&EPA
United States
Environmental Protection
Agency
Office of Research and
Development
Washington, DC 20460
EPA/600/AP-93/001C
July 1993
Urban Soil Lead
Abatement
Demonstration
Project
Volume III: Part 2
Baltimore Report
Review
Draft
(Do Not
Cite or
Quote)
Notice
This document is a preliminary draft. It has not been formally
released by EPA and should not at this stage be construed to
represent Agency policy. It is being circulated for comment on its
technical accuracy and policy implications.
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EPA600/AP-93/001C
July 1993
Urban Soil Lead Abatement
Demonstration Project
Volume III. Part 2
Baltimore Report
Environmental Criteria and Assessment Office
Office of Heafth and Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
Printed on Recycled Paper
-------
DISCLAIMER
This document is an internal draft for review purposes only and does not
constitute U.S. Environmental Protection Agency policy. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
u
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TABLE OF CONTENTS
LIST OF TABIJBS vi
LIST OF FIGURES . . viii
ACKNOWLEDGEMENTS xi
1. EXECUTIVE SUMMARY 1-1
1.1 STUDY DESIGN 1-1
1.2 ENVIRONMENTAL MEASURES 1-2
1.3 DEMOGRAPHIC AND BEHAVIORAL QUESTIONNAIRE ... 1-3
1.4 BIOLOGIC MEASURES 1-3
1.5 INTERVENTIONS 1-3
1.6 ANALYSIS 1-4
1.6.1 Results 1-6
1.7 CONCLUSIONS 1-8
1.8 IMPLICATIONS 1-8
2. INTRODUCTION 2-1
2.1 HEALTH EFFECTS 2-1
2.2 BIOLOGICAL FATE AND METABOLISM OF LEAD 2-1
2.3 SOIL AND DUST LEAD AND THEIR RELATIONSHIP
TO BLOOD LEAD 2-2
2.4 BALTIMORE AS A STUDY SITE 2-3
3. METHODOLOGY 3-1
3.1 PROTOCOL FOR STUDIES INVOLVING HUMAN
SUBJECTS 3-1
3.1.1 Confidentiality 3-1
3.1.2 Informed Consent 3-2
3.1.3 Ethical Considerations 3-2
3.2 STUDY DESIGN 3-2
3.2.1 Site Selection 3-3
3.2.2 Rationale for Study Site Criteria 3-5
3.2.3 Pre-study Data Gathering 3-6
3.2.4 Comparison of Study Communities 3-6
3.2.5 Study Population 3-8
3.2.6 Rationale for Study Subject Criteria 3-8
3.2.7 Sample Size Calculation 3-9
3.2.8 Comparison of Final Study Population 3-9
3.2.9 Attrition and Retention 3-10
ui
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TABLE OF CONTENTS (cont'd)
3.2.10 Community Outreach/Public Relations 3-13
3.2.11 Public Relations Officer 3-13
3.2.12 Community Outreach Coordinator 3-14
4. INTERVENTIONS 4-1
4.1 ENVIRONMENTAL MEASUREMENTS AND ANALYSIS ... 4-1
4.1.1 Soil 4-1
4.1.2 Dust 4-3
4.1.3 Water 4-4
4.1.4 Exterior Paint 4-4
4.1.5 Interior Paint 4-4
4.1.6 Quality Assurance for Soil and Dust Sampling and
Analysis 4-5
4.2 DEMOGRAPHIC AND BEHAVIORAL QUESTIONNAIRE ... 4-5
4.3 BIOLOGICAL SAMPLING AND MEASURES 4-6
4.3.1 Blood 4-7
4.3.2 Hand Lead Determinations 4-7
4.3.3 Quality Assurance and Control for Blood Lead
Measurements 4-8
4.4 DETAILED DESCRIPTION OF THE INTERVENTIONS .... 4-9
4.4.1 Exterior Paint Stabilization 4-9
4.4.2 Soil Abatement 4-10
4.4.3 Abatement Costs 4-10
5. ANALYSIS . 5-1
5.1 DATA COLLECTION AND MANAGEMENT 5-1
5.2 RESULTS 5-2
5.2.1 Effect of Soil Abatement 5-2
5.2.2 Relationship to Blood Lead Level 5-2
6. DATA ANALYSIS 6-1
6.1 VARIABLE SELECTION 6-1
6.2 BIOLOGIC VARIABLES AND VARIABLES FROM THE
QUESTIONNAIRE 6-1
6.2.1 Blood Lead 6-1
6.2.2 Hand Lead 6-1
6.2.3 Age 6-8
6.2.4 Socioeconomic Status 6-8
6.2.5 Season 6-8
6.2.6 Mouthing Behavior 6-15
6.3 ENVIRONMENTAL VARIABLES 6-16
6.3.1 Abatement 6-16
6.3.2 Soil Lead 6-16
iv
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I
TABLE OF CONTENTS (cont'd)
Page
6.3.3 Dust Lead 6-17
6.3.4 Exterior Paint 6-20
6.3.5 Interior Paint 6-20
7. STATISTICAL ANALYSIS 7-1
7.1 STATISTICAL ANALYSIS OF ENVIRONMENTAL
VARIABLES 7-1
7.2 STATISTICAL MODELS FOR BLOOD LEAD AND
HAND LEAD 7-5
7.3 INTERPRETATION OF REGRESSION COEFFICIENTS 7-10
7.4 RESULTS OF STATISTICAL ANALYSIS 7-11
7.4.1 Model 1 7-11
7.4.2 Model 2 7-12
7.4.3 Model 3 7-23
7.4.4 Model 4 7-30
7.4.5 Model 5 7-30
7.5 IMPLICATIONS OF FINDINGS 7-46
7.6 CALL FOR FURTHER RESEARCH 7-50
8. REFERENCES . 8-1
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LIST OF TABLES
Number
3-1 Characteristics of Study and Control Sites at Time of
3-7
3-2
3-3
4-1
4-2
7-1
7-2
7-3
Characteristics of Final Study Population Based on Round 3
Study Data
Attrition and Recruitment Rounds 1 Through 6
Baltimore Paint Stabilization
Baltimore Soil Abatement
Soil Statistics Before Intervention
Dust Statistics Before Intervention
Pre- and Post-intervention Soil Statistics . .
3-10
3-12
4-13
4-14
7-2
7-2
7-3
7-4 Dust Statistics for Control Group Before and After Soil
* Abatement 7-4
7-5 Dust Statistics for Treatment Group Before and After
Soil Abatement < 7-4
7-6 Dust Statistics for Properties with and Without Lead-based
Paint 7-7
7-7 Regression Coefficient for Direct Effect of Abatement on
Blood Lead Model 1 7-13
7-8 Regression Coefficient for Adjusted Effect of Abatement on
Blood Lead Model 2 7-16
7-9 Regression Coefficient for Effect of Age on Blood Lead
Model 2 7-19
7-10 Regression Coefficient for Effect of SES on Blood Lead
Model 2 7-21
7-11 Regression Coefficient for Effect of Season on Blood Lead
Model 2 7-23
7-12 Regression Coefficient for Effect of Log Hand Lead on
Blood Lead Model 2 7-25
vi
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LIST OF TABLES (cont'd)
Number
7-13 Regression Coefficients for Effect of Abatement on Hand
Lead Model 3 7-27
7-14 Regression Coefficients for Adjusted Effect of Abatement on
Blood Lead Model 2 7-31
7-15 Regression Coefficients for Effect of Age on Hand Lead
Model 4 7-34
7-16 Regression Coefficients for Effect of Female Gender on Hand
Lead Model 4 7-36
7-17 Regression Coefficients for Effect of Season on Hand Lead
Model 4 7-38
7-18 Regression Coefficients for Effect of Dust on Hand Lead
Model 4 7-40
7-19 Regression Coefficients for Effect of Gender on Hand Lead
^ Model 5 7-42
7-20 Regression Coefficients for Effect of Age on Hand Lead
Model 5 7-44
7-21 Regression Coefficients for Effect of Season on Hand Lead
Model 5 7-46
7-22 Regression Coefficients for Effect of Dust on Hand Lead
Model 5 7-48
7-23 Regression Coefficients for Effect of Soil Lead on Hand Lead
Model 5 7-50
7-24 R-Squared Coefficient and Mean Square Error for Models with Log
(Blood Lead) as the Response Variable 7-52
vu
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LIST OF FIGURES
Number
3-1 Baltimore study design 3-4
3-2 Recruitment and retention of participants 3-12
4-1 Schedule of project activites 4-2
4-2 Typical property diagram 4-11
6-1 Normal and log-transformed distributions for blood lead,
Round 1 6-2
6-2 Normal and log-transformed distributions for blood lead,
Round 2 6-3
6-3 Normal and log-transformed distributions for blood lead,
Round 3 6-4
6-4 Normal and log-transformed distributions for blood lead,
Round 4 6-5
\
6-5 Normal and log-transformed distributions for blood lead,
Round 5 6-6
6-6 Normal and log-transformed distributions for blood lead,
Round 6 6-7
6-7 Normal and log-transformed distributions for hand lead,
Round 1 6-9
6-8 Normal and log-transformed distributions for hand lead,
Round 2 6-10
6-9 Normal and log-transformed distributions for hand lead,
Round 3 6-11
6-10 Normal and log-transformed distributions for hand lead,
Round 4 6-12
6-11 Normal and log-transformed distributions for hand lead,
Round 5 6-13
6-12. Normal and log-transformed distributions for hand lead,
Round 6 6-14
V11I
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LIST OF FIGURES (cont'd)
Number Page
6-13 Distribution of SES scores using Hollingshead Index 6-15
6-14 Tri-mean of pre- and postabatement soil lead concentrations
for control group 6-18
6-15 Tri-mean of pre- and postabatement soil lead concentrations
for treatment group 6-19
6-16 Pre- and postabatement dust lead load for control group,
all properties 6-21
6-17 Pre- and postabatement dust lead load for treatment group,
all properties 6-22
6-18 Pre- and postabatement dust lead load for control group 6-23
6-19 Pre- and postabatement dust lead load for treatment group 6-24
7-1 Correlation matrix of environmental variables 7-6
V
7-2 Model 1 results of effect of soil abatement on blood lead,
log transformed 7-14
7-3 Model 1 results of effect of soil abatement on blood lead 7-15
7-4 Model 2 results of effect of soil abatement on blood lead,
log transformed 7-17
7-5 Model 2 results of effect of soil abatement on blood lead 7-18
7-6 Model 2 results of effect of age on blood lead, log transformed . . 7-20
7-7 Model 2 results of effect of socioeconomic status on blood lead,
log transformed 7-22
7-8 Model 2 results of effect of season on blood lead, log
transformed 7-24
7-9 Model 2 results of effect of hand lead on blood lead, log
transformed 7-26
7-10 Model 3 results of effect of soil abatement on hand lead, log
transformed 7-28
IX
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LIST OF FIGURES (cont'd)
Number Page
7-11 Model 3 results of effect of soil abatement on hand lead 7-29
7-12 Model 4 results of effect of soil abatement on hand lead, log
transformed 7-32
7-13 Model 4 results of effect of soil abatement on hand lead 7-33
7-14 Model 4 results of effect of age on hand lead, log transformed . . . 7-35
7-15 Model 4 results of femal gender effect on hand lead, log
transformed 7-37
7-16 Model 4 results of effect of season on hand lead, log
transformed 7-39
7-17 Model 4 results of effect of dust lead on hand lead, log
transformed 7-41
7-18 Model 5 results of effect of gender on hand lead, log
transformed 7-43
7-19 Model 5 results of effect of age on hand lead, log transformed . . . 7-45
7-20 Model 5 results of effect of season on hand lead, log
transfonned 7-47
7-21 Model 5 results of effect of dust lead on hand lead, log
transformed 7-49
7-22 Model 5 results of effect of soil lead on hand lead, log
transformed 7-51
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ACKNOWLEDGEMENTS
The Baltimore Soil Lead Abatement Demonstration Project was managed by the
Maryland Department of the Environment (MDE) and drew upon the technical and
epidemiological resources of the State's Lead Poisoning Prevention and the Environmental
Health Programs. Laboratory support was provided by an interagency agreement with the
Department of Health and Mental Hygiene Laboratories Administration.
The Principal Investigator, Katherine P. Farrell, M.D., M.P.H., was Assistant
Secretary for Toxics, Environmental Science and Health Administration TESH for the initial
two years of the project and worked as Director of Community Health Services at the Anne
Arundel County Department of Health for the final year. J. Julian Chisolm, Jr., M.D.,
Co-investigator, is the Director of the Lead Program at the John F. Kennedy Institute and an
Associate Professor of Pediatrics at The Johns Hopkins Medical Institutions. Charles A.
Rohde, Ph.D., Professor and Chairman Department of Biostatistics at The Johns Hopkins
University School of Hygiene and Public Health, and Boon P. Lim, M.D., M.P.H., MDE
\
Administrator for the Environmental Health Program, joined the team as Co-investigators
during the data preparation and analysis phase of the study.
The Project Manager was Merrill Brophy, M.S.N., R.N. Warren Strauss performed the
statistical analysis for the study.
Reginald Harris was an invaluable player during the development of the study design
and protocols. Dr. Richard Brunker, Region ffl of the Environmental Protection Agency
supplied technical guidance and support for the project too.
The goals of the project would not have been met without the dedication and
cooperation of the following: Denise Stanley, Outreach Coordinator; Rebecca Fahey,
Environmental Coordinator; and Laura Coleson, Biological Coordinator. Without their
enthusiastic and constant efforts, the project would not have succeeded.
The project received cooperation and assistance from the City of Baltimore, the
Property Owners Association, and the Park Heights and Walbrook Junction Community
Organizations. Special thanks are due the Liberty Medical Center who contributed clinic
space free of charge.
XI
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Above all we thank the children and their families who participated hi the study.
Although the information in this document has been funded wholly or in part by the United
States Environmental Protection Agency under assistance agreement V-003409-01 to the
Maryland Department of the Environment, it may not necessarily reflect the views of the
Agency and no official endorsement is inferred.
XII
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Baltimore Lead in Soil Project
Data Management Plan
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I
Overview of Data Management Plan
The Baltimore Lead in Soil Project (BLISP) has collected several kinds of
environmental and biological data in the hope of explaining the question: Does the
removal of lead (Pb) through the abatement of Soil surrounding a house and exterior
Paint have an impact on the levels of Lead in children's blood who live in that
house. These data have been entered, manipulated, and quality controlled using
Personal Computers and the Dbase III+ software package. These data are being
analyzed statistically using the SAS statistical Software Package.
Quality Control
Quality control has been achieved through the duplication of effort
and computer programs. Data has usually progressed through the following steps.
1) Data transferred from laboratory source to data entry sheets. (Done twice)
2) Data entered into computer for each set of data entry sheets.
3) Dbase program run on two files to identify differences.
(See appendix A - page 1)
Organization of Data
Data collected can be cast into four groups; Environmental, Biological,
Questionnaire, and Support Data. Support files contain the names of
participants, names of property owners, etc. Two of the three groups of data,
Biological and Questionnaire, are gathered every time blood samples are
retrieved from the participants. BLISP refers to each Blood sampling as a
round. Our study presently consist of six rounds. Within the third group,
Environmental Data, Soil and Dust samples were retrieved before and after
abatement, Paint samples were retrieved once for the Exterior and Interior of
the house, and Water samples were retrieved once during the pre-abatement
period of the project.
C- I
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Producing Files for Data Analysis
The files generally do not contain enough information to be analyzed directly.
However, we can combine information from various files, to produce a new file
with just the information you want to analyze. The fields PROPID and ID are KEY
fields in this database. The field PROPID is an identification number for a property
in the study. The field ID is an identification number for each child participant
in the study. Each file contains one of these KEY fields.
This means that any variables in this database can be combined into a new file
using those key fields or any fields that happen to be contained in the two files
being merged. The new file can be then analyzed directly using a statistical package.
All the Environmental data files contain the field PROPID. All the Biological data
files contain the field ID. All the Questionnaire data files contain both the KEY
fields, ID and PROPID. The Questionnaire file is the key link between the Biological
and Environmental data files. Other important fields in this database include the
PARENTCODE, ROUND, DOT, and BIRTH fields. The age of participants can be
calculated using the DOT - Date of Test field in the QUESTIONNAIRE File and the
BERTH field in the KIDS File. One might want to add or delete records from a new file
based on the ROUND field, which occurs in the QUESTIONNAIRE and BIO_# Files.
If you wanted to group participants with the same mother you would use the
PARENTCODE field located in the KIDS File.
There are fields which can be broken down into new fields, because these fields
might have some special qualities. One of these is the PROPID field. BIISP maintains
a study area and a control area, each having distinct properties (homes). The study
area is designated as Area 1 and the control area is designated as Area 2. This data item
is the only field in the database which has been broken down into another field. The field
AREA was derived from the field PROPID in the Questionnaire file and placed back into
the original Questionnaire file. There also exist a street code and a house code within
the PROPID field. Refer to the field definitions section for specific information on
fields with multiple values, such as SAMPNUM AND SAMPCODE.
A very important factor to consider when analyzing this database is that
an experience data processing professional, or an environmental analyst with high
level data manipulation skills using SAS or Dbase Language is needed to get the
data into the various structure(s) that you may want to analyze.
C-2
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Files
Bioloical
BIO_2.
BIO_3.
BIO_4.
BIO_5.
BIO 6.
Questionnaire
QUEST 1.
QUEST_2.
QUEST_3.
QUEST_4.
QUESTJ.
QUEST 6.
Environmental
PRE_SOIL.
POSTSOIL.
PRE_DUST.
WATER.
IJPAINT.
E PAINT.
Support Files
KIDS.
C -3
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File Structures
C-4
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Structures for KIDS File
field no.
1
2
3
field name
data type
ID NUMERIC
BIRTH DATE
PARENTCODE NUMERIC
width
3
8
4
dec
0
0
0
Structures for BIO # file
field no.
1
2
3
4
5
6
7
8
field name
data type
width
dec
ID
ROUND
MPB
MFP
FE
TIBC
H
ELB
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
3
1
5
3
3
3
6
6
0
0
1
0
0
0
2
2
Structures for WATER file
field no.
1
2
3
4
field name
PROPID
SAMPNUM
SAMPCODE
WF
data type width dec
NUMERIC 7 0
CHARACTER 9 0
NUMERIC 4 0
NUMERIC 6 3
C-5
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Structures for E PAINT file
field no.
1
2
3
4
field name
PROPID
SAMPNUM
SAMPCODE
PF XRF
data type width dec
NUMERIC 7 0
CHARACTER 9 0
NUMERIC 4 0
NUMERIC 6 0
Structures I PAINT file
field no.
1
2
3
4
5
6
field name
PROPID
SAMPNUM
SAMPCODE
PF_PGT 1
PF_PGT~2
PF PGT 3
data type
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
width
7
2
5
6
6
6
dec
0
0
0
0
0
0
Structures for PRE DUST file
field no.
1
2
3
4
5
6
7
field name
PROPID
SAMPNUM
SAMPCODE
WGT_AAS
WGTJCRF
AAS_PPM
XRF PPM
data type width dec
NUMERIC 7 0
CHARACTER 9 0
NUMERIC 4 0
NUMERIC 8 0
NUMERIC 8 0
NUMERIC 8 0
NUMERIC 8 0
C-6
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Structures for PRE SOIL file
field no.
1
2
3
4
field name
PROPID
SAMPNUM
SAMPCODE
FSF
Structures for POSTSOIL file
field no.
1
2
3
4
field name
PROPID
SAMPNUM
SAMPCODE
FSF
data type
NUMERIC
CHARACTER
NUMERIC
NUMERIC
data type
width
7
9
4
4
width
7
9
4
4
dec
0
0
0
0
dec
0
0
0
0
Structures for QUESTIONNAIRE file
field no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
field name
data type
width
dec
CITY
ROUND
FORM
PROPID
AREA
ADDN
ADD
ID
INT
DOT
Q100A
Q100B
Q102A
Q102B
Q200
Q201A
Q201B
Q300
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
DATE
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
DATE
3
3
3
9
3
4
6
5
3
8
3
3
4
4
4
4
4
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C-7
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19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Q301
Q302
Q303
Q304
Q305
Q 306A
Q 306B
Cr306C
Q 306D
(f 306E
Q 307A
Q 307B
Q 307C
Q 307D
Q~307E
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
3
3
4
3
4
3
3
3
3
3
3
3
3
3
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
field no.
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
field name
data type
width
dec
Q308
Q310
Q311
Q312
*3400
Q401
Q402
3403
Q403A
Q403B
Q403C
0404
Q405
Q407
Q407A
0408
Q409
Q410
Q411
Q412
Q413
Q414
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
3
4
4
4
3
3
3
3
3
3
3
3
3
3
4
3
3
3
3
4
3
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C-8
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56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
Q415
Q500
Q501
Q502
Q 505A
Q_505B
Q_505C
Q_505D
Q_505E
Q_505F
QJ06A
Q 506B
Q~506C
Q~506D
Q 506E
NUMERIC 4
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
NUMERIC 3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
field no.
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
field name
data type
width
dec
Q 506F
Q600
Q601A
Q601B
Q602A
Q602B
Q602C
Q603A
Q603B
Q603C
Q604A
Q604B
Q700A
Q700B
Q701
Q702
Q703A
Q703B
Q704A
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
3
3
3
3
3
4
3
3
4
3
3
3
3
6
3
3
3
4
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C-9
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90
91
92
93
94
95
96
97
98
99
100
101
Q704B
Q800
Q801
Q802
Q803
Q804
Q805
Q806
Q807
Q808
Q809
Q1002
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
NUMERIC
4
3
3
4
4
4
5
4
3
3
3
3
0
0
0
0
0
0
0
0
0
0
0
0
C- 10
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Field Descriptions
QUESTIONNAIRE FILE
Field Description or Codes
1 CITY
2
3
4
5
6
7
8
9
10
11
ROUND
FORM
PROPID
AREA
ADDN
ADD
ID
INT
DOT
Q100A
1 = Baltimore
1-6
Internal Use Only
The next 3 field combined in this sequence
1 = Study Area
2 = Control Area
Code for street name
House Number
Child id - a three digit sequential number
1 digit code for name of interviewer
Date of Interview - 6 digits: month, day, year
Are you the parent or guardian of study child?
