13) - The setting of the calibrate

vernier scale.

Field 9 - Peak reading (13) - The XRF reading for the lead

block taken during the daily calibration process.

Field 10 - Peak vernier (13) - The setting of the peak vernier

scale.

Field 11 - Initials of the first inspector (A3)

.

Field 12 - Initials of the second inspector (A3)

.

Field 13 - Month code (13): i.e., 1 - 12.

Field 14 - Day of month (13): i.e., 1 - 31.

Field 15 - Batch number (12)

.

78
Field 16 - Successor index (12)

.

LINE 3 - Questionnaire Line - FORTRAN FormAt (16, 12, 613, 4A3, 13, 18X,

212 ).

Field 1 - DU serial number (16).

Field 2 - Line type number (12), set equal to 3.

Field 3 - Sequence (13) - The index of this inspection within

the day.

Field 4 - Test block (13) - The XRF reading from the medium lead

test block, taken at the time of inspection.

Field 5 - Type (13) - The type of construction, coded according

to RHS-II. An unknown type is denoted by 4.

Field 6 - Exterior surface (13) - The material of the exterior

surface, coded according to RHS-III. Unknown is

denoted by 8.

Field 7 - Occupancy class (13) - Occupancy class of the unit,

coded according to RHS-IV. Unknown is denoted by 8.

Field 8 - Year built (13) - Year the structure was built,

coded according to RHS-V. Unknown is denoted by 4.

Field 9 - Owner/Renter (A3) - The code for owner/renter category

according to RHS-VI. Unknown is denoted by U.

Field 10 - Mortgage type (A3) - Mortgage type, coded according

to RHS-VII. Unknown is denoted by U.

Field 11 - Public housing (A3) - Coded according to RHS-VIII.

Field 12 - Subsidized (A3) - Always N in this survey.

Field 13 - Children resident (13) - This is a single digit

specifying the number of children aged six or less,

79
except that 9 denotes an unknown number of children.

Field 14 - Batch number (12)

.

Field 15 - Successor index (12).

LINES 4-16 - Room Lines - FORTRAN Format (16, 12, A3, 513, A3, 913, 3X,

212 ).

Each line present denotes a room of the specified type. Only those

rooms for which one or more XRF readings were taken appear in the file.

All numeric fields representing XRF readings are given in tenths of mg/cm ;

a numeric value greater than 990 indicates that no reading was taken.

Field 1 - DU serial number (16).

Field 2 - Line (room) type (12) ; a room type = 16 indicates

an unknown room type.

Field 3 - Wall condition code (A3) - This refers to the representative condition of the walls and ceilings in

the room.

Character 1 - The wall material according to RHS-XI(a).

Character 2 - The wall substrate condition according

to RHS-XI(b).

Character 3 - The wall surface condition according to

RHS-XI(c)

.

Fields 4-8 - XRF readings (513) - XRF readings for each of the

four walls and the ceiling.

Field 9 - Trim condition code (A3) - Exactly as in Field 3

except that it describes the condition of the trim

surfaces within the room.

80
Field 10 - Number of windows (13) - The number of windows within

the room.

Field 11 - Window reading (13) - The XRF reading taken from a

window within the room.

Fields 12 & 13 - Number of doors/door reading (213) - Exactly

as given in Fields 10 and 11, except these fields

refer to the doors of the room.

Fields 14 - 18 - XRF readings (513) - XRF readings from a baseboard, floor, radiator, cabinet, and fireplace within

the room.

Field 19 - Batch number (12).

Field 20 - Successor index (12)

.

LINE 17 - Move Line - FORTRAN Format (16, 12, 13, 48X, 212).

Field 1 - DU serial number (16)

.

Field 2 - Line type (12), set equal to 17.

Field 3 - Moves (13) - The number of moves the family has made

within the preceding six years.

Field 4 - Batch number (12)

.

Field 5 - Successor index (12)

.

LINES 18 & 19 - Exterior Lines - FORTRAN Format (16, 12, 7(A3,I3), 313,

212 ) .