1 = yes
2 = no
12 Q100B Relationship to child
1 = mother
2 = father
3 = aunt or uncle
4 = grandparent
5 = foster parent or guardian
6 = other
C- 11
-------
13 Q102A How long has the child been living at this
address ? two digits for years
14 Q102B How many months has the child been living
at this address ?
15 Q200 What is the total number of persons aged 18
or over living in the household?
16 Q201A What is the total number of persons less
than 18 years old living in the household?
17 Q201B How many of these are under six years old?
18 Q300 What is the child's date of birth?
********* Blanked out - Retrieve from KIDS File
19 Q301 What is the child's race?
1 = black
2 = white
20 Q302 What is the child's sex?
1 = male
2 = female
21 Q303 How many hours per day does the child play
2 outdoors? Two digit number
99 = Unknown
22 Q304 Where does the child spend most of their time
outside ?
1 = Around your home
2 = Around a baby sitters, friends, or relative's home
3 = around a day care center or school
4 = at a public park or play-ground
8 = not applicable
9 = unknown
C- 12
-------
23 Q305 How many hours does the child play outside
their home ? Two digit number
99 = Unknown
88 = Not applicable
24-28 Q306A-E Does the child play outdoors around their home
in the following places ?
24 Q306A = backyard
25 Q306B = side yard
26 Q306C = front yard
27 Q306D = street
28 Q306E = alley
The possible responses for each are ;
1 = yes
2 = no response
8 = not applicable
9 = unknown
29-33 Q307A-E Regardless of which place the child plays, does that
area consist of all, or even a percentage of the
following.
29 Q307A = grass
30 Q307B = concrete or asphalt
31 Q307C = dirt or soil
32 Q307D = a sandbox
33 Q307E = a painted porch or deck
The possible responses for each are ;
1 = yes
2 = no response
8 = not applicable
9 = unknown
C- 13
-------
34 Q308 Did the child often take food or a bottle with them
when they played outside?
1 = yes
2 = no response
8 = not applicable
9 = unknown
35 Q310 How many hours does the child play indoors at home?
Two digit number
99 = unknown
36 Q311 How many hours does the child play indoors away from
home ? two digit number with code
99 = unknown
37 Q312 How many hours does the child spend sleeping?
two digit number or code
99 = unknown
38 Q400 Does the child use a pacifier?
1 = yes
2 = no
9 = unknown
39 Q401 How often does the child put their fingers in their
mouth?
1 = a lot
2 = just once in a while
3 = almost never
9 = unknown
C - 14
-------
40 Q402 How often does the child put toys and things
that are not food into their mouth?
1 = a lot
2 = just once in a while
3 = almost never
9 = unknown
41 Q403 How often have you seen the child put their
mouth on a window sill ?
1 = a lot
2 = just once in a while
3 = almost never
9 = unknown
42 Q403A Have you ever seen the child put his mouth on
the window sill?
1 = yes
2 = no
9 = unknown
43 Q403B Have yau ever seen the child put his mouth on
the stair railing?
1 = yes
2 = no
9 = unknown
44 Q403C Have you ever seen the child put his mouth on
any furniture?
1 = yes
2 = no
9 = unknown
C- 15
-------
45 Q404 Have you ever seen the child put paint chips into his
mouth?
1 = yes
2 = no
9 = unknown
46 Q405 Have you ever seen the child eat dirt or sand?
1 = yes
2 = no
9 = unknown
47 Q407 What's the main type of milk that the child drinks?
1 = breast milk
2 = cow's milk
3 = formula
4 = condensed milk
9 = unknown
48 Q407A How many glasses of milk ( ounces ) does your child drink
per day ? Two Digits
49 Q408 Does the child take Feosol, Poly Vi Sol, or any other iron
supplement?
1 = yes
2 = no
3 = formula with iron
9 = unknown
50 Q409 Does the child drink fruit juices everyday?
1 = yes
2 = no
9 = unknown
51 Q410 Does the child eat table food?
1 = yes
2 = no
9 = unknown
C - 16
-------
52 Q411 Does the child eat any vegetables from your garden
or any other garden in your neighborhood?
1 = yes
2 = no
8 = not applicable
9 = unknown
53 Q412 Does the child use their fingers when they eat table food?
1 = yes
2 = no
8 = not applicable
9 = unknown
54 Q413 Is the family's food or drink ever stored or served
in home made or imported clay pottery?
1 = yes
2 = no
9 = unknown
55 Q414 Is any of the family's food stored in the original
cans after being opened, for example fruit juice?
1 = yes
2 = no
9 = unknown
56 Q415 How many glasses or bottles of water does the child
drink? two digit number
57 Q500 Do you have any dogs or cats?
1 = no dogs or cats
2 = dogs only
3 = cats only
4 = at least one dog and cat
9 = unknown
C - 17
-------
58 Q501 Where does the dog stay most of the time?
1 = inside
2 = outside
3 = in and out all the time
8 = not applicable
9 = unknown
59 Q502 Where does the cat stay most of the time?
1 = inside
2 = outside
3 = in and out
8 = not applicable
9 = unknown
60-65 Q505A-F Does anyone who lives in the household work in
any of the following jobs?
54 Q505A = plumbing
55 Q505B = sandblasting
56 Q505C = auto body work
57 Q505D = painting
58 Q505E = demolition
59 Q505F = welding
The possible responses for each are ;
1 = yes
2 = no response
8 = not applicable
9 = unknown
66-71 Q506A-F In the last three months has anyone in your household
done any of the following activities?
66 Q506A = painted pictures with artist's paint
67 Q506B = removed paint from anything
68 Q506C = painted bicycles or cars
C - 18
-------
69 Q506D = worked with stained glass
70 Q506E = soldered electronic parts
71 Q506F = soldered pipes
The possible responses for each are ;
1 = yes
2 = no response
8 = not applicable
9 = unknown
72 Q600 Does the child have any medical or developmental
problems that you know of?
1 = yes
2 = no
9 = unknown
73 Q601A Has the child been tested for sickle cell?
1 = yes
2 = no
9 = unknown
74 Q601B If yes what were the results?
1 = negative
2 = sickle cell trait
3 = sickle cell disease
8 = not applicable
9 = unknown
75 Q602A Has the child ever had anemia or low blood?
1 = yes
2 = no
9 = unknown
C- 19
-------
76 Q602B
77 Q602C
78 Q603A
79 Q603B
80 Q603C
81 Q604A
If yes what year was it diagnosed? 82-88?
99 = unknown or not applicable
If yes, is the child being treated?
1 = yes
2 = no
8 = not applicable
9 = unknown
Has the child ever been tested for lead before?
1 = yes
2 = no
9 = unknown
If yes what year was-it diagnosed? 82-88?
99 = unknown or not applicable
If yes, is the child being treated?
1 = yes
2,= no
8 = not applicable
9 = unknown
Has the child ever received medical care for lead
poisoning?
1 = yes
2 = no
9 = unknown
82 Q604B If yes, was the medical care:
1 = outpatient
2 = inpatient
8 = not applicable
9 = unknown
C-20
-------
83 Q700A Was your house built before WWII?
1 = yes
2 = no
9 = unknown
84 Q700B
85 Q701
86 Q702
87 Q703A
88 Q703B
89 Q704A
Code the year as a four digit number or;
9999= unknown
Has anyone removed paint or sanded a painted
part of the house in the last three months?
1 = yes
2 = no
9 = unknown
Has anyone ever removed paint or sanded a painted
part of the house?
1 = yes
2 = no
9 = unknown
Since you lived in this house, has anyone
removed or sanded paint inside the house?
1 = yes
2 = no
9 = unknown
If so, when? Ex. 91 89 etc.
Since you lived in this house, has anyone
removed or sanded paint from the outside of the house?
1 = yes
2 = no
9 = unknown
C-21
-------
90 Q704B If so, when? Ex. 91 89 etc.
91 Q800 Do you own or rent your home?
1 = rent
2 = own
3 = staying for free
9 = unknown
92 Q801 Marital status
1 = married
2 = divorced
3 = separated
4 = widowed
5 = single
93 Q802 Occupational status coded as a two digit response:
First digit: What is your occupational status?
1 = unemployed
2 = homemaker
3 = employed part time
4 = employed full time
5 = retired
Second digit: What is your occupation?
Refer to the Hollingshead Index of Social Status
for listing of occupations under each main heading
0 = unemployed or homemaker
1 = menial service workers
2 = unskilled workers
3 = machine operators and semiskilled workers
4 = skilled manual workers and craftsmen
5 = clerical and sales workers
6 = technicians, semi-professional and small business owners
7 = small business owners, managers and minor professionals
8 = administrators and proprietors of medium Businesses
9 = unknown
C-22
-------
94 Q803
95 Q804
96 Q805
What is the highest grade of school finished?
99 = unknown
Is the child supported by another person coded?
First digit:
1 = yes
2 = no
9 = unknown
Second digit, what is their relationship to the child?
1 = mother
2 = father
3 = aunt or uncle
4 = grandparent, great aunt or uncle, or grandparent
5 = foster parent or guardian
6 = other
9 = unknown
What is the relationship of the head of the household to
the child?
First digit:
1 = mother
2 = father
3 = aunt or uncle
4 = grandparent, great aunt or uncle,
or great grandparent
5 = foster parent or guardian
6 = other
9 = unknown
C- 23
-------
Second digit: occupational status
1 = unemployed
2 = homemaker
3 = employed part time
4 = employed full time
5 = retired
Third digit: occupation code
Refer to the Hollingshead Index of Social Status
for listing of occupations under each main heading
0 = unemployed or homemaker
1 = menial service workers
2 = unskilled workers
3 = machine operators and semiskilled workers
4 = skilled manual workers and craftsmen
5 = clerical and sales workers
6 = technicians, semi-professional and small business owners
7 = small business owners, managers and minor professionals
8-= administrators and proprietors of medium Businesses
9 = unknown
97 Q806 What is the highest grade of school completed?
99 = unknown
98 Q807 Does your family use the WIC program?
1 = yes
2 = no
9 = unknown
99 Q808 What type of medical insurance does your child have?
1 = no medical insurance
2 = private medical insurance (eg. BC/BS)
3 = Medicaid
8 = other
9 = unknown
C-24
-------
100 Q809 What was the total income for the family before taxes
in the previous year?
1 = less than $5,000
2 = $5,000 or more but less than $10,000
3 = $10,000 or more but less than $15,000
4 = $15,000 or more but less than $20,000
5 = $20,000 or more but less than $25,000
6 = $25,000 or more
8 = refused to answer
9 = unknown
101 Q1002 In your opinion, the quality of the interview is:
1 = reliable
2 = some doubt
3 = unreliable
C - 25
-------
KIDS FILE
1
Field
ID
2 FIRST
3 LAST
4 BIRTH
BIO FILE
Field
1
2
3
4
5
6
ID
ROUND
MPB
MFP
FE
TIBC
H
8 ELB
Description or Codes
Sequential number ID for children in study
All id's are original - used only once
First name of child in study
Last name of child in study
Date of birth of child in study.
Description or Codes
Identification number for each C^;M in the study
Round that Sample was taken
Mean Blood Lead -1 = no data
Mean Free Erythrocytic Protoporphyrin
-1 no data
Ferritin
-1 = no data
Total Iron Binding Capacity
-1 = no data
Hand-wipe
Elbow-wipe
.01 = undetectable
-1 = no data
.01 = undetectable
-1 = no data
C-26
-------
WATER FILE
Field Description or Codes
1 PROPID Identification number of each property in the study
1st Digit - Study Area - "1" or "2"
2nd and
3rd Digits - Codes for Street Names
4th -
7th Digits - House Number
2 SAMPNUM Identification number of each Water Sample collected
1st Digit - Sample type W=Water etc.
2nd Digit - Last digit of year sample taken
3rd and
4th Digits Month sample taken
5th and
6th Digits - Day sample taken
7th Digit - Sequential number of houses sampled
on day in digits 2-6
8th and
9th Digits - Sequential number of samples taken
on a single property
3 SAMPCODE Code for location of Water sample within house
1st Digit - Floor of House sample taken
1 - 1st floor
2 = 2nd floor
3 = 3rd floor
2nd Digit - What type of condition water
sample taken
1 = hot tap
2 = cold tap
3 = hot/cold tap
C -27
-------
3rd and
4th Digits
Special Codes
WF Water Fraction
E PAINT FILE
11 = 1st draw kitchen
12 = 1st draw bathroom
13 = non-lst draw kitchen
14 = non-lst draw bathroom
Field
Description or Codes
PROPID Identification number of each property in the study
Study Area - "1" or "2"
Codes for Street Names
House Number
Identification number of each Paint Sample collected
1st Digit
2nd and
3rd Digits
4th-
7th Digits
SAMPNUM
1st Digit
2nd Digit
3rd and
4th Digits
5th and
6th Digits
7th Digit
8th and
9th Digits
Sample type P=Paint etc.
Last digit of year sample taken
Month sample taken
Day sample taken
Sequential number of houses
sampled on day in digits 2-6
Sequential number of samples
taken on a single property
C- 28
-------
3 SAMPCODE Code for location of Paint sample within house
1st Digit What part of outside of house
was sample taken as you face the
front door of house
1 = LEFT
2 = RIGHT
3 = FRONT
4 = BACK
2nd Digit - What area on that part of the house
was sample taken
1 = 1st floor - LEFT
2 = 1st floor - RIGHT
3 = 1st floor - CENTER
4 = 2nd floor - LEFT
5 = 2nd floor - RIGHT
6 = 2nd floor - CENTER
7 = 3rd floor - LEFT
8 = 3rd floor - RIGHT
9 = 3rd floor - CENTER
3rd and
4th Digits - Special Codes
1 = DOOR
2 = WINDOW SILL
3 = STEPS
4 = WALL (HOUSE)
5 = COLUMN/BEAM
6 = RAILING/BANNISTER
7 = PORCH ROOF
8 = PORCH FLOOR
9 = PORCH WALL
10 = TRAP DOOR
11 = YARD - BRICKS/STONES
12 = FENCE
13 = GARAGE
C-29
-------
14 = SHED
15 = CLOTHES LINE POLE
16 = YARD - SWING/SLIDING BOARD
17 = PORCH BASE
18 = DRAIN PIPES
19 = SEWAGE PIPES
20 = PORCH BENCH
21 = FLOWER POT
22 - STORAGE BOX
23 = OIL TANK
PF XRF Paint Fraction
C -30
-------
I_PAINT FILE
Field Description or Codes
1 PROPID Identification number of each property in the study
1st Digit - Study Area - "1" or "2"
2nd and
3rd Digits - Codes for Street Names
4th-
7th Digits - House Number
2 SAMPNUM Identification number of each Paint Sample collected
1st Digit - Sample type P=Paint etc.
2nd Digit - Last digit of year sample taken
3rd and
4th Digits - Month sample taken
5th and
6th Digits - Day sample taken
7th Digit - Sequential number of houses
sampled on day in digits 2-6
8th and
9th Digits - Sequential number of samples
taken on a single property
3 SAMPCODE Code for location of Paint sample within house
1st Digit - What level of house was sample taken
1 = 1st Floor
2 = 2nd Floor
3 = Basement
4 = between 1st & 2nd floor
5 = between basement & 1st Floor
C -31
-------
2nd and What room or area of that part of the
3rd Digit house was sample taken
1 = front entrance
2 = back entrance
3 = hallway
4 = living room
5 = dining room
6 = kitchen
7 = child's bedroom
8 = parent's bedroom
9 = bedroom - other
10 = family room
11 = den
12 = steps
13 = playroom
14 = enclosed porch
15 = bathroom
4th Digits - Special Codes
1 = Window header
2 = Window casing
3 = Window sash
4 = Window mullions
5 = Window steps
6 = Window sill
7 = Window apron
8 = Door header
9 = Door casing
10 = Door jamb
11 = Staircase railings
12 = Staircase balusters
13 = Staircase stringer
14 = Staircase newel post
15 = Staircase baseboards
16 = Staircase treads
17 = Staircase risers
18 = Upper Walls
19 = Chair Walls
C -32
-------
20 = Lower Walls
21 = Baseboard Walls
22 = Floor
23 = Radiator
24 = Ceiling
25 = Other
4 Results XRF XK-3 analysis in Parts Per Million
C - 33
-------
DUST FILE
Field Description or Codes
1 PROPID Identification number of each property in the study
1st Digit - Study Area - "1" or "2"
2nd and
3rd Digits - Codes for Street Names
4th-
7th Digits - House Number
2 SAMPNUM Identification number of each Dust Sample collected
1st Digit - Sample type P=Paiht etc.
2nd Digit - Last digit of year sample taken
3rd and
4th Digits - Month sample taken
5th and
6th Digits - Day sample taken
7th Digit - Sequential number of houses
sampled on day in digits 2-6
8th and
9th Digits - Sequential number of samples
taken on a single property
3 SAMPCODE Code for location of Dust sample within house
1st Digit - What level of house was sample
taken
1 = First floor
2 = Second floor
3 = Basement
4 = Steps between first and second floor
5 = Steps between basement & first floor
C-34
-------
2nd and
3rd Digits - On that level what is the general
name of the room where the Dust
sample was taken
1 = Front entrance
2 = Back entrance
3 = Hallway
4 = Living room
5 = Dinning room
6 = Kitchen
7 = Child's bedroom
8 = Parents bedroom
9 = Bedroom - other
10 = Family room
11 = Den
12 = Steps
13 = Playroom
14 = Enclosed Porch
15 = Bathroom
4th Digit - Special Codes
1 = Wood floor
2 = Linoleum floor
3 = Carpet on floor
4 = Tile floor
5 = Scatter rug
6 = Window sill
7 = Window well
8 = Plastic runner
9 = Other floor surface
4 WGT_AAS Weight of AAS Analysis Sample
5 WGT_XRF Weight of XRF Analysis Sample
6 AAS_PPM Results from Atomic Absorption Spectrometry analysis
7 XRF_PPM Results from X-Ray Fluorescence analysis
C-35
-------
SOIL FILE
Field Description or Codes
1 PROPID Identification number of each property in the study
1st Digit - Study Area - "1" or "2"
2nd and
3rd Digits - Codes for Street Names
4th-
7th Digits - House Number
2 SAMPNUM Identification number of each Soil Sample collected
1st Digit - Sample type P=Paint etc.
2nd Digit - Last digit of year sample taken
3rd and
4th Digits - Month sample taken
5th and
6th Digits - Day sample taken
7th Digit - Sequential number of houses
sampled on day in digits 2-6
8th and
9th Digits - Sequential number of samples
taken on a single property
2 SAMPNUM Identification number of each Soil Sample collected
1st Digit - Sample type S=Soil etc.
2nd- - Last digit of year sample taken
4th Digits - Month sample taken
5th and
6th Digits - Day sample taken
7th Digit - Sequential number of houses
sampled on day in digits 2-6
8th and
9th Digits - Sequential number of samples
taken on a single property
ODD numbers are TOP samples
EVEN numbers are BOTTOM samples
C -36
-------
3 SAMPCODE Code for location of sample within property
1st Digit - What side of property .sample
taken in relation to house - as
you face house from sample
position
1 = LEFT
2 = RIGHT
3 = FRONT
4 = BACK
2nd Digit - What part of area of
yard determined in 1st digit
are you within
1 = Near foundation - LEFT
2 = Near foundation - RIGHT
3 = Near foundation - CENTER
4 = Mid-yard - LEFT
5 = Mid-yard - RIGHT
6 = Mid-yard - CENTER
7 = Near boundary - LEFT
8 = Near boundary - RIGHT
9 = Near boundary - CENTER
3rd and
4th Digits - Special Codes
01 = Non-patch near foundation
02 = Non-patch in mid-yard area
03 = Non-patch near boundary
11 = patch area near foundation
12 = patch area in mid-yard area
13 = patch area near boundary of
21 = patch area outside boundary
FSF Fine Soil Fraction
TSF Total Soil Fraction
C - 37
-------
Quality Control Program
' «/ C7
CLOSE ALL
SET SAFETY OFF
SET talk on
SET STATUS ON
set print oFF
FILEl = 'Quest6*
FILE2='Q666'
USE &FILE1
INDEX ON ID+Q804+Q805+Q806+Q807+Q808+Q809+Q1002 TO SINDEX.IDX
USE
SELECT A
USE &FILE2
SELECT B
USE &FILE1 INDEX SINDEX.IDX
SELECT A
SET RELATION TO ID+Q804+Q805+Q806+Q807+Q808+Q809+Q1002 INTO B
GOTO TOP
END1 = [N]
7FILE2
SCAN
SELECT B
IF EOFQ
SELECT A
*** LIST NEXT 1
? recnoQ
else
select a
ENDIF
ENDSCAN
close all
set print off
* eject
INDEX ON ID+CrTY+FORM+AREA+ADDN+ADD + INT+DTOC(dot)
*Q100A+Q100B+Q200+Q201A+Q201B+DTOC(Q300)
'Q301+Q302+Q303+Q304+Q305+Q306A+Q306B
*Q306C+Q306D+Q306E+Q307A+Q307B+Q307C+Q307D
Q307E+Q308+Q310+Q311+Q312+Q400+Q401
*Q402+Q403-t-CM04+Q405+Q407+Q408-(-Q409
Q410+Q4H+O412+Q413+Q414+Q415
*Q500+Q501+Q502+Q505A+Q505B+Q505C+Q505D
*Q505E+Q505F+Q506A+Q506B+Q506C+Q506D + Q506E
*Q506F+Q600+Q601A+Q601B+Q602A+Q602B+Q602C
'Q603A+Q603B+Q603C+Q604A+Q604B+Q700A
Q700B+Q701+Q800+Q801+Q802-1-Q803
*Q804+Q805+Q806+Q807+Q808+Q809+Q1002
C - 38
-------
SAFETY GUIDELINES
FOR LEAD PAINT
AND
SOIL ABATEMENT CONTRACTORS
-------
-------
SAFETY GUIDELINES
FOR LEAD PAINT STABILIZATION AND SOIL ABATEMENT CONTRACTORS
Health and safety during lead paint stabilization and soil
abatement may be optimized by using the following engineering and
administrative controls.
A. Lead Paint Stabilization Workers
1. Training
Workers who perform paint stabilization shall receive one
day of approved training. Training shall include:
proper techniques of lead paint stabilization, worker
personal hygiene practices, and general safety
precautions. This training shall also include
information on lead hazards and the risk of lead exposure
to their families and to the residents of the
neighborhoods where paint stabilization is in progress.
Specific laws applicable to the lead workers shall be
discussed including the Maryland Occupational Safety and
Health (MOSH) Standard for Occupational Exposure to Lead
in Construction Work, Code of Maryland Regulation (COMAR)
09.12.32 and the Maryland Department of the Environment
(MDE) Occupational, Industrial, and Residential Hazards,
COMAR 26.02.07.
2. Other Personnel
Contractor and MDE personnel who supervise stabilization
and abatement activities shall undergo the same training
and monitoring requirements, and shall adhere to the
rules governing personal protective devices and safety
when engaged in stabilization or abatement activities.
B. Contract Worker 3lood Lead Level Monitoring
Blood lead level monitoring shall be provided by MDE and
results will be provided to the contractor by the Project
Manager. Blood samples shall be taken from stabilization
and abatement workers to determine baseline blood lead
levels (PbB) and free erythrocyte protoporphyrins (FEP)
before commencing stabilization and abatement activities.
Workers whose PbB exceeds 25/ig shall not be allowed to
work while their lead levels remain elevated. Follow-up
blood lead sampling occurs after 30 days and every two
months thereafter while stabilization and abatement
activities are ongoing. At the end of the work, or when
the contractor employee is no longer employed for this
work PbB and FEP is required.
C - 39
-------
If a worker' s PbB reaches 2 0/ig, that worker' s work
practices and hygiene practices shall be reviewed with
the employee to identify pathways of exposure and to
minimize further increases in blood lead levels. A
worker shall not be permitted to continue abating if: one
PbB sampling of 25/ig or three successive PbB samplings of
20^g occurs. If blood lead reaches these levels, then
blood lead level monitoring shall continue every 30 days
until reduction of the blood lead levels is accomplished.
The worker may be returned to the job according to the
requirements of Maryland Occupational Safety and Health
Standard for Occupational Exposure to Lead in
Construction Work.
C. Personal Protection Equipment
-Half face piece air purifying negative pressure
respirator equipped with High Efficiency Particulate Air
(HEPA) filters (lead paint stabilization),
-Disposable work clothing and booties,
-Heavy duty leather or cotton work gloves,
-Protective eye goggles or safety glasses, and
-Heavy soled work boots.
D. Clothing and Equipment Decontamination
1. HEPA vacuuming of disposable work clothing, prior to
removal, will prevent the spread of lead dust. Work
clothing may be rolled down, keeping the outside on the
inside of the bundle for disposal.
2. Water-safe equipment may be rinsed and stored off
site, by the contractor, at the end of each work day.
Hand and face washing stations shall be supplied by the
contractor on site. Liquid soap, disposable towels, and
trash receptacles shall be available.
3. A first aid kit and an emergency eye wash station
shall be available on site. At least one worker on site
shall be trained in first aid.
4. Potable drinking water shall be supplied on site by
the contractor and shall be protected from lead
contamination.
C - 40
-------
E. Dust Control
1. Eating, drinking, smoking, chewing gum, or applying
cosmetics shall not be permitted on site. Workers hands
and face shall be washed each time they leave the work
site.
2. Adequate misting of lead painted surfaces and soil
abatement areas is required to reduce dust levels.
F. Project Participants
Participants shall leave the residence during
stabilization or abatement activities. The MDE/LIS
OutReach Coordinator will arrange for suitable, alternate
facilities during the work day.
Signs shall be erected seven days prior to the
commencement of the work and shall read:
Baltimore Lead in Soil Project
Caution
Work In Progress to Make Your
Neighborhood Lead Safe
Dust may contain lead which is hazardous to health.
WORK TO BEGIN;
G. Project Debris
Lead contaminated debris and excavated soil becomes the
property of the contractor. Non-hazardous soil, based on
the EP toxicity testing, shall be disposed according to
hazardous waste requirements. The contractor shall
remove all debris and excavated soil from the residence
for off site disposal. The excavated soil will be
removed at the end of each work day. During
transportation of the soil, the debris shall be covered
to prevent dust generation.
Reasonable measures shall be taken to prevent process
water and other wet debris from entering the storm water
system.
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PUBLIC RELATIONS PLAN
DEHWMCSTOf TH( rxvMOSMENT
BALTIMORE LEAD IN SOIL PROJECT
ENVIRONMENTAL MARYLAND DEPARTMENT
PROTECTION AGENCY OF THE ENVIRONMENT
June 1988
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TABLE OF CONTENTS
INTRODUCTION AND BACKGROUND I
OVERVIEW OF PROJECT I
PURPOSE OF THE PUBLIC RELATIONS PLAN 2
GEhERAL LEAD AWAREhESS 2
INTEGRATION OF PROJECT SPECFIC PUBLICITY 4
REACHING SPECIAL TARGET GROUPS 5
USE OF MATERIALS AhO MEDIA 6
TIMETABLE FOR YEAR I. 10
STAFFING , II
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INTRODUCTION AND BACKGROUND
The Baltimore Lead in Soil Project is a cooperative agreement involving as
principals the U.S. Environmental Protection Agency (EPA) and the Maryland
Department of Environment (MDE). The project is unusually complex and dependent on
the goodwill and cooperation of a variety of individuals and groups within and outside
government. The proposal as submitted to the oversight pane! appointed by EPA
described many of the agencies and groups which will, through their support and
cooperation, make this project possible. Letters of agreement have also been submitted
from some of the most vital contributors to the project, such as Baltimore City
government.
The success of this cooperative agreement, however, depends not on written
guarantees, but on continuing good relationships between agencies and groups as well as
the maintenance of a positive image for the project in the eyes of the general public, the
academic world, and a variety of special interests including the communities directly
impacted by the project. This image depends not only as what is done, but on how what
is done is presented.
OVERVIEW OF PROJECT
The three year project will be carried out in Baltimore, Maryland to test the
effectiveness of measures to reduce soil lead contamination in the prevention of lead
poisoning.
Two neighborhoods have been identified for inclusion in the project after a review
of demographics, soil lead levels in previous studies and a determination that they are
reasonably accessible and comparable. Baseline blood lead and free erythrocyte
protoporphyrin (FEP?s) will be obtained on children aged less than six years in both
areas. Children will be tested m !ate summer when lead levels are usually highest, and
again in mid-winter when they are lowest. Soil and house dust lead levels will also be
determined at approximately 400 properties in the two neighborhoods.
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Environmental abatement consisting of measures to prevent exposure to lead via
soil, will be carried out in only one of the neighborhoods in the spring of 1989. The study
area for abatement will be decided by a random method after the baseline sampling is
complete. Follow up tests on children will be done at the same times of the year in 1989
for evaluation of post-abatement levels.
If soil lead abatement is found effective, it would also be performed in the control
area and, again, follow-up tests would be done to further validate the first year's
findings.
This project is being carried out by the Maryland Department of the Environment,
in cooperation with Baltimore City and the John F. Kennedy Institute for Handicapped
Children in fulfillment of a cooperative agreement between the State of Maryland and
the Environmental Protection Agency.
PURPOSE OF THE PUBLIC RELATIONS PLAN
The objective of this plan is to create an awareness of lead hazards and of the
benefits of measures which reduce exposure to lead in general, and particularly those
specific activities being undertaken as part of the project.
The plan encompasses both health education aspects and, to a degree, marketing of
the project to the public, especially the population which will directly contribute to the
success of the project. The cooperative nature of this project makes it vital that the
project maintain a high visibility, get good political support, and maintain a high
standards of professionalism. Since health education can be a powerful preventive tool,
it is essential that both neighborhoods be exposed to identical messages with the same
degree of intensity to avoid confounding the results.
GENERAL LEAD AWARENESS
Since is was established in 1985, the Lead Poisoning Prevention Program in the
Maryland Department of Environment has had the goal of reducing lead hazards in a
primary prevention mode rather than continuing the more traditional approach of
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screening and identifying children with lead poisoning and only then correcting the
problem.
In order to achieve this goal, one of the major strategies is to increase public
awareness of lead poisoning and its prevention. This approach not only helps people
protect themselves, but even more importantly it creates a constituency for lead
poisoning victims who in the past tended to be disorganized and poorly represented.
Past activities included distribution of a report entitled "Lead Poisoning:
Strategies for Prevention," preparation and distribution of brochures, pamphlets and use
of a static display at health fairs, county fairs, trade shows, medical conventions, etc.
The display highlights lead exposure sources and includes a doll house painted on one side
with peeling, chipping paint while the other side is well maintained. The "bad" side of
the house also has exposed soil showing paint chips close to the painted wall, while the
"good" side has grass, vegetation and trees.
Lead has been the topic of a large number of presentations to the public, academic
meetings, trade groups, etc. Training-seminars have been held statewide to build
capacity .within local governments to respond to lead related issues. Videotapes have
been made and used by local cable TV companies, and another currently in production is
aimed at training contractors to abate lead paint safely.
Future Plans for General Leod Awareness
All the aforementioned activities will continue with even greater emphasis
particularly on Baltimore City as a target audience. The city not only has the largest
number of at risk and affected children, but it also is the site for the Lead in Soil
Project. At the June, 1988, meeting of the Council on Lead Poisoning Prevention, it was
decided that a request would be made for State funding of additional lead education
efforts in Maryland Department of the Environment (MDE) next year (FY'90). A
brochure specifically designed to accompany the doll house exhibit is being prepared. An
annual Lead Poisoning Prevention Week, held for the first time last May, is described
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under Project Specific Publicity. We plan to create a video and slide library, and expand
our single static display to make it more audience specific for special groups. Lead
poisoning prevention is a major priority area for the department and will continue to
receive a great deal of emphasis and publicity for the period of the project and beyond.
INTEGRATION OF PROJECT SPECFIC PUBLICITY
With the good news of the funding of the Lead in Soil proposal, this Department
began to increase efforts in the public relations and awareness area in order to lay the
groundwork for the project itself.
- At a press conference on January 22 the award was announced. Various federal,
state and local officials, including James Self, EPA Region II! Administrator,
participated in the press briefing. Appropriately, this event was held in
conjunction with a conference on Locol/State/Federal Government cooperation.
Television and newspaper coverage was widespread.
The logo and slogan for the project were selected through an in-house
departmental competition, offering as a prize dinner for two at a downtown hotel
restaurant that was donated by the principal investigator and not charged to the
project. The art work was done later after the selection of the winning ideas.
Included in this packet are two versions of the logo and slogan, one specifically
oriented towards children, and the other for use where a more serious image is
appropriate.
- The Governor declared May 15 to 22 as Lead Poisoning Prevention Week,
creating a forum for a variety of publicity/education efforts. The highlight of
the week was the ceremonial first soil sample for the project on May 19.
Maryland's Lieutenant Governor Melvin A. Steinberg took the sample and again
various public figures including, Mr. Seif, participated. A more complete
description of the event and of other activities of the week are included in
Appendix I. All major events and project specific media contacts are being
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coordinated with EPA Region III and Baltimore City Government. Mjch
emphasis is being placed on the cooperative aspect of the project and its
importance to the State of Maryland.
REACHING SPECIAL TARGET GROUPS
In addition to the general publicity efforts, we plan to promote specific messages
aimed at potential clients in two categories:
I. Families being asked to participate;
2. Property owners being asked to cooperate.
In the first category efforts to reach the target groups were necessarily delayed
until the selection of the neighborhoods was made. However, a great deal of groundwork
has been completed with coalitions of community organizations, church groups, and
political leaders in Baltimore who have been deeply involved in Lead Poisoning
Prevention week. Interactions with the actual neighborhood groups is now being
escalated and an additional component, staff training in community relations, will assure
that the project retains its positive image in the community.
Staff Interaction with the Public
In order to create goodwill for the project, all field and other staff are being
instructed as part of their training to interact in a professional, friendly, and positive
way with members of the community. They have been given sufficient general
information on lead to be able to discuss it, answer questions, and make referrals for
non-lead related problems such as housing, social, and economic issues and, above all, to
be good listeners. Field staff will wear T-shirts with the logo of ;the project in warm
weather and jackets with the logo in inclement weather. They will, thus, be easily
recognized as part of the project. They will also wear State I.D. cards.
Community Meetings:
These will be a prime methodology for enrolling participants. Parents who indicate
interest will provide their names, addresses, and The names of children to be screened.
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They will be placed on a mailing list and be sent appointment cards as reminders when
the clinics start biological monitoring. Meetings will, where possible, be held with
sponsorship by community organizations and church groups.
Community Leaders Meetings;
These will be used to orient community leaders and enlist support for the project.
Community leaders will be approached individually, if necessary. However, coalition
groups will be targeted for presentations whenever possible.
USE OF MATERIALS AND MEDIA
Materials will be used to inform families in the neighborhoods about the study and
to announce community meetings. An additional static display will be developed, as well
as brochures on the project (one for general use, the other for property owners). T Shirts
with the project logo will be worn by field staff and child-size versions will be issued to
children who have blood tests performed at the clinics. Children will also receive
stickers with the logo and pins (depending on age and the mothers' wishes). Additional
incentives to encourage participation will be requested from corporate and non-profit
sponsors who will be asked to provide samples of child care and cleaning products,
coupons, etc.
Any costs incurred by participants for project-related expenses will be
reimbursed. These might include water bills increased following abatement, as we may
need to access homeowners water supplies. Even during the first year, it may be
necessary to Water down areas for sampling to avoid loss of the vital top 2cm of the
sample* Dust control and care of sodded areas wilt, however, be the major areas of
impact on water bills.
Incentives for study subjects need to provide immediate benefit at the time of
screening, and a major benefit at time of completion of the protocol. Incentives will be
selected based on the particular needs of the individual family and will be chosen to
avoid interference with social security or welfare benefits, while being aimed at
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achieving better health and quality of life. Where possible, the incentives will aim at
reducing long term risk of lead exposure or improving health and nutritional status. In
addition, we will aim at decreasing mobility and promoting a sense of pride in the
community.
At the completion of the program, major incentives will be given to families which
have participated m every serening for which they ore eligible. In other words, those
families which did not drop out of the project.
Property Owners;
While it is important to enroll neighborhood residents in the biological sampling, it
is equally important to gain the cooperation of the property owners in order to assure
access to properties for soil sampling and abatement. We anticipate varied success in
this endeavor since the project may be viewed with some suspicion by some property
owners. Cooperation in owner-occupied housing is likely to be higher than rental;
however, the inclusion of rental properties in varying states of repair will be very
important, since rental properties tend to have poorly maintained yards, more soil, and a
higher population of young family occupancy.
To lay the groundwork for building good relationships, we intend to work through
the Property Owners Association of Greater Baltimore, which has been extensively
involved in the Governor's Council on Lead Poisoning prevention and has advocated that
increased educational efforts be added to abatement efforts, so that abatements done by
property owners are not rendered futile by either inadequate housekeeping by tenants or
tracking of lead from neighboring properties. Since the focus of this project is on a
neighborhood based approach, it should be consistent with their views. Some of their
members are very much opposed to "door-to-door" screening or testing of properties
since tenants can place rent in escrow if lead paint is identified on the property, while
the finding of elevated blood levels in a tenant usually requires that an abatement be
done.
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Because of the publicity given to the problem of lead poisoning in Baltimore in the
past few years, many property owners are interested in testing and abating their
properties in a preventive mode or, at least, paying greater attention to the maintenance
of high risk properties. Testing services are available from private companies for a fee
which generally is about $150 per house. They are also available through a non-profit
housing aid organization for low income families on a limited basis. The Baltimore City
Health Department reserves testing services for the follow-up of children with elevated
blood lead levels. As an incentive to assisting with this project, we can offer lead paint
testing services for the exterior of dwellings and, on a limited basis, internal spurfaces.
In addition, the assurance that flaking, peeling, or chalking lead paint on exterior
surfaces would be stabilized by scraping, replacing essential wood trim if deteriorated,
and re-painting will be a considerable benefit, especially if an entire block or more can
be done together. Additionally, there will be a 50% chance of being included in the lead
abatement area, which may mean landscape improvements, paving, and fence
replacement as needed. The benefits of participation will be outlined in meetings with
the Association, and a segment will be submitted for inclusion in their newsletter,
"Proper Ties," which goes to all of their members. A mailing will also go to candidate
property owners in the neighborhoods chosen for inclusion to enlist their cooperation and
inform them about the project. A special meeting will be arranged for input and
questions from property owners. Each participating owner will be contacted several
times by project staff to ensure continuing goodwill and legality of all aspects of actions
affecting property.
Political Leaders and Others in Leadership Roles:
A determination has been made as to the names of all political leaders representing
these neighborhoods and additional public figures who reside there. These, along with
church leaders and organization leaders, will be kept informed and asked for support for
the project. Community meetings will, when possible, be called by local leaders or held
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in cooperation with them. In accordance with Department policy, reports will be filed on
oil contacts with elected officials by individuals. The Office of Governmental Relations
will assist in coordinating this aspect as they have already done for the media events
referenced in other sections of this report.
In addition to local political support, we intend to fully avail the excellent support
we have had from the Maryland Congressional Delegation, the Mayor of Baltimore, and
several State Delegates and Senators along with members of the Baltimore City Council
for other areas of Baltimore who welcome the focus this project brings to a city-wide
problem. Below is a list of elected officials invited to the ceremony.
U.S. Senator Paul S. Sarbanes
U.S. Senator Barbara A. Mikulski
Congressman Benjamin Cardin
Congressman Kweisi Mfume
Baltimore Mayor Kurt L. Schmoke
State Senator Julian Lapides
State Delegate Samuel Rosenberg
State Delegate Curtis Anderson
State Delegate Anne S. Anderson
State Delegate Kenneth Montague
State Delegate Howard P. Rowlings
State Delegate John S. Arnick
State Delegate Margaret H. Murphy
City Councilman Jody T. Landers
City Councilman Martin E. Curran
City Councilman Wilber Cunningham
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TIMETABLE - YEAR 1
APRIL 88 - APRIL 89
Pre-Project: Media Announcement Regarding Project Funding. Press Conference, January 22 with press release. Present: Mr. Self,
EPA Region Ml; Secretary Walsh, MDE; Senator Sarbanes and others.
APRIL
Day Care Center
Poster Contest
NOV
Community
Meetings
MAY
Lead
Awareness
Week
DEC
Fliers,
Community
Meetings
JUNE
Governors
Reception
Annual report on
Lead Program to
Governor
JAN
Presentations to
medical providers
JULY
Fliers,
Community
meetings
Property
owners, etc.
FEB
Property
owners
meetings
RE: Abatement
AUGUST
Medical
Awareness
efforts
Possible press
release on
first clinic
MARCH
- Press release
RE: Selection
of area for
abatement
SEPT
Community
meetings
Contractor
Awareness
efforts
APRIL
Day Care
Center
Poster
Contest
OCTOBER
Community
meetings
Contractor
Awareness
efforts
MAY
Lead Awareness
Week
- Community
meetings
Fliers
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STAFFING
Most of the activities described will be conducted by in-house staff of MDE and
specific project staff. It is essential, however, that at least a part-time position be
relegated to the coordination of this plan. We propose to hire a part-time (50%) public
relations coordinator for an Administrative Officer who would start in August, 1988 and
work for ten (10) months of the year. We are not requesting additional funding for this
purpose which requires only a minor amendment to the budget. Since the individual
selected is also a Community Health Nurse, this would obviate the need to hire and train
nurses for the periods of biological sampling to assist the clinical coordinator. This
would also reduce the problem of turnover and inexperience and assure continuity. The
resume of the selected candidate is attached (Appendix II).
Other sources include: Charles Walker, Public Relations Director, MDE; Ray
Feldman, Deputy Public Affairs Director, MDE; Sill Palm, Health Educator, Center for
Environmental Health, MDE; and Rebecca Burner, Director, Governmental Relations,
MDE.
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APPENDIX I
Lead Poisoning Prevention Week (May 15-21, 1988) was organized for the first time
in 1988. The majority of activities were centered this year in the Baltimore area, but
promotional efforts took place across the state. The purpose of this week was to
organize educational and awareness activities on the continued dangers of lead in our
environment, and the importance of prevention. The ultimate goal of activities such as
these is to help eliminate all but sporadic cases of lead poisoning in Maryland by the year
2000.
The original plans involved a very broad, multi-media, educational/awareness
approach. Many excellent ideas were actualized because of insufficient time and
resources. The plan that was put into place had three major components:
I. Production of a high visibility, positive media event to focus attention on the
Baltimore Lead in Soil Project.
2. Development of a state-wide poster contest for day care children to focus in a
positive way on prevention, target a key at-risk group, and give state-wide visibility
to the Baltimore Lead in Soil Project and the general Leqd Program.
3. Improvement of working "relationships with local health departments state-wide.
Following a request from the Governor's Advisory Council on Lead, Governor
Schaefer proclaimed May 15-21, 1988 as Lead Poisoning Prevention Week. An Official
proclamation was received by the Center for Environmental Health in late March.
Subsequent to this, organizing for Lead Poisoning Prevention Week (LPPW) took place in
al I three areas of the plan.
1. MEDIA EVENT
Intense planning and organizing began in March. The program staff decided
that an appropriate media event would be the taking of the first soil sample on the
EPA Grant by the Governor or Lieutenant Governor. Lt. Governor Melvin A.