Field 1 - DU serial number (16)

.

Field 2 - Line type number (12)

.

Field 3 - Wall condition (A3) - Like Field 3 of the interior

81
section, but here refers to the exterior wall.

Field 4 - Wall reading (13) - XRF reading for the wall.

Fields 5 & 6 - (A3, 13) - Like Fields 3 and 4, for the porch

floor

.

Fields 7 & 8 - (A3, 13) - Like Fields 3 and 4, for exterior door.

Fields 9 & 10 - (A3, 13) - Like Fields 3 and 4, for exterior

window sill or frame.

Fields 11 & 12 - (A3, 13) - Like Fields 3 and 4, for porch

railings

.

Fields 13 & 14 - (A3, 13) - Like Fields 3 and 4, for fence.

Fields 15 & 16 - (A3, 13) - Like Fields 3 and 4, for a painted

surface of the garage. (Line 18 only.)

Fields 17 - 19 - (313) - The number of bedrooms, bathrooms,

and rooms other than bedrooms or bathrooms which

were not inspected. (Line 18 only.)

Field 20 - Batch number (12) ; this will be found in Field 15

for line 19.

Field 21 - Successor index (12) ; this will be found in Field 16

for line 19.

LINES 20 - 29 - Formatted PSE Line - One line appears for each child from

whom blood was collected. FORTRAN Format (16, 12, A2,

712, 2A1 , 212, II, Al, 15, Al, II, 12, 15, 212, 15,

12, 211, 14X/5I1, 212, 2A5 , 211, 212).

Field 1 - Serial number (16)

.

Field 2 - Child number + 19 (12) ; thus child 1 is denoted by

82
Field 3

Field 4

Field 5

Field 6

Field 7

Field 8

Field 9

Field 10

Field 11

Field 12

Field 13

Field 14

Field 15

Field 16

Field 17

Field 18

Field 19

Field 20

20, child 2 is denoted by 21 etc.

Inspector's identification (A2)

.

Month of inspection (12)

.

Day of month (12)

.

Blood lead level (12), initial screening micro.

Age of child in months (12) ; "99" indicates 99 months

or older.

Rank of child in family (12)

.

Height of child (inches) (12)

.

Weight of child (pounds) (12)

.

Sex (Al) ; (M=Male; F=Female)

.

Race (Al) ; (W=White; B=Black; 0=0riental)

.

Months child has lived in present dwelling unit (12)

.

Months child has lived in present census tract (12).

Percent of waking hours child spends in his unit (II)

:

1 . 0

- 25%

2. 25% - 50%

3. 50% - 75%

4. 75% - 100%

More than 25% of waking hours spen;t at friends or

relatives? (Al) . Y=Yes; N=No.

Friend's or relative's census tract (15) if Field

16 indicates Yes.

Does child attend preschool? (Al) . Y=Yes; N=No.

Preschool days/week (II)

.

Preschool hours/day (12); in tenths of hours.

f

83
Field 21 - Preschool census tract (15).

Fields 22 & 23 - Favorite play areas (212)

:

1. Grass

2. Dirt

3. Pavement

Field 24 - Play area census tract (15)

.

Field 25 - Indoor play area (12) ; room number used on DCF.

Field 26 - Pica evidence (II)

:

1. No

2. Possible

3. Confirmed

4. Other

Field 27 - Number of siblings six or under (II)

.

Field 28 - Number of siblings 7 to 11 (II)

.

Field 29 - Number of siblings 12 or over (II).

Field 30 - Family income (II)

:

1. 0 - 3,999

2. 4,000 - 6,999

3. 7,000 - 10,999

4. 11,000 or more

5. Cares not to answer

6. None of the above

Field 31 - Work situation (II)

:

0. Neither works

1. Mother works

2. Father works

3. Both work

84
Field 32 Child care (II)

:

0. Not answered

1. Older sibling

2. Adult non-relative

3. Adult relative

4. Day care

Field 33 - Years of education of mother (12)

.