Steinberg agreed to participate in the "Firsf Soil Sample," and Governor William
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Donald Schaefer agreed to host the winners of the day care poster contest in a
ceremony at the Statehouse in Annapolis. As the neighborhoods for the study had
not yet been chosen, community groups in Baltimore were contacted about locations
that could be used for this event. St. Ambrose Housing Aid Society volunteered a
property in the Govans neighborhood that had been recently abated for lead, and was
vacant. A date was set (May 19), and formal invitations were mailed to federal,
state, and local politicians, EPA officials, community groups and individuals who had
been involved with the issue of lead or the EPA grant. Because of the threat of
inclement weather during this period, provisions were made in advance to
accommodate the possibility of rain. Weather immediately prior to and following
the scheduled event was rainy, necessitating thai additional measures be taken: a
tent, chairs and outdoor carpeting. Catering was arranged. Balloons in the
Maryland State Colors were displayed on the house and in the tent. Inside the house,
a display of the Old House Dollhouse highlighting lead hazards, literature from MDE
and posters related to the grant and to lead paint abatement were displayed.
Approximately two dozen colorful entries received in the Lead Busters Poster
Contest were also on view. In addition, an information sheet was prepared about the
abatement done by St. Ambrose Housing Aid and these abatements were showcased
in a tour of the home following the groundbreaking ceremonies. More than thirty
(30) media packets were prepared for media and the political delegation. In
addition, a six page program was prepared for attendees and name tags, lead buster
stickers and buttons were distributed to those in attendance. Lt Governor Steinberg
EPA Regional Administrator James Seif, and Maryland Department of the
Environment Secretary Martin W. Walsh took the first soil sample under the
direction of project manager, Reginald Harris, and the principal investigator, Dr.
Katherine Parrel 1. A team effort, involving 5 of the 9 members of 9 of the Lead
Program Staff and other key MDE staff members, was responsible for the resounding
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success of this event. Dr. Julian Chisotm received a citation from Governor
Schaefer, lauding his contributions to the State of Maryland for 40 years of
leadership and commitment to the prevention and treatment of childhood lead
poisoning.
Feedback received outside and inside of MDE indicated that the event clearly
was a success. Participation was high (estimated 100 people participated) and
enthusiasim and interest was generated among those in attendance. This event gave
us the opportunity to "kickof f" the lead in soil project and increase awareness of the
project and related issues. Media coverage of the event itself included all three
local T.V. stations, Maryland Public Television, and one popular Baltimore radio
station. The event was also successful in bringing a high level of visibility for the
project among those persons and organizations in Maryland with the greatest
interest in this problem. It generated a positive image, and developed networks that
will be essential in the success of the project.
(2) STATEWIDE DAY CARE POSTER CONTEST
The Lead Busters Poster Contest for Day Care Children was organized to
target young families with children under the age of seven, the age group most
vulnerable to lead poisoning. Day care families often have other young children not
in organized centers. Day care centers are well-organized and able to respond
quickly to requests, such as this poster contest. Staff felt that sponsoring a poster
contest would help to accentuate prevention strategies in a positive way and provide
increased visibility for the Department's Lead Poisoning Prevention Program and the
Lead in Soil Project. The "Lead Busters Logo, chosen in an internal MDE contest on
March 31, 1988 was established as a symbol of the Lead-in-Soil Project because of
it's attractiveness to the under-six age group.
Two age groups (3 and 4 year olds, and 5 and 6 year olds) and three categories
for poster submission (Lead Safe Housing and Soil; Good Nutrition; and Handwashing)
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were established. A letter to day care center directors, flyers about the contest,
labels for posters and a brochure about Lead Poisoning Prevention were sent to all
licensed day care centers in the State of Maryland. Key personnel in local
jurisdictions were also sent cover letters and copies of the pocket. In addition, the
Lead Program participated m Boby Fes1, April 29-30 and May I, with our Old House
Dollhouse exhibit, display and contest flyers. Contest materials were also
distributed at a meeting of the Maryland Child Care Association. Prizes were
contributed by the National Aquarium, Maryland Science Center, Baltimore Zoo,
Baltimore Orioles, a local McDonalds franchise and an educational supply store,
minimizing the prizes that had to be purchased for the contest. Judges were
recruited from the Baltimore Museum of Art, Maternal and Child Health Day Care
Licensing Unit of DHMH, and internally within MDE.
Participation in the contest was good: two hundred thirty-five (235) entries
were submitted by children in nineteen day care centers from across the state.
Centers from nine local jurisdictions were represented. Nineteen winners were
selected, and attended a ceremony in.the State House in Annapolis where they were
presented with citations by Governor Schaefer on June 22, 1988. The prize-winning
posters were featured in a display in the lobby of 20! W. Preston Street May 23-3!,
and will be displayed throughout the State during the next 6-9 months.
The Lead Poisoning Prevention Program feels that this effort was very
successful in reaching one of our target audiences and in increasing positive state-
wide visibility for the Lead in Soil Project, the Lead Program and MDE We
anticipate repeating this next year. Plans include and earlier start on publicity so
we will have access to newsletters and day care organizations and provider networks
and an attempt to makec sponsors to increase the value of prizes.
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(3) IMPROVEMENT OF WORKING RELATIONSHIPS WITH LOCAL HEALTH
One oif the priorities of the Marylond Department of the Environment has
been its efforts to strengthen State/local ties. Through a positive education and
awareness campaign and good communication with local health, the Lead Program
hoped to encourage local initiatives and consolidate the state-local health working
relationships. Three mailings were made to all local health departments. The first
on April 18, containing information about Lead Poisoning Prevention Week and a
copy of the Governor's Proclamation. The second one on May 10, contained sample
stories about lead to be used with local media contacts. The third on June 6,
included follow-up information about the Lead Busters Poster Contest Winners. In
addition, Dr. Parrel! addressed the Health Officers and distributed Lead Poisoning
Prevention Week resource packets at the Health Officers Round Table meeting on
May 4, 1988. Copies of mailings to health officers were also sent to Nursing
Directors, Environmental Health Directors, Health Educators and Day Care
Coordinators in the local jurisdictions. Calls were placed to all local health
educators and several requests for additional literature were filled.
The week of lead awareness events showcased not only the Lead in Soil Project
but the contributions of local health departments. Baltimore City Health
Department organized an event May 16 to kickoff Lead Poisoning Prevention Week
and publicized their new pamphlet: "A Health Pregnancy - Things You Should Know
About Lead", written and produced specifically for this week. Heart shaped large red
balloons were displayed and distributed to all city clinics. In addition, Baltimore
City Health Department sent out a mailing to all obstetricians and nurse midwives in
Baltimore about prevention of lead exposure during pregnancy, including a copy of
the new pamphlet. This is the first pamphlet we have seen that focuses on positive
prevention of exposure during pregnancy. Follow-up calls to other counties across
the state identified seven additional local health departments that were
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participating in Lead Poisoning Prevention Week by working with news media and
providing Lead Poisoning Prevention literature at their clinics. They were Caroline,
Charles, Garrett, Prince George's, Montgomery, Howard, and Baltimore Counties.
News articles appeared in many local papers.
In Baltimore, a number of community organizations also rose to the occasion
and organized activities during this week. A coalition of groups including Parents
Against Lead, St. Ambrose Housing Aid Society, Middle East Community
Organization, South East Community Organization and the Kennedy Institute
organized a Lead Awareness Day for May 20. Literature was distributed throughout
a neighborhood in the Middle East Community and 52 kindergarten children at School
135 were screened for lead by a nurse from Kennedy Institute. Staff from Kennedy
Institute collaborated with two staff members from the Lead Program to produce a
new videotape about lead poisoning prevention, which enjoyed it's premier showing in
the Wednesday lead clinic at Kennedy Institute on May 18. A tour of rental
properties in Baltimore was hosted by the Property Owners Association of Greater
Baltimore for the Lead Council on May 17. The tour helped to highlight some of the
problems and issues associated with lead paint abatements in the City of
Baltimore. A presentation was made by one of our program staff to the Science
Council of Baltimore City Schools, A physician at University of Maryland
organized a meeting between occupational ly lead-exposed workers and the
Commissioner of Labor and industry to hear the worker's perspective and to review
progress the workers had made in compiling an informational pamphlet about
prevention of occupational lead exposure in radiation shops. The response from
community groups was quite enthusiastic. Most individuals and organizations
indicated a willingness to do this again next year and to spend more time planning
and organizating efforts.
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Appendix D
Consent Forms
Participant Informed Consent
Property Owners Consent
PAGE
,D-1
,D-6
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STATE OF MARYLAND
DEPARTMENT OF THE ENVIRONMENT
2500 Broening Highway Baltimore, Maryland 21224
(301)631-
William Donald Schaefer Rol*rt Perciasepe
Governor Secretary
INFORMED CONSENT INFORMATION SHEET
This study will be done to find out whether lead from soil
endangers children and whether we can protect them from lead
poisoning by covering, removing or mixing the soil
Lead in soil comes from old paint and from the use of leaded
gasoline. usually lead stays on the surface of soil and it can
poison children who play around it and get their hands or toys
dirty. It is also carried indoors on people's shoes where it
becomes part of house dust. Children absorb lead during their
normal activities when lead dust and dirt is carried on their
hands, toys, or pacifiers to their mouths. Frequent washing helps,
but if there is a lot of lead in the environment it is hard for
parents to protect children from it. Some children eat paint chips
or soil, or gnaw on painted surfaces. These children can develop
lead poisoning very fast. Lead can damage the growing child' s
brain and it interferes with the making of red blood cells. It
can also damage the kidneys and other organs. Lead causes
behavior, hearing, growth, and learning problems and can cause
seizures or even death. The effects on the brain can be permanent.
Lead also is dangerous to unborn children. If the lead in the
mother's blood is high, it can reach the baby and may cause
miscarriages, stillbirths, early labor, premature delivery, and low
birth weight. Babies whose mothers had high lead levels are slower
to learn and develop.
In this study, children under age six years and pregnant women
will be tested in two neighborhoods of the City. Tests will be
done at the end of summer when lead levels are usually at their
highest and again in winter when they are usually lower. Soil and
dust will be tested for lead also.
After these tests, soil from one of the neighborhoods will be
removed, covered or turned over so that the lead level at the
surface will be low wherever it was found high on the test. This
will be done in spring. Tests will be done on the children after
the soil removal to find out whether their lead levels have gone
down. Tests will again be done in September and mid winter to see
if there is a delayed effect of removing this source of lead.
If the soil removal helps to prevent lead poisoning, it will
be done in the control neighborhoods too. The reason for using
two neighborhoods is to compare the one where soil was cleaned up
with the one where it was not. If you have lead paint in your home
-------
we will advise as to how this can be managed. The soil study uses
Environmental Protection Agency (EPA) federal funds and does not
include correction of indoor paint hazards. However, there are
state funds available for this which property owners can obtain
from the Department of Economic and Community Development. Paint
removal can be dangerous and must be done using safe practices. If
you would like information on paint removal or the methods of
cleaning that will make your home lead safe, this will be available
from the staff conducting the study.
i
The testing will include blood lead and FEP tests. The FEP
test looks for the effects of lead in blood and it helps find
children with iron poor blood. If you or your doctor want other
tests done such as sickle cell, the blood can be drawn at the same
time. Anyone found to have high lead levels or low iron in their
blood will be referred for medical follow-up. If the blood lead is
high, the city will inspect the home for lead.
The blood sampling will involve taking blood from a vein in
the arm or, in the case of the infants, from the heel. There will
be some discomfort, but no danger involved in this procedure. Some
individuals may have some bruising around the arm vein due to
leaking of blood from the vein. This can be kept to minimum by
pressing on the vein for a minute or so after the needlestick. If
brusing occurs, it usually lasts only for a day or two and has no
permanent effects.
A questionnaire will be filled out on each participant in the
study to get some background information. This will take about 15
minutes. These will be no sensitive or embarrassing questions, but
if you wish you may refuse to answer any questions that worry you.
The information will be kept confidential and will not be shared
with landlords, neighbors or anyone else without your express
permission. If you want test results sent to your doctor a release
form must be signed.
Each child's hands will be wiped with a non-allergenic cloth
to determine the amount of lead on the child's skin at the time of
the study. There will be no danger or discomfort involved in this
procedure.
Transportation will be provided free to and from the testing
place. All participation is voluntary and you may drop out of the
study at any time. In addition to the health benefits of the
study, there will be an incentive scheme with rewards for
participation and a major prize for those who complete the whole
program.
After the project, all soil that has been turned or removed
will have sod or seed replacement and the lots will be attractively
landscaped. Any trash will be hauled away. If there is old,
peeling paint on the outside, this will be fixed and repainted.
D - 2
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Any fences or gates will be repaired if the need arises and the
house will be rat proofed. The neighborhoods participating will
also get priority for city neighborhood improvement programs such
as parks, trees, and playgrounds.
The outcome wi 11 be a safer, healthier and more pleas ant
environment for families in the study and control areas.
We hope you will participate. If you have any questions,
please call the Soil Lead Abatement Demonstration Project at 333-
7471 or ask any of the study staff.
Consent Agreement
I have read or had explained to me the information above and
I understand what it means for me and my child (ren).
Signed: .__
Date:
Witness:
Date:
D - 3
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Consent Form for Children
I give permis s ion for to
participate in the lead poisoning study of the Maryland Department
of the Environment and Baltimore City Health Department. The study
is being done to find out whether lead in soil can endanger
children and whether removing or covering soil can protect them
from lead poisoning.
/
I understand that the following actions are planned in this
project which will need my consent:
1. Medical and social information will be recorded concerning my
child and the family.
2. Samples of blood will be taken from my child for laboratory
tests.
3. Samples will be taken on several occasions according to the
timetable attached.
4. If my child is found to have too much lead or too little iron
in the blood, I will be advised and referred for proper
medical management.
I understand that these actions will be performed by
representatives of the Maryland Department of the Environment or
the Baltimore City Health Department. I have been provided with
information about the study and have had a chance to ask questions
about it. All information concerning my child and the family will
be kept confidential.
Witness Signature of parent/guardian
Relationship to child
DateDate
D - 4
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OPTIONAL
I would like results of blood samples sent to my child's
doctor or clinic. I authorize release of this confidential
information to:
Physician or Clinic's Name Address
Signature of parent/guardian Date
Timetable for Children's Blood Samples
Sample 1 Late Summer/Early Fall Year 1
Sample 2 Mid Winter Tear 1
Sample 3 Late Summer/Early Fall Year 2
Sample 4 Mid Winter Year 2
Sample 5 Late Summer/Early Fall Year 3
Sample 6 Mid Winter Year 3
Children must be aged less than six years at the time they enter
the study will not have further sampling. the family must have
lived in the area for at least three months.
D - 5
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STATE OF MARYLAND
DEPARTMENT OF THE ENVIRONMENT
2500 Broening Highway Baltimore, Maryland 21224
(301) 631-
Waiiam Donald Schaefer Robert Perciasepe
Governor Secretary
PROPERTY OWNER'S CONSENT AGREEMENT
PROGRAH DESCRIPTION
The Soil Lead Abatement Demonstration Project (* Program*) is
a three-year study of the effectiveness of lead contaminated soil
removal or abatement in the reduction or abatement in the reduction
of lead exposure in children. This study is being conducted in the
Park Heights and Walbrook Junction/Rosemont communities.
Evaluations will monitor the level of lead in dust, soil, exterior
paint and water as well as children's blood. Treatments such as
paint stabilization, landscaping and encapsulation of soil may be
instituted, where deemed appropriate, as a means of abating lead.
CONSENT AGREEMENT
The Maryland Department of the Environment (*MDE*) and the
undersigned property owner (*Owner*) hereby agree to the following
terms as conditions governing participation int the Program
described above:
1. MDE will be granted access to houses, apartments and
all surrounding property during regular business hours throughout
the course of this study.
2. the Owner will identify a person who may be
contacted by MDE who will have authority to discuss landscaping and
painting options. The name, address and phone number of that
person is as follows:
3. Upon request, an Owner may receive information
concerning the results of MDE's study or environmental test results
of his/her property. However, an Owner may not receive results of
obtained by virtue of this study.
4. In the event that exterior paint is cracking
chipping or peeling and contains lead, MDE may undertake a lead
paint stabilization project in order to stabilize and reduce
exterior lead levels. This will consist of surface preparation and
re-painting.
5. In the event that surface soil lead contamination
exceeds 500 parts per million, MDE may perform and finance a
-------
5. In the event that surface soil lead contamination
exceeds 500 parts per million, MDE may perform and finance a
landscaping project to reduce lead levels in soil Appropriate
sites for such treatment shall be selected based upon the level of
contamination of the soil, its accessibility to children and
factors pertinent to the environmental objectives of the project.
6. MDE will employ only licensed and bonded contractors
in the performance of all lead abatements, stabilizations,
landscaping, and encapsulation projects. The names of the
contractor, his/her license number, bonding and insurance
information will be provided to the owner.
r
7. MDE will consult with the owner or his/her designee
concerning the terms of all stabilization, landscaping and
encapsulation contract contracts. MDE will use reasonable efforts
to accommodate desires of the owner concerning the color of paint
to be used on exterior surfaces and landscaping options.
8. MDE reserves the right to remove a property from
participation in this study in the event that: (1) an occupant
refuses or fails for any reason to participate in the bi-annual
blood lead screening program and/or (2) MDE is denied access to a
property.
Having read, understood and agreed to the terms and conditions
stated herein, we the undersigned hereby agree that the
property (ies) identified below will participate in the Soil Lead
Abatement Demonstration Project described herein and that the Owner
will employ good faith efforts to ensure the success of the
project.
D - 7
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ADDRESS OF PARTICIPATING PROPERTY
DATE
SIGNATURE OF OWNER
DATE
Approved as to form and legal
sufficiency on this 16th day
of ,19
Merrill Brophy
Project .Manager
Soil Lead Abatement
Maryland Department of the
Environment
2500 Broening Highway
Baltimore, Maryland 21224
Neil F. Quinter
Assistant Attorney General
Maryland Department of the Environment
2500 Broening Highway
Baltimore, Maryland 21224
D - 8
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Appendix E
Questionnaires
PAGE
Administration-1 E-1
Followup Questionnaire E-17
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MARYLAND DEPARTMENT OF THE ENVIRONMENT
TOXICS OPERATIONS PROGRAM
Lead in Soil Abatement Demonstration Project
Administration - 1
Field Supervisors Complete items 1 through 6 before giving
questionnaire to interviewer.
1. City code.
2. Form number
3. Address.
Street Code
Study Area
House No.
4. Child ID.
5. Child's full name.
6. Interviewer ID.
Interviewer: Start completing questionnaire at item 7.
7. Date of interview.
Month Day Year
8^ Starting time of interview, : AM
PM
E - 1
-------
Year
Child Code
Form Number
Introduction
Thank you for agreeing to participate in this project.
100 A. Are you the parent or guardian of
1. Yes
2. No
B. relationship to child_
C. Do you know how spends (his/her) time?
1. Yes
2. No.... (Ask to talk to the parent or guardian who
can best talk about how the child spends (his/Her)
time. If that person is not available,
reschedule the appointment and end here.)
101. What is your name?
First Last
102. How long has been living at this address?
Years and Months
(If three months or less, stop the interview.)
103. Do you plan to move in the next three months? (If yes, ask
where to and get change of address.)
1. Yes
2. No
3. Unknown
104. Usual source of health care
105. Physician or clinic name:
106. Physician's phone number ( )
E - 2
-------
Census
200. What is the total number of persons aged 18 or over living in
this household?
persons
201. A. What is the total number of persons less than 18 years old
living in this household? Be sure to include all young
children and infants.
persons
B. How many of these are under six years old?
children under six years of age.
E - 3
-------
First I am going to ask you a couple of questions
about . (Do each child in the family in a
separate interview.) Then I will ask you questions about places
(he/she) spends time.
300. A. What is 's date of birth?
Month Day Year
B. How old is today?
_Years Months
301. What is . race?
1. Black
2. White
3. Asian
4. Hispanic
5. Other
302. What is 's sex?
1. Male
2. Female
Now I would like to ask how spent (his/her) daytime
hours during a typical day. (Interviewer - a typical day is
defined as "an average day in the last week")
303. About how many hours per day does play
outdoors? (Code 99 for unknown)
hours outdoors (if 0 or unknown go to questions 310)
304. On a typical day, where does spend most of
(his/her) time outside?
1. Around your home
2. Around a baby sitter's, friend's, or relatives's home
3. Around a day care center or school
4. At a public park or playground
8. At some other location (Specify)
9. Unknown
305. About how many hours did (he/she) play outside around
(his/her) home? (Code 99 for unknown)
hours outdoors around home (If 0 or unknown go to
question 310)
E - 4
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306. Where does
Year
Child code
Form number
_usually play outdoors around
(his/her) home?
1 Back yard
2 Side yard
3 Front yard
4 Street
5. Alley
8 Other (Specify)
9 Unknown
307. Is the ground where (he/she) plays grassy, concrete, asphalt,
plain dirt or soil, a sandbox, or some other surfaces?
1 Grassy
2 Concrete or asphalt
3 Dirt or soil
4 Sandbox
5 Painted porch or deck
8 Other (Specify)_
9 Unknown
308. Did
often take some food or a bottle with
(him/her) when (he/she) played outside?
1 Yes
2 No
9 Unknown
310. On a typical day, about how many hours does
indoors at home? (Code 99 for unknown)
hours per day
311. On a typical day, about how many hours does
play indoors away from home? (Code 99 for unknown)
hours per day
312. On a typical day, about how many hours does
play
spend sleeping? (Include naps and night time sleeping.
99 for unknown)
hours per day
Code
E - 5
-------
Year
Child code
Form number
400. Does
Mouthing Behavior
use a pacifier?
1 Yes
2 No
3 Unknown
401. How often does
(his/her) mouth?
put (his/her) fingers in
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
402. Many children put toys and things that are not food into their
mouths. Would you say that does this a lot,
once in a while, or almost never?
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
403. Many children cut their teeth on hard surfaces. How often
have you seen put (his/her) mouth on a window
sill?
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
404. Have you ever seen
mouth?
put paint chips into (his/her)
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
405. Have you ever seen
eat dirt or sand?
1 Yes
2 No
9 Unknown
E - 6
-------
Year
Child code
Form number
406. Are there any things that we have not mentioned that you have
seen put in (his/her) mouth? (List all
mentioned.)
Now I would like to ask you about 's diet.
407. What is the main type of milk that (he/she) drinks?
1 Breast milk
2 Cow's milk
3 Formula
4 Canned (condensed) milk
8 Other (Specify)
9 Unknown
408. Does take Feosol, Poly Vi Sol with Iron
supplement?
1 Yes
2 No
3 Formula with iron
9 Unknown
409. Does (he/she) drink fruit juices everyday? (If yes, verify
that juice is real juice.)
1 Yes
2 NO
9 Unknown
410. Does (he/she) eat any table food (adult food)?
1 Yes
2 No (Go to question 413)
9 Unknown (Go to question 413)
411. Does (he/she) eat any vegetables from your garden or any other
garden in your neighborhood?
1 Yes
2 No
9 Unknown
E - 7
-------
Year
Child code
Form number
412. If
eats table food, does (he/she) use
fingers?
1 Yes
2 No
9 Unknown
413. Is the family's food or drinks ever served or stored in home-
made or imported clay pottery?
1 Yes
2 No
9 Unknown
414. Is any of the family's food stored in the original cans after
being opened, for example, canned fruit juice?
1 Yes
2 No
9 Unknown
415. On any given day, how many glasses or bottles of water
(excluding canned or bottled juices and soft drinks, but
including drinks mixed with tap water) does
drink?
glasses or bottles of water
E -
-------
Year
Child code
Form number
Pets
500. Do you have any dogs or cats?
1 No dogs or cats (Go to question 505)
2 Dog(s) only
3 Cat(s) only
4 At least one dog and cat
9 Unknown (Go to question 505)
501. Does the dog stay inside, stay outside or go in and out of the
house?
1 Inside most of the time
2 Outside most of the time
3 In and out all of the time
8 Not applicable - no dog in house
9 Unknown
502. Does the cat stay inside, stay outside, or go in and out of
the house?
1 Inside most of the time
2 Outside most of the time
3 In and out all of the time
8 Not applicable - no cat in house
9 Unknown
Lead Work or Hobbies
505. Does anyone who lives in this household work in any of the
following jobs?
a. Lead Working h
b. Metal foundry i
c. Oil refining j
d. Painting k
e. Demolition ; 1
f. Welding m
g. Chemical processing n
Plumbing
Sandblasting
Autobody working
Road stripe painting
Metal recycling
Radiator shop
Other lead processing
(Code "Yes" if respondent chooses any of the above jobs.)
1 Yes
2 No
E - 9
-------
9 Unknown
Year
Child Code
Form number
506. I would like to ask about hobbies or other work that may have
been done in this household. In the last three months, has
anyone who lives here done any of the following activities at
home?
a. Painted pictures with artists' paint.
b. Removed paint from parts of the house or furniture in
the house.
c. Painted bicycles or cars.
d. Worked with stained glass.
e. Cast lead into fishing sinkers, bullets or anything
else.
f. Soldered electronic parts.
g. Soldered pipes.
h. Made pottery.
(Code "Yes" if respondent chooses any of the above
activities.)
1 Yes
2 No
9 Unknown
E - 10
-------
Year
Child code
Form number
Health
The next few questions are about 's health.
600 A. Does have any medical or developmental
problems that you know of?
1 Yes (specify below)
2 No (Go to question 601)
9 Unknown (Go to question 601)
B. If yes, list and date:
601. A. Has ; been tested for sickle cell?
1 Yes
2 No (Go to question 602)
3 Unknown...(Go to question 602)
B. If yes, what were the results?
1 Negative
2 Sickle cell trait
3 Sickle cell disease
4 Unknown
602. A. Has ever had anemia or low blood?
1 Yes
2 No (Go to question 603)
9 Unknown (Go to question 603)
B. If yes, what year was ; diagnosed
as anemic ?
C. If yes, is (he/she) presently being treated?
1 Yes
2 No
9 Unknown
E - 11
-------
Year
Child Code
Form number
603. A. Has ever been screened for lead before?
1 Yes
2 No....(Go to question 700)
9 Unknown (Go to question 700)
B. If yes, list year
C. If yes, what were the results?
1 Normal
2 High
9 Unknown
604. A. Has ever received medical care for lead
poisoning?
1 Yes (Go on to 700)
2 No (Go on to 700)
9 Unknown
B. If yes, was this medical care:
1 Outpatient
2 Inpatient
9 Unknown
E - 12
-------
Year
Child code
Form number
Housing Characteristics
700 A. Was your house built before World War II?
1 Yes
2 No
9 Unknown (Go to question 701)
B. What year was it built?
(If unknown, enter 9999)
701. Have you or has anyone else removed paint or sanded any
painted part of your house in the last three months?
1 Yes
2 No
9 Unknown
702. Have you or anyone else ever removed paint or sanded any part
of your house?
1 Yes
2 No
9 Unknown
E - 13
-------
Year
Child code
Form Number
Demographics
800. Do you own or rent your home?
1 Rent
2 Own
3 Staying in home for free
9 Unknown
801. What is your marital status?
1 Married
2 Divorced
3 Separated
5 Widowed
5 Single
802. A. Which of the following groups best describes your
occupational status? (Read the following choices.)
1 Unemployed..(Go to question 803)
2 Homemaker...(Go to question 803)
3 Employed part time
4 Employed full time
B. What is your occupation?
803. What is the highest grade or year of school that you finished?
Grade or year (Code 99 if unknown)
804. A. Is supported by another person?
1 Yes
2 No...(Go to question 807)
B. Relationship of this person to
E - 14
-------
Year
Child Code
Form number
805. A. What is the relationship of the head of household
to .
B. Which of the following groups best describes the
occupational status of the head of the household? (Read the
following choices)
1 Unemployed...(Go to question 806)
2 Homemaker... . (Go to question 806)
3 Employed part time
4 Employed full time
806
C. What is (his/her) occupation?^
What is the highest grade or year of school that the head of
household finished?
Grade or year (Code 99 if unknown)
807. Does your family use the WIC program?
1 Yes
2 No
9 Unknown
808. What kind of medical insurance does your child have?
1 No medical insurance
2 Private medical insurance(for example Blue Cross/Blue
Shield)
3 Medicaid
4 Other (Specify)
9 Unknown
809. What was the total income for this family before taxes in
1987?
1 Less than $5,000
2 $5,000 or more but less than $10,000
3 $10,000 or more but less than $15,000
4 $15,000 or more but less than $20,000
5 $20,000 or more but less than $25,000
6 $25,000 or more
8 Refused to answer '
9 Unknown
This completes our interview. Is there anything else you want to
add?
E - 15
-------
Thank you for your cooperation.
Year
Child code
Form number
Administration - 2
1001. Interviewer: Please sign below and fill in yqur ID number
Signature
1002. The quality of this interview isi
1 Reliable
2 Some doubt..
3 Unreliable.. Explain:
ID
Interviewer - check booklet to be sure all questions are answered
and writing and number's ar legible.
E - 16
-------
MARYLAND DEPARTMENT OF THE ENVIRONMENT
TOXICS OPERATIONS PROGRAM
Lead in Soil Abatement Demonstration Project
Summer 1991 Screening
Administration - Follow up
Field Supervisor: Complete items 1 through 6 before giving
questionnaire to interviewer.
1. Form number
2. Address.
Q 4
Street Code
Study Area
House No.
4. Child ID.
5. Child's full name
6. Interviewer ID.
Interviewer: Start completing questionnaire at item 7.
7. Date of interview.
Month
Day
i I
Year
Year 9. 1
Child Code
Form Number Q jf
E - 17
-------
Introduction
Thank you for agreeing to participate in this project.
100. A. Are you the parent or guardian of
1. Yes
2. No
B. Relationship to child_
C. Do you know how spends (his/her) time?
1. Yes
2. No.... (Ask to talk to the parent or guardian who
can best talk about how the child spends (his/Her)
time. If that person is not available,
reschedule the appointment and end here.)
101. What is your name?
First Last
Census
200. What is the total number of persons aged 18 or over living in
this household?
persons
201. A. What is the total number of persons less than 18 years old
living in this household? Be sure to include all young
children and infants.
persons
B. How many of these are under six years old?
children under six years of age.
Year 1 1
Child Code
Form number Q 6.
First I am going to ask you a couple of questions
about . (Do each child in the family in a
separate interview.) Then I will ask you questions about places
(he/she) spends time.
£ - 18
-------
300. A. What is
B. How old is
301. What is
1. Black
2. White
3. Asian
4. Hispanic
5. Other
302. What is
1. Male
2. Female
s date of birth?
Month
_Years
race?
Day Year
today?
Months
's sex?
E - 19
-------
Year £ 1
Child Code
Form number Q £
Now I would like to ask how spent (his/her) daytime
hours during a typical day. (Interviewer - a typical day is
defined as "an average day in the last week")
303. About how many hours per day does
outdoors? (Code 99 for unknown)
hours outdoors (if 0 or unknown go to questions 310)
304. On a typical day, where does spend most of
(his/her) time outside?
1 Around your home
2 Around a baby sitter's, friend's, or relatives's home
3 Around a day care center or school
4 At a public park or playground
5 At some other location (Specify)
8 Not applicable
9 Unknown
305. About how many hours did (he/she) play outside around
(his/her) home? (Code 99 for unknown)
hours outdoors around home (If 0 or unknown go to
question 310)
306. Where does usually play outdoors around
(his/her) home?
Circle as many as stated:
1 Back yard
2 Side yard
3 Front yard
4 Street
5 Alley
8 Other (Specify)
9 Unknown
E - 20
-------
Year 9. 1
Child Code
Form number Q. 6.
307. Is the ground where (he/she) plays grassy/ concrete, asphalt,
plain dirt or soil, a sandbox, or some other surfaces?
Circle as many as stated:
1 Grassy
2 Concrete or asphalt
3 Dirt or soil
4 Sandbox
5 Painted porch or deck
8 Other (Specify)
9 Unknown
308. Did often take some food or a bottle with
(him/her) when (he/she) played outside?
1 Yes
2 No
9 Unknown
310. On a typical day, about how many hours does
indoors at home? (Code 99 for unknown)
__ hours per day
311. On a typical day, about how many hours does
play indoors away from home? (Code 99 for unknown)
hours per day
312. On a typical day, about how many hours does
spend sleeping? (Include naps and night time sleeping. Code
99 for unknown)
hours per day
E - 21
-------
Year
Child code
Form number
9 1
Q 6
400. Does
Mouthing Behavior
use a pacifier?
1 Yes
2 No
3 Unknown
401. How often does
(his/her) mouth?
put {his/her) fingers in
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
402. Many children put toys and things that are not food into their
mouths. Would you say that does this a lot,
once in a while, or almost never?
1 A lot
2 Just once in a while
3 Almost; never
9 Unknown
403. Many children cut their teeth on hard surfaces. How often
have you seen put (his/her) mouth on a window
sill?
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
404. Have you ever seen
mouth?
put paint chips into (his/her)
1 A lot
2 Just once in a while
3 Almost never
9 Unknown
405. Have you ever seen
1 Yes
2 No
9 Unknown
eat dirt or sand?
E - 22
-------
Year 91
Child Code
Form Number Q6
Mouthing Behavior (Continued)
403a. Does your child put his/her mouth on the windowsill?
1 Yes
2 No
9 Unknown
403b. Does your child put his/her mouth the bannister or stair
railing?
1 Yes
2 No
9 Unknown
403c. Does your child put his mouth on any furniture eg. bed
railing?
1 Yes
2 No
9 Unknown
E - 23
-------
Year 9. i
Child code
Form number Q 6.
Now I would like to ask you about 's diet.
407. What is the main type of milk that (he/she) drinks?
1 Breast milk
2 Cow's milk
3 Formula
4 Canned (condensed) milk
8 Other (.Specify)
9 Unknown
408. Does take Feosol, Poly Vi Sol with Iron, or
any other iron supplement?
1 Yes
2 No
3 Formula with iron
9 Unknown
409. Does (he/she) drink fruit juices everyday?' (If yes/ verify
that juice is real juice.)
1 Yes
2 No
9 Unknown
410. Does (he/she) eat any table food (adult food)?
1 Yes
2 No (Go to question 413)
9 Unknown (Go to question 413)
411. If eats table food, does (he/she.) use
fingers?
1 Yes
2 No
9 Unknown
412, How many glasses of water (including drinks mixed with water
does drink per day?
glasses of water?
E - 24
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Year 1 1
Child code
Form number Q 6.
Pets
500. Do you have any dogs or cats?
1 No dogs or cats (Go to question 505),
2 Dog(s) only
3 Cat(s) only
4 At least one dog and cat
9 Unknown (Go to question 505)
501. Does the dog stay inside, stay outside or go in and out of the
house?
1 Inside most of the time
2 Outside most of the time
3 In and out all of the time
8 Not applicable - no dog in house
9 Unknown
502. Does the cat stay inside, stay outside, or go in and out of
the house?
1 Inside most of the time
2 Outside most of the time
3 In and out all of the time
8 Not applicable - no cat "in house
9 Unknown
E - 25
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Year £ 1
Child code
Form number Q 6.
Lead Work or Hobbies
505. Does anyone who lives in this household work in any of the
following jobs?
a. Painting
b. Demolition
c. Welding
d. Plumbing
e. Sandblasting
f. Auto body work
(Code "Yes" if respondent chooses any of the above jobs.)
1 Yes
2 No
9 Unknown
506. I would like to ask about hobbies or other work that may have
been done in this household. In the last three months,
has anyone who lives here done any of the following activities
at home?
a. Painted pictures with artists' paint.
b. Removed paint from parts of the house or furniture in
the house.
c. Painted bicycles or cars.
d. Worked with stained glass.
e. Soldered electronic parts.
g. Soldered pipes.
(Code "Yes" if respondent chooses any of the above
activities.)
1 Yes
2 No
9 Unknown
E - 26
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Year 9. JL
Child code
Form number 6
Housing Characteristics
701. Have you or has anyone else removed paint or sanded any
painted part of your house in the last three months?
1 Yes
2 No
9 Unknown
702. A. Since you have lived in this house, has anyone removed or
sanded paint inside the house.
1 Yes
2 No
9 Unknown
B. If yes when
703. A. Since you have lived in this house, has anyone removed or
sanded paint outside the house.
1 Yes
2 No
9 Unknown
B. If yes when
E - 27
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Year 9. 1
Child code
Form Number Q 6.
Demographics
800. Do you own or rent your home?
1 Rent
2 Own
3 Staying in home for free
9 Unknown
801. What is your marital status?
1 Married
2 Divorced
3 Separated
5 Widowed
5 Single
802. A. Which of the following groups best describes your
occupational status? (Read the following choices.)
1 Unemployed.. (Go to question 803)
2 Homemaker...(Go to question 803)
3 Employed part time
4 Employed full time
5 Retired
B. What is your occupation?
803. What is the highest grade or year of school that you finished?
Grade or year (Code 99 if unknown)
804. What is the relationship of the head of household to
B. Which of the following best describes the occupational
status of the head of the household? (Read the choices)
1 Unemployed (Go to question 805)
2 Homemaker....(Go to question 805)
3 Employed part time
4 Employed full time
5 Retired
C. What is (his/her) occupation?
805. A. What is the highest grade or year of school that the head
of household finished?
Grade or year (Code 99 if unknown)
E - 28
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Year 9. 1
Child code .
Form Number Q 6.
806. Does your family use the WIG program?
1 Yes
2 No
9 Unknown
807. What kind of medical insurance does your child'have?
1 No medical insurance
2 Private medical insurance(for example Blue Cross/Blue
Shield)
3 Medicaid
4 Other (Specify)
9 Unknown
808. What was the total income for this family before taxes last
year?
1 Less than $5,000
2 $5,000 or more but less than $10,000
3 $10,000 or more but less than $15,000
4 $15,000 or more but less than $20,000
5 $20,000 or more but less than $25,000
6 $25,000 or more
8 Refused to answer
9 Unknown
This completes our interview. Is there anything else you want to
add?
1001. Interviewer: Please sign below and fill in your ID number
Signature ID
1002. The quality of this interview is:
1 Reliable
2 Some doubt..
3 Unreliable.. Explain:
Interviewer - check booklet to be sure all questions are answered
and writing and numbers ar legible.
E - 29
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-------
Appendix F
Four Factor Index of
Social Status
-------
Working Paper
June, 1975
FOUR FACTOR INDEX OF
SOCIAL STATUS
August B. Hollingshead
P.O. Box 1965 Yale Station
New Haven, Connecticut 06520
-------
I.Introduction
Characterization of the status structure of society is a
general problem in sociology. For many years sociologists have
discussed the issue of how to determine the positions individuals
or nuclear families occupy in the status structure of a given
society. Several measures have been devised to solve this problem,
but consensus has not been reached on the methodological procedures
that best estimate the positions individuals or nuclear families
occupy in the status structure of complex industrial, urban
societies.
In the early 1940s, I made a systematic examination of status
in a middle-western community. In 1948 I began to study the social
structure of the New Haven area, a highly urbanized, industrial
community. Two years later, I constructed an index designed to
measure social status in this community, based on the use of
education, occupation, and area of residence taken from a cross-
sectional sample of nuclear families living there. The procedures
followed in the development of that index are described in Social
Class and Mental Illness
In the following years I analyzed data from a five percent sample
of nuclear families resident in the New Haven community and found
that area of residence contributed very little to the estimated
status position of a nuclear family: the multiple correlation
between estimated status and education and occupation was .975.
This correlation indicated that area of residence could be dropped
as an indicator of status. In 1957 I published privately a
pamphlet demonstrating that education and occupation could be used
to construct an index of social status.
The Two Factor Index of Social Position has been widely used,
but, with the social and cultural changes that have occurred since
its publication, it stands in need of revision. The major points
of criticism directed toward it are: it is now dated; the range of
occupations used is too narrow; and the family's status position is
based on data about the head of the household. The Four Factor
Index of Social Status presented here is designed to meet these
deficiencies.
II. The New. Index
The new index takes into consideration the fact that social
status is a multidimensional concept. It is premised upon three
basic assumptions:
1. A differentiated, unequal status structure exists in our
society.
2. The primary factors indicative of status are the
occupation an individual engages in and the years of
schooling he or she has completed; other salient factors
F - 1
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are sex and martial status.
3. These factors may be combined so that a researcher can
quickly, reliably, and meaningfully estimate the status
positions individuals and members of nuclear families
occupy in our society.
The four factors used in the new index are: education,
occupation, sex, and marital status. Education changes during
childhood and youth, but it generally stabilizes in the adult
years; the. years of schooling an individual has completed are
believed to be reflected in acqijired knowledge and cultural tastes.
Moreover, education is a prerequisite to entry into occupations
that carry higher prestige in the social system. Occupation may
change in the early years of adult life, but it too tends to become
stable as a person grows into the late twenties and on into the
thirties. It is presumed to be indicative of the skill and power
individuals possess as they perform the maintenance functions in
society.
The sex of an individual remains constant throughout the course
of the life cycle, but it' plays an important part in the roles
individuals play in the performance of maintenance functions in the
society. Marital status defines the relationship of an adult male
or female to the family system; it may or may not be stable from
the early adult years on into old age. Both males and females
participate in the educational process, mainly during the childhood
and adolescent years. Most adult males enter the labor force and
fill occupational roles; in contemporary industrial society, more
and more females are entering the labor force. Marital status is
important in the calculation of social status because of
differences in the ways adult family members participate in the
economic system. One spouse may be a full-time participant in the
labor force while the other is not gainfully employed outside the
home. However,, as the years, the proportion of intact nuclear
families with both spouses gainfully employed increases. Other
families may be headed by a single, widowed, separated, or divorced
male or female who is . now or in the past has been gainfully
employed. This index takes into consideration the several
categories.
III. Estimation of Social Status
Information on each of the four factors is easily gathered in
an empirical study. The sex of a respondent is observable directly
and is assumed to be what appearances indicate. The other factors
require inquiry and evaluation. The use of each factor in the
estimation of standards described in the following sections.
A. Marital Status
1. Married and Living with Spouse
F - 2
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a. One spouse, male, or female, gainfully employed: other
spouse not employed. The estimated social position of this type of
nuclear family is calculated on the basis of the employed member's
education and occupation.
b. Both spouses gainfully employed. The education and
occupation of each spouse is used to estimate the status position
of the nuclear family.
It is assumed that the education and occupation of each spouse
constitutes an equal proportion of the nuclear family's status. In
the absence of theoretical and empirical evidence, a rule of thumb
is followed, that is education and occupation scores for the
husbands and wife are summed and divided by two. Research has
indicated that the prestige of occupations is similar for males and
females and that education is essentially the same for males and
females in the same occupation. In accordance with this finding,
the combined score for the two spouses is assigned as the status
score of the family.
2. Family Without Spouse
Nuclear families or households may be headed by persons who
have never married, divorced persons permanently separated from a
spouse, or widowed persons. Households falling into this category
present the researcher with various alternatives:
a. When the head has never been married, the status score is
calculated by the use of the head's occupation and
education.
b. When a divorced person is employed full time in a
gainful occupation, the occupation and education of the
present head of the household should be used to calculate
the status score.
c. When a separated or divorced person is receiving support
payments from a absent, present or former, spouse, but is
not gainfully employed, the status score should be
calculated from the education and occupation of the
supporting spouse.
d. When a widow or widower who is not gainfully employed is
living on the income from the deceased spouse's estate,
the status score should be computed on the education and
occupation of the deceased spouse during the time he or
she was gainfully employed.
B. Retired Persons
For retired persons, the status score should be calculated
from the education and occupation of the person before he, she, or
F - 3
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they retired. The factor of marital status should be handled in
the same way that it is for nuclear families with one or both
spouses active in the labor force.