Field 34 - Years of education of father (12).

Field 35 - Mother’s origin (A5) ; a five-character code defined

as follows:

Character 1:

0 = Pennsylvania, but not Allegheny County

1 = Allegheny County

A = Not Pennsylvania

Characters 2-3:

AA = Non-U. S.

otherwise = Two-letter state postal code

Characters 4-5:

AA = If state code in 2 - 3

otherwise = Two-letter country of origin abbreviation

Field 36 - Father’s origin code (A5) ; as in Field 35.

Field 37 - Number of parents resident (II)

.

Field 38 - Number of adults resident (II)

.

Field 39 - Batch number (12) .

Field 40 - Successor index (12)

.

85
LINES 30 - 39 - Blood Collector's Comments - FORTRAN Format (16, 12,

8A6, A3, 14X/3A6, A3, 212).

Field 1 - Serial number (16).

Field 2 - Line number (12).

Fields 3 - 15 - Free form text (8A6, A3, 3A6, A3).

Field 16 - Batch number (12)

.

Field 17 - Successor index (12).

86
APPENDIX C

TABLE OF CONTENTS TO DATA ANALYSES PERFORMED

The data analyses discussed in this report represent selected

results from a considerably wider class of analyses that were in fact

performed using the Pittsburgh survey data. The obiect of this appendix

is to provide a brief summary of the types of tabulations and statistical

analyses that have already been conducted. Such analyses are grouped

together under the following headings:

I. HOUSING - investigations of housing-related variables and measured

lead levels.

II. CHILD - preliminary investigations of the blood data and certain

PSE information.

III. HOUSING/CHILD - investigations of child data (especially blood

lead levels) in relation to housing variables.

IV. SAMPLING - investigations of sampled dwelling unit characteristics, and comparison of dwelling units containing tested/

non-tested children.

Certain analyses have been presented in this housing analysis

report (Parts I, II) or in a companion blood analysis report T^l. Such

analyses are indicated below by the designations (F) and (B)

,

respectively.

Other analyses have been performed using the Pittsburgh data but not

reported, and these are indicated below by (U) , for "unpublished.''

I. HOUSING ANALYSES

(H) A. Multidimensional tabulations of highest lead reading, by

- occupancy class

- room type

87
- lead level

- surface type

- DU age category

- surface condition

- level of aggregation (dwelling, room, surface)

(H) B. Multidimensional tabulations of different room-based statistics,

giving their mean and standard deviation, by

- occupancy class

- room type

- lead interval

- surface type

- DU age category

- surface condition

- statistic (mean, standard deviation, median, high)

(U) C. Wall lead levels and census tract variables, plotted in relation

to one another. Census tract variables include:

- fraction of population under the age of 7

- education level

- income

- fraction of households below poverty level

- value of dwelling

- housing age

- fraction of non-rent income

(H) D. Statistical analyses of lead level distributions by

- DU age category

- surface type

88
- surface condition

- statistic (mean, high DU reading)

and using probability plots for the following distributions:

- normal

- lognormal

- Weibull

- extreme value

- uniform

- Cauchy

- Tukey ' s X

II. CHILD ANALYSES

(B) A. Summary statistics for blood lead levels, by

- age of child

- sex of child

(U) B. Distributions and probability plots for blood lead levels, bv

- age of child

- sex of child

(U) C. Correlation matrices for combinations of

- age of child

- sex of child

- blood lead level

III. HOUSING/CHILD ANALYSES

(U) A. Blood lead levels plotted against census tract variables

(B) B. Summary statistics for blood lead levels, by

89
- DU age category

- age of child

- sex of child

(U) C. Graphical plots and correlation matrices for combinations of

- blood lead levels

- DU age category

- age of child

- sex of child

(IT) D. Probability plots for blood lead levels, bv

- DU age category

- age of child

- sex of child

(U) E. Correlation matrices for combinations of

- blood lead levels

- room type

- surface type

- surface condition

- surface lead level statistics

fraction of surfaces exceeding fixed levels

mean

median

high

standard deviation

(U) F. Blood lead level distributions (frequency/cumulative) by

- DU age category

- age of child

90
- sex of child

- fraction of surfaces exceeding certain fixed levels

(H) G. Multidimensional tabulations of different room-based statistics,

giving their mean and standard deviation, by

- occupancy class

- room type

- blood lead interval

- surface type

- DU age category

- surface condition

- statistic (mean, standard deviation, median, high)