C. The Educational Factor
The years of school a respondent has completed are scored on
a seven-point scale, premised upon the assumption that men and
women who possess different levels of education have different
tastes and tend to exhibit different behavior patterns. The years
of school and individual has completed are grouped in the same way
as in the earlier Two Factor Index of Social Position. The amount
of formal education a person has completed is scored as follows:
LEVEL OF SCHOOL COMPLETED ' SCORE
Less than seventh grade 1
Junior high school (9th grade) 2
Partial high school (10th or llth grade) 3
High school graduate (whether private, 4
preparatory, parochial, trade or public)
Partial college (at least one year) or specialized 5
training
Standard college 'or university graduation 6
Graduate professional training (graduate degree) 7
D. The Occupational Factor
The occupation a person ordinarily pursues during gainful
employment is graded on a nine-step scale. Whenever possible, the
scale has been keyed to the occupational titles used by the United
States Census in 1970, and the three-digit code assigned by the
census is given. However, the occupational titles assigned by the
census are not precise enough to delineate several occupational
categories, especially proprietors of businesses, the military,
farmers, and persons dependent upon welfare. Therefore, the
occupational scale has departed from the titles and codes used by
the census for a number of occupations and occupational groups.
OCCUPATIONAL SCALE
SCORE 9 Higher Executives, Proprietors of Large Businesses, and
Major Professionals
a. Higher Executives; chairpersons, presidents, vice-
presidents , secretaries, treasurers;
b. Commissioned officers in the military; majors,
lieutenant commanders, and above, or equivalent;
c. Government of ficials , federal, state, and local: members
of the United States Congress, members of the state
F - 4
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legislatives, governors, state officials, mayor, city
managers;
d. Proprietors of businesses valued at $250,000 and more;
e. Owners of farms valued at $250,000 and more;
f. Major professionals (census code list).
Census
Occupational title code
Actuaries 034
Aeronautical engineers 006
Architects 002
Astronautical engineers 006
Astronomers 053
Atmospheric scientists 043
Bank officers ' 202
Biologic scientists 044
Chemical engineers 010
Chemists 045
Civil engineers 010
Dentists 062
Economists 091
Electrical/electronic engineers 012
Engineers, not elsewhere classified 023
Financial managers 202
Geologists 051
Health administrators 212
Judges 030
Lawyers 031
Life scientists, n.e.c, 054
Marine scientists 052
Materials engineers 015
Mathematicians 035
Mechanical engineers 014
Metallurgical engineers 015
Mining engineers 020
Optometrists 063
Petroleum engineers ' 021
Physical scientists, n.e.c. 054
Physicians 065
Physicists 053
Political scientists 092
Psychologists 093
Social scientists, n.e.c. 096
Sociologists 094
Space scientists 043
Teachers, college/university, including coaches 102-140
Urban and regional planners 095
Veterinarians 072
F - 5
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SCORE 8 Administrators. Lesser Professionals, Proprietors of
Medium-Sized Business
a. Administrative officers in large concerns; district
managers, executive assistants, personnel managers,
production managers;
b. Proprietors of businesses valued between 5100.OOP and
5250,00
c. Owners and operators of farms valued between $100,000
and $250,000:
d. Commissioned officers in the military: lieutenants,
captains, lieutenants, s.g. and j.g., or equivalent;
e. Lesser professional (census code list)
Census
Occupational title code
Accountants 001
Administrators, college 235
Administrators, elementary/secondary school 240
Administrators, public administration, n.e.c. 222
Archivists 033
Assessors, local public administration 201
Authors 181
Chiropractors . 061
Clergyman 086
Computer specialists, n.e.c. 005
Computer systems analysts 004
Controllers, local public administration 201
Curators 033
Editors 184
Farm management advisors 024
Industrial engineers 013
Labor relations workers 056
Librarians 032
Musicians/composers 185
Nurses, registered 075
Officials, public administration,, n.e.c. 222
Personnel workers 056
Pharmacists 064
Pilots, airplane 163
Podiatrists 071
Sales engineers 022
Statisticians 036
Teachers, secondary school 144
F - 6
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Treasurers, local public administration, n.e.c 201
SCORE 7 Smaller Business Owners, Farm Owners, Managers,
Minor Professionals
a. Owners of smaller businesses valued at 575,000 to
5100,000;
b. Farm owners /operators with farms valued at S 7 5 > 0 0 Q to
5100,000;
c. Managers (census code list);
d. Minor professionals (census code list);
e. Entertainers and artists.
Census
Occupational title code
Actors 175
Agricultural scientists 042
Announcers, radio/television 193
Appraisers, real estate 363
Artists 194
Buyers, wholesale/retail trade 205
Computer programmers 003
Credit persons 210
Designers 183
Entertainers, n.e.c. 194
Funeral directors 211
Health practitioners, n.e.c. 073
Insurance adjusters, examiners, investigators 326
Insurance agents, brokers, underwriters 265
Managers, administration, n.e.c. 245
Managers, residential building 216
Managers, office, n.e.c. 220
Officer, lodges, societies, unions 223
Officers/pilots, pursers, shipping 221
Operations/systems researchers/analysts 055
Painters 190
Postmasters, mail supervisors 224
Public relations persons 192
Publicity writers 192
Purchasing agents, buyers, n.e.c. 225
Real estate brokers/agents 270
Reporters 184
Sales managers, except retail trade 233
Sales representatives, manufacturing industries 281
Sculptors 190
Social workers 100
F - 7
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Stock/bond salesmen 271
Surveyors 161
Teachers, except college/
university/secondary school 141-143
Teachers, except college/university, n.e.c 145
Vocational/educational counsellors 174
Writers/ n.e.c. 194
SCORE 6 Technicians, Semiprofessionals, Small Business Owners
a. Technicians (census code list);
t
b. Semiprofessionals; army, m/sgt., navy, c.p.o., clergymen
(not professionally trained), interpreters (court);
c. Owners of businesses valued at 550,000 to 375,000;
d. Farm owners /operators with farms valued at $50,000 to
S75.000.
Census
Occupational title code
Administrators, except farmallocated 246
Advertising agents/salesmen 260
Air traffic controllers 164
Athletes/kindred workers 180
Buyers, farm products 203
Computer/peripheral equipment operators 343
Conservationists 025
Dental hygienists 081
Dental laboratory technicians 426
Department heads, retail trade 231
Dietitians 074
Draftsmen 152
Embalmers 165
Flight engineers 170
Foremen, n.e.c. 441
Foresters 025
Home management advisors 026
Inspector, construction, public administration 213
Inspectors, except construction, public administration 215
Managers, except farmallocated 246
Opticians, lens grinders/polishers 506
Payroll/timekeeping clerks 360
Photographers 191
Professional, technical, kindred workersallocated 196
Religious workers, n.e.c. 090
Research workers, not specified 195
Sales managers, retail trade 231
Sales representatives. Wholesale trade 282
Secretaries, legal 370
Secretaries, medical 371
Secretaries, n.e.c. 372
Sheriffs/bailiffs 965
Shippers, farm products 203
Stenographers 376
F - 8
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Teacher aides, except school monitors 382
Technicians 150-162
Therapists 076
Tool programmers, numerical control 172
SCORE 5 Clerical and Sales Workers, Small Farm, and Business
Owners
a. Clerical workers (census code list);
b. Sales workers (census code list);
c. Owners of small business valued at $25,000' to 350,000;
d. Owners of small farms valued at $25,000 to 550,000.
Census
Occupational title code
Auctioneers 261
Bank tellers 301
Billing clerks 303
Bookkeepers 305
Bookkeeping/billing machine operators 341
Calculating machine operators 342
Cashiers " 310
Clerical assistants, social welfare 311
Clerical workers, miscellaneous 394
Clerical/kindred workers 396
Clerical supervisors, n.e.c. 312
Clerks, statistical 375
Collectors, bill/account 313
Dental assistants 921
Estimators, n.e.c. 321
Health trainees 923
Investigators n.e.c. 321
Key punch operators 345
Library assistants/attendants 330
Recreation workers 101
Tabulating machine operators 350
Telegraph operators 384
Telephone operators 385
Therapy assistants 084
Typists 391
Score 4 Smaller Business Owners, Skilled Manual Workers,
Craftsmen, and Tenant Farmers
a. Owners of small businesses and farms valued at less than
325,000;
b. Tenant farmers owning farm machinery and livestock;
c. Skilled manual workers and craftsmen (census code list);
d. Noncommissioned officers in the military below the rank
of master sergeant and C.P.O.
F - 9
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Census
Occupational title code
Airline cabin attendants 931
Automobile accessories installers 401
Bakers 402
Blacksmiths 403
Boilermakers 404
Bookbinders 405
Brakemen, railroad 712
Brickmasons/stonemasons 410
Brickmason/stonemason apprentices 411
Cabinetmakers 413
Carpenters 415
Carpenter apprentices 416
Carpet installers 420
Cement/concrete finishers 421
Checkers/examiners/inspectors, manufacturing 610
Clerks, shipping/receiving 374
Compositors/typesetters 422
Conductors, railroad 226
Constables 963
Counter Clerks, except food 314
Decorators/window dressers 425
Demonstrators 262
Detectives 964
Dispatchers/starters, vehicles 315
Drillers, earth 614
Dry wall installers/lathers 615
Duplicating machine operators, n.e.c. 344
Electricians 430
Electrician apprentices 431
Electric power linemen/cablemen 433
Electrotypers 434
Engineers, locomotive " 455
Engineers, stationary 545
Engravers, except photoengravers 435
Enumerators 320
Expediters 323
Firemen, fore protection 961
Firemen, locomotive 456
Floor layers 440
Foremen, farm 821
For gemen/ hammermen 442
Furriers 444
Glaziers 445
Heat treaters / annealers / temperers 446
Heaters, metal 626
Housekeepers, except private household 950
Inspectors, n.e.c. 452
Inspectors/scalers/graders, log and lumber 450
Interviewers 331
Jewelers/watchmakers 453
Job and diesetters, metal 454
Lithographers 515
Loom fixers 483
Machinists 461
Machinist apprentices 462
F - 10
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Mail carriers, post office 331
Mail handlers, except post office . 332
Managers, bar/restaurant/cafeteria 230
Marshals, law enforcement 953
Mechanics 470-495
Meter readers 334
Millers, grain/flour/feed 501
Millwrights 355
Molders, metal 503
Molder apprentices 504
Office machine operators, n.e.c. 514
Pattermakers/modlemakers 522
Photoengraver 515
Plasterers 520
Plasterer apprentices 521
Plumbers/pipefitters 522
Plumber/pipefitter apprentices 523
Power station operators 525
Postal clerks 361
Practical nurses 926
Piano/organ tuners/repairmen 516
Pressmen, plate printers, printing trade 530
Pressmen apprentices 531
Projectionists, motion picture 505
Printing trade apprentices, except pressmen 423
Proof readers 362
Radio operators 171
Receptionists 364
Repairmen 471-486
Rollers/finishers, metal 533
Sheetmetal workers 533
Sheetmetal worker apprentices 536
Stereotypers 434
Stock clerks/storekeepers 381
Stone cutter/carvers 546
Structural metal workers 550
Superintendents, building 216
Switchmen, railroad 713
Tailors 551
Telephone linemen/splicers 552
Telephone installers/repairmen 554
Ticket/station/express agents 390
Tile setters 560
Tool and diemakers 561
Tool and diemaker apprentices 562
Weighers 392
Welders/flame cutters 680
Score 3 Machine Operators and Semiskilled Workers (census
code list)
Census
Occupational title code
Animal caretakers 740
Asbestos/insulation workers 601
Assemblers 602
Barbers 935
F - 11
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Blasters/powdermen 603
Boardinghouse/lodging housekeepers 940
Boatmen/canalmen 701
Bottling operatives - 604
Bulldozer operators 412
Bus drivers 703
Canning operatives 604
Carding, lapping, combing operatives 670
Chauffeurs 714
Child care worker, except private household 942
Conductors/motormen, urban rail transit 704
Cranesmen/derrickmen/hoistmen 424
Cutting operatives 612
Deliverymen 704
Dressmakers/seamstresses, except factory 613
Drill press operatives 650
Dyers 620
Excavating/grading/road machine operators 436
except bulldozer
Farm services laborers, self-employed 824
File clerks 325
Filers/polishers/sanders/buffers 621
Fishermen/oystermen 752
Forklift/tow motor operatives 706
Furnacemen/smelters/pourers 622
Furniture/wood finishers 443
Graders/sorters/manufacturing 623
Grinding machine operatives 651
Guards/watchmen 962
Hairdressers/cosmetologists 944
Health aides, except nursing 922
Housekeepers, private household 982
Knitters/loopers/toppers 671
Lathe/milling machine operatives 652Machine
Machine operatives, miscellaneous specified 690
Machine Operative, n.e.c. 692
Meat cutters/butchers, except manufacturing 631
Meat cutters, butchers, manufacturing 633
Metal platers 635
Midwives (lay) 924
Miliners 640
Mine operatives 640
Mixing operatives 710
Motormen, mine/factory/logging camp, etc. 710
Nursing aides/attendants 925
Oilers/greasers, except auto 642
Operatives, miscellaneous 694
Operatives, not specified 695
Operatives, except transportallocated 696
Orderlies 925
Painter, construction/maintenance 510
Painter apprentices 511
Painters, manufactured article 644
Paperhangers 512
Photographic process workers 645
Precision machine operatives, n.e.c. 653
Pressers/ironers, clothing 611
Punch/stamping press operatives 656
F - 12
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Riveters/fasteners 660
Roofers/slaters 534
Routemen 705
Sailors/deckhands 661
Sawyers 662
Service workers, except private household-
allocated
Sewers/stitchers . 976
Shoemaking machine operatives 663
Shoe repairmen 664
Sign painters/letterers 542
Spinners/twisters/winders 543
Solderers 672
Stationary firemen 665
Surveying, chainmen/rodmen/axmen 666
Taxicab drivers 60S
Textile operativesallocated 714
Transport equipment operativesallocated 674
Truck drivers 726
Upholsterers 715
Weavers 563
Welfare service aides 673
Enlisted members of the armed services 954
(other than noncommissioned officers)
Score 2 Unskilled Workers (census code list)
Census
Occupational title code
Bartenders 910
Busboys 911
Carpenter's helpers 750
Child care workers, private household 980
Construction laborers, except carpenters' helpers 751
Cooks, private household 981
Cooks, except private household 912
Crossing guards/bridge tenders 960
Elevator operators 943
Food service, n.e.c., except private household 916
Freight/materials handlers 753
Garage workers/gas station attendants 623
Garbage collectors 754
Gardeners/groundskeepers, except farm 755
Hucksters/peddlers 264
Laborers, except farmallocated 796
Laborers, miscellaneous 780
Laborers, not specified 785
Laundry/drycleaning operatives, n.e.c. 630
Lumbermen/raftsmen/woodchoppers 761
Meat wrappers, retail trade 634
Messengers 333
Office boys 333
Packers/wrappers, n.e.c. 643
Parking- attendants 711
School monitors 952
Waiters 915
Warehousemen, n.e.c. 770
F - 13
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Score 1 Farm Laborers/Menial Service Workers (census code
list)
Census
Occupational title code
Attendants , personal service , n . e . c . 933
Attendants , recreation/amusement 932
Baggage porters /bellhops 934
Bootblacks 941
Chambermaids, maids, except private household , 901
Cleaners /charwomen 902
Dishwashers 913
Farm laborers, wage workers 931
Farm laborers/farm foremen/kindred workers- 846
allocated
Janitors / sextons 903
Laundresses , private household 983
Maids /servants, private household 984
Newsboys 266
Personal service apprentices 945
Private household workers --- allocated 986
Produce graders /sorter, except factory/farm 625
Stockhandlers 762
Teamsters 763
Vehicle washers /equipment cleaners 764
Ushers , recreation/ amusement 953
Dependent upon welfare no regular occupation
IV. The Estima-h-ion of Status
The status score of an individual or a nuclear family unit is
estimated by combining information on sex, marital status,
education, and occupation. The status score of an individual is
calculated by multiplying the scale value for occupation by a
weight of five (5) and the scale value for education by a weight of
three (3)16. To calculate the status score for a nuclear family it
is necessary to determine the education, occupation, and marital
status of its head or heads and their relationship to the labor
force in the present, or for retired persons in the past. Two
examples illustrate this point:
A. .Tohn Smith lives with his spouse'who is housewife.17 He is the
manager of a supermarket. He completed high school and one
year of business college. His status is computed as follows
Peter Paul
Factor Scale score Factor weight Score x Weight
/
occupation 6 5 30
education 5 3 15
total score 45
F - 14
-------
B. The Peter Paul family's score is computed differently because
both Peter and his wife are gainfully employed. Peter is an
installer for the telephone company. His wife is employed as
a clerk in an insurance company office. Peter completed high
school. His wife completed high school and one year of
business college. The scores for each are calculated as
follows:
Factor Scale score Factor weight Score x Weight
occupation 4 5 20
education 4 3 12
total score 32
Marv Paul
Factor Scale score Factor weight Score x Weight
occupation 55 25
education 53 15
total score 40
To determine the Peter Paul family's social status, the scores for
each spouse are summed and the total is divided by two:
Peter Paul 32
Mary Paul 40
total score 72 divided by 2=36.
The total score for the family is higher than that for Peter alone,
but lower than for Mary alone. When two spouses are gainfully
employed the husband's or the wife's education and occupation may
raise or lower the calculated score for there family.
Computed scores range from a high of 66 to a low of 8. This
range remains constant whether the computed score is base on the
occupation of one or two members of a nuclear family or household.
it. is assumed that the higher score of a family or nuclear unit,
the higher the status its members are accorded by other members of
our society. This assumption is derived from the assignment of
differential values to the amount and kind of education an adult
has received and to the occupational functions individuals perform
in society. Values assigned to the amount of education an adult
has received are linked, in turn, to occupational functions. In
contemporary American society, differential rewards are assigned to
occupational functions. In a diffuse way, these values are social;
in a specific sense, they are pecuniary. The most highly valued
occupations are associated with financial, managerial, legal, and
medical functions. Consequently, the banker, the corporation
executive, the corporation lawyer, and the medical specialist are
most highly rewarded for the functions they perform. Technical,
clerical, and sales work carry lower rewards. Such functions as
stoop agricultural labor in the fields of factory farms carry the
lowest pecuniary and social rewards. There are many gradations
between these examples. The important point about occupational
F - 15
-------
function is that the work an individual performs is what is
evaluated. The pecuniary and social rewards associated with it are
society's way of compensating the individual for the work he
performs. Secondly, individuals are identified in society with
their occupational pursuits. In this process, the invidious value
associated with the occupational function is associated with the
individual who performs it. Thirdly, for the mass of individuals,
the income earned on the job is translated into goods and services.
This is expressed in economic terms as a level of living. The
general relationship between occupational pursuits, pecuniary
rewards, and level of living results in the socioeconomic divisions
so vividly recognized in our society.
V. Validation of the Index
To validate the scales used for education and occupation, we
analyzed data gathered in the United States Census in 1970. The
linkage between the years of school completed and occupational
pursuits is shown in Tables 1 and 2 of the Appendix. The analysis
summarized in Table 1 reveals a definite gradient between the years
of school completed and the score assigned to a group of similar
occupations. The gradient is similar for males and females in the
labor force. The correlation between median years of school
completed by sex and occupational score groups is summarized in
Table 2. The coefficient of correlation, r, is essentially the
same for both males and females.
Although I did not utilize data on income in this index, I
have analyzed them for validation purposes. The linkage between
the score assigned to occupational groups and earned income is
summarized in Table 3. The mean dollars earned by each
occupational code group, listed in the 1970 census, traces a
distinct gradient from the highest to the lowest scored occupations
with one exception: in both sexes persons engaged in skilled
occupations, with a score of 4, earned on the average more than
persons in the clerical and sales groups with a score of 5. This
variation between the prestige scores assigned to the clerical and
sales occupations may be attributed to the favorable view of white-
collar clerical and sales work, in contrast to blue-collar skilled
manual work in our society. Another important component in this
variation between prestige scores and earned income is the high
percentage of workers with the score of 4 who belong to craft
unions. Sex is a factor also, since a high proportion of clerical
and sales workers are females, whereas the majority of skilled
manual workers are males. However, when sex is controlled, skilled
manual workers earn more than clerical and sales workers.
The disparity between the mean earnings in each of the nine
occupational group by sex is are reflection of the differential
values assigned to occupational tasks performed by males in
contrast to females. This disparity cannot be attributed to
differences in years of school completed by the two sexes, as is
demonstrated by the figures given in Table 1.
The National Opinion Research Center has been studying
evaluation of occupations and occupational groups for some 30
years. As a criterion against which the scores assigned to
occupations and occupational groups could be tested, I compared the
F - 16
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scores for occupational groups in this index with the prestige
scores developed by the NORC for use in its General Social Survey.18
The occupational titles used by the United States Bureau of the
Census for the 1970 census and scored by.the present index and the
NORC were correlated. The Pearsonian Product Moment Coefficient of
Correlation between the nine-step occupational scale and the NORC
prestige scores is r = .927. The coefficient of determination is
r2 - .860.
The analyses reported here of interrelations between years of
school completed, occupational pursuits, and earnings on the job
demonstrate the existence of a status system in contemporary
American society that is symbolized by the amount / of education
adults have received, the occupations they pursue, and the sex
bestowed on them by the biological lottery we are all enmeshed in.
Education tends to condition occupational opportunities, and the
pecuniary value assigned to occupations, in turn, conditions the
amount of income an individual earns on the job. In sum, the
scores computed by the use of this index are a measure of
inequality in the social system of the United States.
VI. Two Unfinished Tasks
Further research is indicated to determine the effects of
marital status on social status. Preliminary studies indicate that
when both spouses are gainfully employed, instead of just one,
there is a distinct effect on the socioeconomic status of the
individual and/or the nuclear family. A second incomplete research
problem is the division of the continuum of scores based on
education and occupation into meaningful groups. Tentatively, I
believe computed scores for individuals or nuclear families can be
aggregated into groups of scores that encompass the major strata
symbolic of social standing in contemporary American society. I
have found that meaningful groups of scores for estimating the
position of an individual or a nuclear family in the status
structure are as follows:
Range of computed
Social Strata scores
Major business and professional 66-55
Medium business, Minor professional, technical 54-40
Skilled craftsmen, clerical, sales workers 39-30
Machine operators, semiskilled workers 29-20
Unskilled laborers, menial service workers 19-8
When the scores are aggregated, individuals and nuclear
families with scores that fall into a range of scores are presumed
to be in the stratum.
-------
SES
Class 1 = 55 to 66 Major business and professional
Class 2 = 40 to 54 Medium business, minor professional, technical
Class 3 = 30 to 39 Skilled craftsmen, clerical, sales workers
Class 4 = 20 to 29 Machine operators, semiskilled operators
Class 5 = 8 to 19 Unskilled laborers, menial service workers
SCHOOLING
1 = 7th grade
2 = 9th grade
3 ~ 10th or llth grade
4 = high school, including vocational
5 = partial college (at least 1 year) or specialized training
6 = college or university degree
7 - graduate degree
F - 18
-------
Appendix G
Intercalibration Study
-------
-------
Interlaboratory Calibration Study for the Analysis of
Lead in Dust and Soil Samples
One main focus in lead research today is to measure the
association between lead in either dust or soil and children' s
blood lead concentrations. The results of these studies rely on
the measurements of lead concentration in dust and soil samples
gathered from the areas where children are exposed. Several
different chemical techniques are available for measuring the lead
concentration in environmental samples including x-ray fluorescence
spectroscopy (XRF), atomic absorption spectrometry (AAS), and
inductively coupled plasma / atomic emission spectroscopy (ICP).
There are several questions that must be answered about these
methods of measuring lead concentration in dust and soil:
1) Are these three different techniques for Soil and Dust analysis
interchangeable?
2) How consistent are each of these techniques both within each
individual laboratory, and between different labs?
To answer these questions, EPA designed a soil and dust round
robin interlab calibration study. In this study, 15 soil and 5
dust samples were carefully prepared and homogenized by the EMSL
lab in Las Vegas (these samples were not approved as NBS reference
materials). These twenty samples were sent to five different labs,
some of which were capable of performing more than one method of
chemical analysis. Each lab was asked to run several replicates of
each sample for each method of analysis, in an effort to measure
the within lab variability. The lead concentration measurements
from each sample, lab, and method would then be used to answer the
questions listed above.
LAB
CIN
BAL
BOS
LV
RTP
XRF
Y
Y
Y
Y
AAS
Y
Y
ICP
Y
Y
Y
One approach to answering these two questions is to derive a
consensus value of lead concentration for each of the twenty
samples prepared by the lab in Las Vegas. The behavior of
measurements from one particular city, or from one specific method
of chemical analysis could then be compared to these consensus
values. As an intermediate step, it was decided that a separate
G - 1
-------
set of consensus values should be calculated for each method of
analysis.
This entails modeling each lead concentration measurement as
a function of the sample and city for each method of analysis. A
separate analysis was done for soil and dust samples, because there
was evidence showing that these two mediums are different, and are
treated differently in the lab. In exploring different models, one
of the criterion was that there be no significant interaction
between sample and city. A model which does include interaction
effects makes it difficult to calculate a consensus value.
The data was set up so that the response variable (Y^n)
denotes the lead concentration measurement using method (m) of
analysis, of sample(i), in city(j), replicate number(k).
Y^J and s2mij were calculated - the mean and variance of the lead
concentration measurement of sample(i), city(j), using method(m) of
analysis. It appeared that the variance across replications
increased as the concentration of lead in each sample increased.
This effect was uniform for all three methods of analysis, for all
cities involved, and for both dust and soil samples. This pattern
suggests that the errors may be multiplicative instead of additive.
An additive model suggests that the variances remain stable as the
lead concentration measurements increase or decrease, while a
multiplicative model indicates that the variances are linearly
related to the mean.
A generalized linear model with a log link function was
applied to the data in an effort to determine appropriate consensus
values for the lead concentration of each sample. Two models were
explored, one in which the response variable was weighted by the
inverse of the within lab variance s2^, and the other in which each
response variable received equal weight. Both models appear as
follows:
~ sample(mi) + city(mj) + error
exp{sample(mi)} is interpreted as the consensus value for lead
concentration in sample(i) using method(m) of analysis.
Measurements for city(j) using method(m) of analysis must be
multiplied by exp{-city(mj)} in order to obtain the consensus
values.
A standardized residual analysis of these models showed that
the errors were normally distributed. These models suggest that
there are differences between the cities when measuring lead in
both dust and soil. The question of whether the three different
methods of analysis are interchangeable may be answered by an
analysis of covariance structures.
G - 2
-------
Multiplicative Model with Weight = "Within Lab" Variance
Consensus Values For Dust Samples
SAMPLE
XRF
AAS
ICP
1
2
3
4
5
92.8
342.7
1319.0
2943.4
228.3
54.2
221.9
1492.2
2378.1
232.4
81.7
283.4
1362.3
2133.4
206.2
Consensus Values For Soil Samples
SAMPLE
XRF
AAS
ICP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
460.2
960.7
1140.5
2493.5
4139.3
761.0
664.1
1062.3
2987.8
6175.2
13120.7
335.3
12498.5
941.3
1663.2
430.5
1002.1
1106.2
2474.2
4164.1
776.9
623.3
1049.4
3272.6
6863.2
13645.4
361.5
13041.6
949.5
1744.1
426.6
909.6
1018.8
2342.1
3706.1
736.1
656.0
1005.4
3274.9
6411.5
13224.7
323.6
13080.0
923.3
1716.8
G - 3
-------
Multiplicative Model with Weight = 1
Consensus Values For Dust Samples
SAMPLE
XRF
AAS
ICP
1
2
3
4
5
99.1
366.3
1334.0
2932.8
242.4
44.8
217.8
1468.7
2395.7
207.5
80.2
293.9
1392.3
2232.2
211.0
Consensus Values For Soil Samples
SAMPLE
XRF
AAS
ICP
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
399.2
927.5
1002.5
2285.5
3869.7
698.0
610.7
934.2
2849.7
5758,8
13640.3
290.1
12375.7
836.1
1530.0
420.2
1005.9
1109.3
2482.8
4151.1
771.0
611.6
1049.3
3318.4
6890.9
13583.0
352.9
13085.0
934.6
1748.4
415.2
895.3
1007.9
2305.5
3674.8
718.8
644.3
990.2
3209.4
6335.7
13038.3
315.2
12757.8
911.9
1690.5
G - 4
-------
Multiplicative Model with Weight = "Within Lab" Variance
Constant for Adjusting Dust Samples
CITY
KEVEX -
XMET -
XRF
AAS
ICP
CIN
BAL
BOS
LV
RTF
BOS
1.0074
0.7803
1.1527
1.1653
*
*
0.9616
1.0416
*
*
*
*
,
1.0707
1.0707
0.8834
Constant for Adjusting Soil Samples
CITY
KEVEX -
XMET -
XRF
AAS
ICP
CIN
BAL
BOS
LV
RTF
BOS-
0.8698
1.1909
1.0733
0.8977
*
1.0370
0.9839
1.0166
*
*
s
1.0166
1.0166
- 0.9684
*
G - 5
-------
Multiplicative Model with Weight = 1
Constant for Adjusting Dust Samples
CITY XRF AAS ICP
CIN 1.0076 0.9620
BAL 0.7804 1.0412
KEVEX - BOS 1.1525 . 1.1118
LV 1.1651 . 0.9892
RTP . . 0.9177
XMET - BOS
Constant for Adjusting Soil Samples
CITY XRF AAS ICP
CIN 0.8690 0.9840
BAL 1.1926 1.0166
KEVEX - BOS 1.0760 . 0.9980
LV 0.8955 . 1.0567
RTP . . 0.9508
XMET - BOS 1.0367
G - 6
-------
Appendix H
Bid Schedule
-------
-------
SPECIAL FORM OF
Department of General Services Date:
STATE OF MARYLAND
Earl F. Seboda, Secretary DCS Project No: MDE-88-001-TESH-1
301 West Preston Street Contract #4
Baltimore, Maryland 21201
Gentlemen:
We hereby submit our proposal for
LEAD PAINT AND .SOIL STABILIZATION PROJECT IN BALTIMORE COUNTY
Having carefully examined the "Instructions to Bidders", the "General
Conditions", and the Specifications and Plans for the subject
construction
Specifications numbered
Addenda numbered
and having received clarification on all items of conflict or upon which
any doubt arose, the undersigned proposes to furnish all labor,
materials and equipment called for by the said documents for the
following unit prices or lump sum in accordance with the Contract
Documents.
BID SCHEDULE
NOTE: BIDS shall include sales tax and all other applicable taxes and
fees.
NO.
ITEM
UNIT
ESTIMATED
QUANTITY
UNIT
PRICE
TOTAL
PRICE
1. General Requirements:
Bonds and Mobilization
LUMP SUM COST
2. Window & Frame
Complete Preparation
and Painting
3. Window & Frame
Minimum Preparation
and Painting
4. Door & Frame
Complete Preparation
and Painting
Each 1,990 S
Each
Each
37 $_
317 S
H - 1
-------
5. Door & Frame
Minimum Preparation
and Painting Each 65 £.
6. Porch Column,
Complete Preparation
and Painting LF 4.532 jL
7. Porch Column,
Minimum Preparation '
and Painting LF 106 J>_
8. Porch Railing
Complete Preparation
and Painting LF 2.489 £_
9. Porch Railing
Minimum Preparation
and Painting LF 188 £_
10. Porch Fascia & Trim
Complete Preparation
and Painting ' SF 13.771 S_
11. Porch Fascia & Trim
Minimum Preparation
and Painting SF 401 §_
12. Porch Ceiling
Complete Preparation
and Painting SF 16.226 S_
13. Porch Floor,
Complete Preparation
and Painting SF 14.763 £.
14. Front Cornice
Complete Preparation
and Painting SF 8.754 £.
15. Bow Window Units,
Complete Preparation
and Painting (Contingency
item) Each 1.
16. Gutter & Downspout
Complete Preparation
and Painting LF 4.306
17. Sun Room (Window Enclosed
Porch) Comp. Preparation
and Painting Each L
H - 2
-------
18. Steps,
Complete Preparation
and Painting SF 3.715
19. Stair Handrail
Complete Preparation
and Painting LF 1.171
20. Painted Masonry Wall,
Complete Preparation
and Painting SF 38,660
21. Wood or Metal Siding
Complete Preparation
and Painting SF 5.931
22. Scuttle Type Basement Door,
Complete Preparation
and Painting Each 25
23. Garage, Complete
Preparation & Painting LF 1.200
24. Oil Tanks, Complete Each 9
Preparation & Painting
25. Metals - Trim, Complete LF 519
Preparation & Painting
26. Metals - Trim, Minimum LF 111
Preparation & Painting
27. Metal Roof SF 2.147
Preparation & Painting
28. Misc. Surfaces, Complete SF 2.724
Preparation & Painting
29. Misc. Surfaces, Minimum SF 1.083
Preparation & Painting
30. Remove Storm Windows Each 556
No ladder required
31. Remove Storm Window Each 246
Use of ladder required
32. Locate and delineate soil Each 51
removal work areas at each
site
33. Remove and dispose of Ton 750
non-toxic soil and debris
H - 3
-------
34. Remove and dispose of toxic Ton 90 £ _ 3 _
soil and debris
35. Furnish, place and compact CY 440 3 _ 3 _
clean earth
36. Furnish and place clean CY 230 5 _ 3 _
topsoil
r
37. Furnish and place sod SY 4 .000 £ _ S_ _
38. Seed and mulch bare areas SY 1.900 5 _ . §_ _
as directed
39. Remove and re-erect existing LF 300 £ _ S_ _
fence
BIDDER agrees to perform all the work described in the CONTRACT
DOCUMENTS, PLANS AND SPECIFICATIONS for the following price:
Total Bid Price
Submitted with this proposal is a fully executed Bid Bond in the
amount of 5% of the bid when the total bid is $50,000 or more.
It is understood that the bid price will be firm for a time period of
ninety (90) calendar days from the bid opening date and that if the
undersigned be notified of acceptance of this proposal within this time
period, the firm shall execute a contract for the above stated
compensation and shall complete the work within (60) calendar days from
the date the firm has executed the contract and agrees that if the work
is not completed within the time period specified, the Contractor will
be liable for Liquidated Damages of $300 per calendar day as specified
in the "General Conditions", Section 7, Article 14. Also, it is agreed
that on or before the date the firm has executed the contract, the firm
will have and submit to the State an Affirmative Action Plan as
specified in Section 9.02 of the "General Conditions".
(Sign for Identification)
Bid Bonds, except those of three low bidders will be returned after
the bid opening. Other bid bonds will be returned after the related
contract has been executed. If no bid has been accepted within .ninety
(90) days after the bid opening, then any bond, may be returned upon
demand of the bidder.
Failure to property and completely fill in all blanks may be causa for
H - 4
-------
rejection of this proposal.
All alternates called for in the Contract Documents must be submitted
herewith.
(Construction Firm License No.) (Date Issued) (Place of Issuance)
Federal Employer Identification No.
(or Social Security No. if no F.E.I.N.)
INDIVIDUAL PRINCIPAL
FIRM NAME
In Presence of
Witness: - SIGNED
ADDRESS
TELEPHONE NO
CO-PARTNERSHIP PRINCIPAL
In Presence of
Witness:.
(Name of Co-Partnership)
ADDRESS
TELEPHONE
as to BY
(Partner)
as to BY
(Partner)
as to BY
(Partner)
H - 5
-------
CORPORATE PRINCIPAL
Attest:
(Corporate Secretary)
(Name of Corporation)
ADDRESS
TELEPHONE NUMBER
BY .
(Affix Corporate Seal)
(Sign for Identification)
The bidder represents, and it is a condition precedent to acceptance
of this bid, that the bidder has not been a party to any agreement to
bid a fixed or uniform price.
WITNESS:
(SEAL)
Signature of Office and Title
SUBSCRIBED AND SWORN TO before me, a Notary Public of the State of
, County or City of this
day of , 19 .
Notary Public
(Please submit in duplicate)
H - 6
-------
Appendix I
Models For Baltimore Data
Introduction 2-3
Log Transformed Response Variable
in Linear Regression Model .' 4-15
Untransformed Response in GLM
with Normal Error and Log Link 16-27
Models for Comparison with
Boston and Cincinatti Projects 28-30
-------
The material presented in this appendix are the statistical output
from the GLIM software package of models used to understand the
Baltimore data. The models are an attempt of explaining how the
experimental treatment of soil abatement has influenced the blood
lead and hand lead of children involved in the study. These are
primarily linear regression models using a measure of blood lead or
hand lead as the response variable. The response variables in the
Baltimore study were typically distributed log-normal. In each set
of models, the direct effect of group assignment is measured, and
then an appropriate covariate adjusted analysis was performed. The
models presented are cross sectional by round of sampling, and
represent each of three statistical approaches:
1) Apply a natural log transformation to the response variable and
model the data through multiple linear regression with additive
errors. This was the approach selected for presentation in the
main report. It is possible to transform the regression
coefficients back to the original scale of measurement, but the
interpretation of their effects becomes multiplicative instead of
addditive.
2) Use the untransformed response variable in a generalized linear
model with normal error structure and a log link function. The
errors associated with this set of models have multiplicative
effects.
3) In the rounds of sampling following the intervention, use the
log transformed response variable in a linear model with group
assignment, and a summary of the pre intervention response (log
scale) as covariates. This model was developed by the Boston Lead
Free Kids Study, and "can be used to compare and contrast the
results found among the three participating cities.
These three sets of models were applied to two seperate populations
within the Baltimore study. One population represented children
who were sampled in all six rounds of the experiment, while the
other population consisted of every child for whom we had complete
data. The models were applied to both populations to demonstrate
that there were no apparent biases introduced by the attrition
suffered throughout the experiment.
The response variables and covariates used in these models are
described in detail in the Variable Selection section of the main
report, and the statistical models are explained in the section
labels Statistical Models for Blood Lead and Hand Lead.
-------
Following is a list of Variable abbreviations and definitions used
in the GLIM output:
1 Ipb
2 pb
3 Ihw
4 hw
5 ABAT
6 CONT
7 AGEO
8 AGE1
9 AGE2
10 AGE3
11 SES
12 SEAS
13
14
15
16
17
18
19
20
21
MOUT(l)
MOUT(2)
FEMA
DUST
SEX(l)
SEX(2)
SOIL
BLPB
BLHW
Log Blood Lead
Blood Lead
Log Hand Lead
Hand Lead
Treatment Group - Indicator that child lived in a
property that received soil abatement
Control Group - Indicator that child lived in a
property that did not receive soil abatement
Indicator that child is between the ages of 0 and 1
Indicator that child is between the ages of l and 2
Indicator that child is between the ages of 2 and 3
If child is older than three, AGE3 is a linear term
which represents the Child's age - 3
Socio Economic Status (Hollingshead Index)
Indicator that sample was taken between the months
of March and November (When Children are Outdoors)
Indicator of Weak Mouthing Behavior
Indicator of Strong Mouthing Behavior
Indicator that Child is Female
Measure of Dust Lead
Indicator that Child is Male
Indicator that Child is Female
Measure of Soil Lead
Mean of Pre Intervention Log Blood Lead
Mean of Pre Intervention Log Hand Lead
In the GLIM output, the deviance is a measure of the variation left
unexplained by the model. Dividing the deviance by the degrees of
freedom will result in the mean squared error (represented by the
scale parameter).
-------
: ROUND 1 - CHILDREN PRESENT IN .ALL SIX ROODS
! RESPONSE VARIABLE - LOG BLOOD LEAD
! MODEL 1
Swar IpbSerr nS
Slit %gmS
deviance = 32.622
d.f. = 139
Sfit + a bate + control - %gmSdis eS
deviance = 32.556 (change = -0.06565)
-------
! ROUND 1 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
| RESPONSE VARIABLE - LOG BLOOD LEAD
: MODEL 1
Syvar IpbSerr nS
SFit %gm$
deviance = 70374
! dX = 272
Sfit +abate + control - ^gmSdis eS
deviance = 70.271 (change = -0.1031)
dX = 271 (change = -1 )
estimate s.e. parameter
i 2.405 o.0600i ^IBAT
2 2361 0.03592 CONT
scale parameter taken as 0-593
! MODEL 2
Sfit + ageO +agel + age2 +age3 * ses + season + moutb/lhw - mouthSdis eS
deviance = 49335 (change = -20.74)
dX = 263 (change = -8 )
estimate s.e; parameter
1 2333 0.1306 ABAT
2 2327 . 0.1265 CONT
3 -0.6558 0.1245 AGEO
4 -0.01758 0.09485 AGE1
5 0.03895 0.09171 AGE2
6 -0.04762 0.03830 AGE3
7 -0.009923 0.002417 SES
8 0.1391 0.05343 SEAS
9 0.1139 0.04152 MOUTfDXHW
10 0.1650 0.03896 MOUT(2).LHW
scale parameter taken as 0.1883
? RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
Syvar IhwSerr n$
w] - model changed
'" Sfit %gm$
deviance = 162.73
dX a 272
Sfit + abate + control %gm$dis eS
deviance = 162.73 (change = -0.001083)
dX = 271 (change = -1 )
estimate s.e. parameter
1 2.095 0.09132 ^VBAT
2 2.090 0.05466 CONT
scale parameter taken as 0.6005
! MODEL 4
[ilSfit + ageO + aeel * age2 +age3 + female + season + dustSdis eS
-* -
deviance" = 12^57 (chaoge V-3436)"
dJ. = 264 (change^-? )
estimate s.e. parameter
.
1 2J98 0.1451
2 2J59 0.1313 CONT
3 -1J14 04840 AGEO
4 -0.4166 OJ485 AGE1
5 -0.07236 (U481 AGE2
6 0.01890 0.06098 AGE3
7 ^3.1462. OJoiSOZ FEMA
8 n 0.02264 OU»617 SEAS
9 0.00003876 OJMMM3166 DUST
scale parameter taken as 0.4862
° MODEL 5
+age2 +age3 + season +dust +soil - ffcgm$dis eS
deviance = 128.4
dX = 264
^ estimate n js.ev parameter
0.1372 EX(l)
2 2.135 0.1370 SEX(2)
3 -1212 0.1850 AGEO
4 -Q.4159 0.1495 AGE1
5 -0,07558 0.1480 AGE2
6 0.01779 0.06142 AGE3
7 0.02684 0.08542 SEAS
8 0.00004023 0.00003176 DUST
9 -2.797e-05 0.0001307 SOIL
scale parameter taken as 0.4864
-------
: ROUND 2 - CHILDREN PRESENT IN .ALL SIX ROCNDS
I RESPONSE VARIABLE - LOG BLOOD LEAD
»
! MODEL 1
Svvar IpbSerr n$
SFit «fcgm$
deviance = 27.579
d.f. = 135
Sfit + abate + control - %gm$dis eS
deviance = 27.480 (change = -0.09952)
dX = 134 (change =» -1 )
estimate s.e. parameter
1 2383 0.06220 ABAT
2 2327 0.04971 CONJ-
scale parameter taken as 0.2051
Sfit + ageO +acel + ace2 +age3"+ ses + season + mouth/lhw - mouthSdis eS
deviance = 2C672 (change = -2.808)
oJ. = 127 (change = -7 )
1
2
4
6
8
9
10
estimate
2388
2361
0.000
0.007542
0.2174
0.02353
-0-009250
0.03492
0.02039
0.07505
s.e.
0.1562
0.1590
aliased
0.1389
0.1272
0.05385
0.004070
0.07738
0.04701
0.04542
parameter
'ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
SEAS
MOimDXHW
. _ UTtt).L-
._ MOUT(2).LHW
scale parameter taken as 0.1943
RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
Syvar IhwSerr nS
WJ model changed
" S
deviance a 110.59
= 135
+ abate -f control - %em$dis eS
deviance = 110^9 (change = -0.0004272)
dJl = 134 (change = -1 )
estimate s.c. parameter
1 2J87 0.1248 ^LBAT
2 2^91 0.09972 CONT
scale parameter taken as 0.8253
MODEL 4 , ^,.
SGt + ageO + agel + age2 +age3 + female + season + dustSdis eS
deviance =^93.688 (change = -16.90)
= 128 (change = -6 )
estimate
1533
1.979
0.000
-0.1505
0.1670
0.2038
-03607
0.05406
0.0001485
.