(B) H. Distributions and summary statistics for blood lead levels, by

- fraction of surfaces exceeding fixed levels

- surface condition

(B) I. Summary statistics for blood lead levels, by

- DTT age category

- maximum surface lead level

IV. SAMPLING ANALYSES

(H) A. Comparison of sample characteristics with 1970 census data, by

- census tract counts

- dwelling unit counts

(B) B. Comparison of dwelling units containing children tested,

children not tested, and all sampled dwelling units, by

- occupancy class

- surface type

91
- room type

- level of aggregation (room, surface)

- statistic (mean, standard deviation)

92
NBS-1 14A (REV. 7-73)

U.S. DEPT. OF COMM. BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR REPORT NO. NBSIR 77-1250

2. Gov’t Accession

No.

3. Recipient’s Accession No.

4. TITLE AND SUBTITLE

ANALYSIS OF HOUSING DATA COLLECTED IN A LEAD-BASED PAINT

SURVEY IN PITTSBURGH, PENNSYLVANIA: PART I

5. Publication Date March 1977

6. Performing Organization Code

7. AUTHOR(S)

Douglas R. Shier and William G. Hall

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

. WASHINGTON, D.C. 20234

10. Project/Task/Work Unit No.

11. Contract/Grant No.

12. Sponsoring Organization Name and Complete Address (Street, City, State, ZIP)

Office of Policy Development and Research

Department of Housing and Urban Development

Washington, D.C. 20410

13. Type of Report & Period Covered Final

14. Sponsoring Agency Code

15. SUPPLEMENTARY NOTES

16. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bibliography or literature survey, mention it here.)

This report is a companion document to a previous report (NBSIR 76-1024) on blood lead levels of children tested during a lead-based paint survey in

Pittsburgh, Pennsylvania. The emphasis in this report is on the methodology

used and types of housing-related information collected by the survey. Through

the use of portable x-ray fluorescence lead detectors, measurements were taken

from a variety of surfaces within rooms of the dwelling unit as well as at

locations exterior to the unit. Analyses of these x-ray fluorescence

measurements established that older housing units exhibit considerably greater

lead levels than newer housing units. In addition, wet rooms (kitchen and

bathrooms) have higher levels than other (dry) rooms, rooms with a poor

surface/substrate condition have higher levels than rooms with a good

surface/substrate condition, and trim surfaces (e.g., doors, windows,

baseboards) have higher levels than walls. Also, exterior surfaces show

higher readings than functionally similar interior surfaces. While the

present report concentrates on the housing aspect of the survey, subsequent processing of the Pittsburgh data is under way to determine possible relationships

among blood lead levels, socioeconomic variables and housing-related

characteristics

.

17. KEY WORDS (six to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name,- separated by semicolons)

Children; data analysis; housing; lead paint; lead poisoning; surveys; x-ray

fluorescence.

18. AVAILABILITY ^Unlimited 19. SECURITY CLASS

(THIS REPORT)

21. NO. OF PAGES

1 For Official Distribution. Do Not Release to NTIS UNCL ASSIFIED 100

1

1 Order From Sup. of Doc., U.S. Government Printing Office Washington, D.C. 20402. SD Cat. No. 03

20. SECURITY CLASS

(THIS PAGE)

22. Price

1* 1 Order From National Technical Information Service (NTIS)

Springfield, Virginia 22151 UNCLASSIFIED $5.00

* U. S. GOVERNMENT PRINTING OFFICE : 1977--240-848/192 USCOMM-DC 2 904 2- P 7

4