Q.2311
0.2214
aliased
0^673
0^498
0.1015
0^487
0^494
parameter
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
SEAS
OUKMMM625 DUST
scale parameter taken as 0.7319
it! MODELS
Sfit sex +ageO
deviance = 92^79
oM. = 128
, M ... .
+age2 +age3 +season +dust +soil - "cgmSdis eS
estimate
1.792
1.441
0.000
-0.1925
0.1494
0.1848
0.08260
0.0001484
0.0003678
s.e.
0^417
0-2434
aliased
02670
02482
0.1016
0.1496
0.00004587
0.0002570
parameter
"SExm
SEXf2J
AGEO
AGE!
AGE2
AGE3
SEAS
DUST
SOIL
scale parameter taken as 0.7209
-------
! ROUND 2 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
! RESPONSE VARIABLE - LOG BLOOD LEAD
! MODEL 1
Svyar IpbSerr nS
$Ht Begins
I deviance = 54.716
dX = 254
Sfit + abate + control %gm$dis eS
deviance = 54.687 (change = -0.02920)
dX = 253 (change = -1 )
estimate s.e. parameter
1 2338 0.05857 ABAT
2 2313 0.03355 CONT
scale parameter taken as 0.2162
! MODEL 2
Sfit + aeeO +aeel + age2 +age3 * ses + season + mouth/lhw - mouthSdis e$
deviance = 47T428 (change = -7258)
dX = 245 (change = -8 )
estimate s.e. parameter
1 2.441 0.1209 ABAT
2 2.431 0.1197 CONT
3 -0.5121 0.2670 AGEO
4 -0.1468 0.1014 AGE1
5 0.05951 0.09507 AGE2
6 -0.03420 0.03748 AGE3
7 -0.01082 0.002662 SES
8 0.004144 0.05630 SEAS
9 0.06129 0.03494 MOUT(1)XHW
10 0.1027 0.03445 MOUT(2)XHW
scale parameter taken as 0.1936
RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
Syvar IhwSerr nS
w] model changed
deviance = 203.52
dX = 254
Sfit + abate + control - %gmSdis eS
deviance = 202.83 (change = -0.6901)
dX = 253 (change = -1 )
estimate
1 2.157
2 2J78
s.e,
0.1128
0.06462
parameter
ABAT
CONT
2 2.278 U.U046Z CUNT
scale parameter taken as 0.8017
. MODEL 4
Sfit + ageO + agel + age2 +age3 + ft
deviance = 171.67 (change = -31.16)
dX. = 246 (change = -7 )
51 + age2 +age3 + female + season + dustSdis eS
^ !_!?Z _^"-»-t -I £\
estimate
1.794
1.902
-0.7262
-0.1154
0.06398
0.2154
-0.1378
0.1209'
s.e.
0.1794
0.1611
0.5074
04924
0.1819
0.06869
04060
0.1057
parameter
CONT
AGEO
AGE1
AGE2
AGO
FEMA
SEAS
0.0001509 0.00003866 DUST
scale parameter taken as 0.6978
! MODEL 5
Sfit sex +ageO +ageL +age2 +age3 + season +dust +soil - %gm$dis eS
deviance = 170^7
dX = 246
estimate
1.762
1.626
-0.7244
-0.1266
0.06258
0.2083
0.1303
0.0001435
0.0002419
s.e.
0.1717
0.1750
0-5057
0.1919
0.1810
0.06867
0.1056
parameter
0.00003862
0.0001573
SEXY2)
AGEO
AGE1
AGE2
AGE3
SEAS
DUST
SOIL
scale parameter taken as 0.6934
-------
! ROUND 3 - CHILDREN PRESENT IN ALL SIX ROUNDS
I RESPONSE VARIABLE - LOG BLOOD LEAD
t
! MODEL 1
5 war IpbSerr n$
SfitfegmS
o] deviance = 30.528
d.f. = 129
Sfit + abate + control - %gmSdis eS
deviance = 30.518 (change = -0.009666)
d.f. = 128 (change = -1 )
estimate s.e. parameter
1 2*245 0.06584 \\BAT
2 2.228 0.05638 CONT
scale parameter taken as 0.2384
! MODEL 2
Sfit + ageO +agel + age2 +age3 + ses +
deviance = 2C639 (change = -5.880)
dZ = 122 (change^ -6 )
mouth/lhw - mouthSdis eS
estimate
2.069
2.073
0.000
-0.4918
0.03714
-0.04629
-0.006410
0.1565
0.2352
S.C.
0.1728
0.1712
aliased
0.4613
0.1362
0.04060
0.004198
0X5300
00)5273
parameter
*ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SI
MOUT(2)XHW
scale parameter taken as 0.2020
RESPONSE VARIABLE - LOG HAND LEAD
MODEL 3
Syvar IhwSerr n$
. model changed
$fit%gm$
ol deviance = 84^05
= 129
Sfit -f abate + control - %gm$dis e$
deviance = 84.773 (change = -0.03214)
dX = 128 (change = -1 )
estimate s.e. parameter
1 2.053 0.1097 ^BAT
2 2J021 0.09397 CONT
scale parameter taken as OJS623
! MODEL 4
Sfit + ageO + agel + age2 +age3 + female + dustSdis eS
deviance = 73^96 (change = -11J8)
= 123 (chang -5 )
estimate
2^39
2.267
0X00
-0.7902
-03175
-0.004791
-0.4888
s.e.
OJ974
0.1870
aliased
0.7946
0.2314
0X6893
parameter
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
0.00008436 0X0004288 DUST
scale parameter taken as 0^983
MODEL 5
i] Sfit sex +ageO +a«l +age2 +age3 +dust -f soil - %gm$dis eS
deviance =
dX = 123
estimate
2.224
1.741
0X00
-0.7747
-03193
-0.005672
0.00008422
0.00006254
s.e. parameter
0.2230 ^EX(l)
0-2160 SEXfe)
aliased AGEO
0.7926 AGE1
0.2309 AGE2
0.06877 AGE3
0.00004286 DUST
0.0002586 SOIL
scale parameter taken as 0.5983
-------
I ROUND 3 - ALL CHILDREN SAMPLED'THROUGHOLT EXPERIMENT
! RESPONSE VARIABLE - LOG BLOOD LEAD
! MODEL 1
Syvar IpbSerr nS
Sfit %gm$
deviance = 58313
d.f. = 228
Sfit -f abate + control - %em$dis eS
deviance = 58313 (change = -0.0004959)
d.f. = 227 (change = -1 )
estimate s.e. parameter
1 2.257 0.05313 \\BAT
2 2.254 0.04314 CONT
scale parameter taken as 02569
! MODEL 2
Sfit + ageO +aeel + age2 +age3,+ ses +
devian« = 4O80 (change = -4.432)
dJ. = 220 (change = -7 )
mouth/lhw - mouthSdis eS
estimate
2.202
2.213
-0.1843
0.07009
0.1218
-0.04249
-0.007053
0.08384
s.e.
00378
0.1349
0.1772
0.1396
0.1079
0.03370
0.003221
0.04169
0.04068
parameter
CONT
AGEO
AGE!
AGE2
AGE3
SES
MOUTtt).LHW
MOUT(2).LHW
scale parameter taken as 0.2222
RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
.. Syvar IhwSerr nS
wj - model changed
n$fit%gm$
o] deviance = 164.52
o] (Lf. = 228
Sfit + abate + control - %gmSdis eS
deviance = 16433 (change = -OJ.912)
dX = 227 (change = -1 )
estimate s.e. parameter
1 1.899 QM919 1ABAT
2 1^»58 0.07243 CONT
scale parameter taken as 0.7239
MODEL 4
ilSfit + ageO +
o J- - -
o
0
o
o
o
estimate
2J41
2.187
-0.6854
-0.4594
-0.2158
0,01716
-0.4666
0.00008175
l + age2 +age3 + female + dustSdis
(change = -26.06)
parameter
s.e.
0.1643
0.1516
02933
0.2292
00798
0.05653
0.1053
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
OJXW03749 DUST
scale parameter taken as 0.6256
! MODEL 5
Sfit sex -fageO +acel +age2 +age3 +dust +soil * %gm$dis eS
deviance = 13834
dJ. = 221
estimate
2.199
1.730
-0^916
-0.4787
-0.2170
0,01706
0.00008190
s.e.
0.1782
0.1648
OJ2941
0.2267
0.1799
0.05657
parameter
8 -5.640e-05
0.00003760
0.00020%
SEX«)
AGEO
AGE1
AGE2
AGE3
DUST
SOIL
scale parameter taken as 0.6260
-------
! ROUND 4 - CHILDREN PRESENT IN .ALL SIX ROUNDS
! RESPONSE VARIABLE - LOG BLOOD LEAD
! MODEL 1
Jwar IpbSerr nS
deviance = 34.477
d.f. = 132
Sfit -f-abate -f control - ^mSdis eS
deviance = 34.222 (change = -OJ553)
dX = 131 (change = -1 )
estimate s.e. parameter
1 2.117 0.06830 ABAT
2 2.028 0.05825 CONT
scale parameter taken as 0.2612
MODEL 2
Sfit + ageO +agel + age2 + age3 + ses + mouth/low - mouthSdis eS
deviance = 27.450 (change = -6.772)
dX = 126 (change = -5 )
estimate s.e. parameter
1 1.977 0.1669 \\BAT
2 1.998 0.1623 CONT
3 0.000 aliased AGEO
4 0.000 aliased AGE1
5 -0.1321 0.3431 AGE2
6 -0.05259 0.02992 AGE3
7 -0.007688 0.904291 SES
8 0.1903 QJOS733 MOUTfDXHW
9 OJ824 0.05888 MOUT(2)XHW
scale parameter taken as 0.2179
RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
Swar IhwSerr n$
w] - model changed
ol deviance = 30.971
of dX = 132
oj
if Sfit + abate + control - %gmSdis eS
"l * * . _ «VJV **« f » » ^ * f\
0
O
0
o
0
0
0
i
i
deviance = 77.777 (change = -3.193)
dX = 131 (change^ -1 )
estimate s.e. parameter
1 1.878 0.1030 ^BAT
2 1.565 OJ)8781 CONT
scale parameter taken as 0.5937
! MODEL 4
Sfit + ageO + agel + age2 + age3 + female + dustSdis eS
01 deviance = 71379 (change = -5.798)
o dX = 127 (change = -4 )
o]
estimate s.e. parameter
1 1.789 0.1752 ^LBAT
2 L531 0.1692 CONT
3 0.000 aliased AGEO
4 0.000 aliased AGEl
5 -0.1383 0.5524 AGE2
6 0.04095 0.04757 AGE3
7 -OJ2887 OJ318 FEMA
8 0.00008650. 0.00004040 DUST
scale parameter taken as 0^668
o
° ! MODEL 5
Sfit sex +ageO +aeel +age2 +age3 +dust +soil - %gmSdis eS
JauinnAa Tl Q/n "" "^
deviance = 73.943
AS. = 127
estimate s.e. parameter
1 1^72 0^716 *SEX(1)
2 1J60 0^835 SEX(2)
3 0.000 aliased AGED
4 0.000 aliased AGEl
5 -02204 0.5586 AGE2
6 0.04482 0.04817 AGE3
7 0.00008800 0.00004094 DUST
8 -0.0001079 0.0002379 SOIL
scale parameter taken as 0.5822
10
-------
! ROUND 4 ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
! RESPONSE VARIABLE - LOG BLOOD LEAD
f
! MODEL 1
Swar IpbSerr nS
Slit %gta$
deviance = 43.688
d.f. = 174
SOt + abate + control - %gmSdis eS
deviance = 42.911 (change = -0.7770)
d.f. = 173 (change = -1 )
estimate s.e. parameter
1 2.169 0.05309 ABAT
2 2.036 0.05339 CONT
scale parameter taken as 02480
! MODEL 2
Slit + ageO +agel +. age2 +age3 +- ses +
deviance = 31.497 (change = -11.41)
dJ. = 167 (change^ -6 )
mouth/law - mouthSdis eS
estimate
2.094
2.094
0.000
0.02029
-0.06191
-0.07006
-0.008668
04647
0.2719
s.e.
0,1304
0.1283
aliased
02110
0.1504
0.02446
0.003405
0.04659
0.04401
parameter
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOurmxHW
MOUTOJXHW
scale parameter taken as 0.1886
RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
Syvar IhwSerr n$
w] model changed
" Sfit %gm$
deviance = 118.88
dX = 174
Sfit +abate + control - %gmSdis eS
deviance = 114.55 (change = -4329)
dX = 173 (change = -1 )
estimate s.e. parameter
1 1^59 QM674 *ABAT
2 1.544 0.08724 CONT
scale parameter taken as 0.6621
! MODEL 4
Sfit -f ageO -( aeel + age2 +age3 + female + dustSdis eS
deviance = 106:97 (change = -7^73)
dX = 168 (change^ -5 )
estimate
1.691
1.444
0.000
0^300
03536
0.04633
0.1999
0.00008103
s.e.
0.1560
0.1574
aliased
03799
02751
0.04440
0.1220
parameter
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
0.00003922 DUST
scale parameter taken as 0.6368
if! MODELS
il Sfit sex 4-ageO +agel +age2 +age3 +dust +soil -%gmSdis eS
deviance = 109.15
= 168
estimate
1.609
1-399
0.000
0^780
0.4144
0.04S75
0.00008444
-0.0001730
s.e.
0.1539
0.1595
aliased
03838
02763
0.04488
0.00003958
0.0002306
parameter
*SEX(1)
SEXh)
AGEO
AGE1
AGE2
AGE3
DUST
SOIL
scale parameter taken as 0.64%
11
-------
: ROUND 5 - CHILDREN PRESENT IN ALL SIX ROODS
: RESPONSE VARIABLE - LOG BLOOD LEAD
! MODEL 1
Swar IpbSerr nS
SHt ^cgmS
deviance = 36226
d.f. = 135
Sfit + abate + control TcgmSdis eS
defiance = 35.952 (change = -0.2743)
d.f. = 134 (change = -1 )
estimate
1 2.179
2.088
s.e.
0.06743
0.05903
parameter
ABAT
CONT
scale parameter taken as 0-2683
I ! MODEL 2
il Sfit + ageO +agel + age2 -f age3 -i- ses + mouth/lhw - mouthSdls eS
-^
deviance = 24.510 (change = -11.44)
-------
: ROUND 5 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
! RESPONSE VARIABLE - LOG BLOOD LEAD
! MODEL 1
Syvar IpbSerr nS
Slit %gm$
deviance = 47.942
cLf. = 172
Sfit + abate + control - %gmSdis eS
deviance = 46.923 (change = -1.019)
d.f. = 171 (change = -1 )
estimate
1 2.259
2 2.106
0.05682
0.05584
parameter
CONT
scale parameter taken as 0.2744
! MODEL 2
Sfit + ageO +agel + age2 +aee3 + ses + mouth/lhw - mouthSdis eS
deviance = 30T736 (change = -16.19)
dX - 165 (change = -6 )
estimate
1.874
1.665
0.000
-0.02518
0.08798
-0.06385
-0.007217
0.2453
03715
s.e.
0.1512
0.1662
aliased
0.2648
0.1534
0.02378
0.003319
0.04527
0.05017
parameter
*ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOurmxHw
MOUT(2).LHW
scale parameter taken as 0.1863
RESPONSE VARIABLE LOG HAND LEAD
! MODEL 3
Syvar IhwSerr nS
w] - model changed
11 Sfit %gm$
deviance = 99.500
d-f. = 172
Sfit + abate + control - %gm$dis eS
deviance = 96.106 (change = -3394)
-------
: ROUND 6 - CHILDREN PRESENT IN ALL SIX ROUNDS
! RESPONSE VARIABLE - LOG BLOOD LEAD
i
! MODEL 1
Swar IpbSerr nS
deviance = 35.245
dJ. = 132
SHt + abate + control - %gm$dis eS
deviance = 34JJ32 (change = -0.4132)
d.f. = 131 (change = -1 )
estimate
1 2.234
"* 2.123
0.06549
0.06120
parameter
ABAT
CONT
scale parameter taken as 0-2659
! MODEL 2
Sfit + ageO +aeel + age2 -f-age3 ₯ ses +
deviance = 26.414 (change = -8.418)
mouth/lhw - mouthSdis e$
= 127 (change -4 )
estimate
1.956
1.854
0.000
0.000
0.000
-0.04667
-0.01269
02609
03580
s.e.
0.2066
0.2186
atiased
aliased
aliased
0.02956
0.004315
0.06144
0.07089
parameter
ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOurmxHW
MOUT(2)XHW
scale parameter taken as 0.2080
! RESPONSE VARIABLE - LOG HAND LEAD
! MODELS
Syvar IhwSerr nS
w] model changed
"
o
o
o
i
0
o
o
o
o
o
0
o
i
i
o
o
o
o
o
o
o
o
o
o
o
0
o
'o
deviance = 55.742
dX= 132
Sfit + abate + control - fcgmSdis eS
deviance = 55.414 (change = -03289)
dX = 131 " *
estimate s.e, parameter
1 2352 0.08260 ^BAT
2 2.451 0.07719 CONT
scale parameter taken as 0.4230
! MODEL 4
Sfit + ageO + aael + age2 +age3 + female + dirttSdis eS
deviance = 49340 (change = -5.474)
dJl = 128 (change^-3 )
estimate
2.422
2.556
0.000
0.000
0.000
0.03363
-0.4055
5.035e-06
s.e.
0.1567
0.1557
aliased
aliased
aliased
0.03881
0.1093
parameter
0^)0003345
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
scale parameter talcMi as
DUST
03902
MODELS
it Sfit sex +ageO
deviance = 49.443
= 128
+age2 +age3 +dust +soil - %gmSdis eS
estimate
2.414
0.000
0.000
0.000
0.03344
3.985e-06
.
0.1527
0.1657
aiiased
aliased
aliased
0.03862
0.00003329
parameter
*SEXm
SEX(2)
AGEO
AGE1
AGE2
AGE3
0.0003307 0.0001967
scale parameter taken as
DUST
SOIL
03863
-------
: ROUND 6 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
r RESPONSE VARIABLE - LOG BLOOD LEAD
i MODEL 1
Swar IpbSerr nS
$fit %gm$
deviance = 42.745
dX = 169
Sfit + abate + control - %gm$dis eS
deviance = 41.507 (change = -1238)
d.f. = 168 (change = -1 )
estimate s.e. parameter
1 2305 0.05360 ABAT
2 2.134 0.05423 CONT
scale parameter taken as 0.2471
! MODEL 2
Sfit 4- ageO +agel + age2 +age3 + ses +
deviance = 28371 (change = -12.64)
dX = 163 (change = -5 )
mouth/lhw - mouthSdis eS
estimate s.e. parameter
1 2.095 0.1631 ABAT
2 1.954 0.1736 CONT
3 0.000 aliased AGEO
4 0.000 aliased AGE1
5 -0.1074 0.1594 AGE2
6 -0.06745 0.02294 AGO
7 -0.01229- 0.003347 SES
8 0.2412 0.04998 MOUT(1)XHW
9 0.3301 0.05402 MOUT(2)XHW
scale parameter taken as 0.1771
RESPONSE VARIABLE - LOG HAND LEAD
! MODEL 3
Syvar IhwSerr n$
wl - model changed
" Sfit %gm$
deviance = 73.843
dX = 169
Sfit +abate + control - %gmSdis e$
deviance = 73.605 (change = -0.2377)
dX = 168 (change = -1 )
estimate s.e. parameter
1 2374 0.07138 \\BAT
2 2.448 0.07222 CONT
scale parameter taken as 0.4381
' MODEL 4
il Sfit + ageO + agel + age2 +age3 + female -i- dustSdis eS
deviance = 67319 (change = -5.685)
dX = 164 (change = -4 )
estimate
2.402
2.505
0.000
0.000
03945
0.03421
-03392
0.00001513
s.e.
0.1313
0.1362
aliased
aliased
0.2426
0.03335
04)9927
04)0003226
parameter
ABAT
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
scale parameter taken as
DUST
0.4141
I MODEL 5
Sfit sex +ageO +
deviance = 67.58
dX = 164
+age2 +age3 +dust +soil -
estimate
2.400
2.053
0.000
0.000
03945
0.03247
0.00001454
0.0002598
s.e.
0.1283
0.1344
aliased
aliased
0.2415
0.03332
0.00003216
0.0001899
parameter
SExm
SEX(2)
AGEO
AGE1
AGE2
AGE3
DUST
SOIL
scale parameter taken as 0.4121
-------
: ROUND 1 OF SAMPLING ^ T _ r n.r,
! RESPONSE VARIABLE - BLOOD LEAD - LOG LI>K
i
! MODEL 1
Syvar pbSerr nSlink IS
I model changed
Sfit %gmS
deviance = 50472 at cycle 4
d.f. = 139
Sfit + abate + control - ^mSdis eS
deviance = 5046.5 (change = -I.) at cycle 4
d.f. = 138 (change = -1 )
estimate s.e. parameter
1 2.562 0.06230 ABAT
2 2.551 0.05139 CONT
scale parameter taken as 36-57
! MODEL 2
Sfit + ageO +ai
deviance = 38!
dX = 130
rel + aee2 +age3 + ses + season + mouth/lhw- mouthSdis eS
fe.4 (change =-11502) at cycle 4
(change = -8 )
1
2
3
4
5
6
8
9
10
estimate
2297
2.369
-03734
0.2514
0.1199
0.06698
-0.009623
0.1054
0.08822
0.1656
s.e.
0.1890
0.1801
0.2558
0.1145
0.1163
0.05667
0.003841
0.07939
0.05904
0.05266
parameter
CONT
AGEO
AGE1
AGE2
AGE3
SES
SEAS
MOCTfl).LHW
MOUT(2)XHW
scale parameter taken as 29.97
RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODEL 3
Syvar hwSerr nSlink IS
w] - model changed
deviance = 11860. at cvcle 5
-------
: ROUND 1 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
r
! MODEL 1
Syvar pbSerr nSlink IS
wj - model changed
' Sfit %gm$
deviance = 9921. at cycle 4
d.f. = 272
Sfit +abate + control - %gm$dis eS
deviance = 9918. (change = -2.) at cycle 4
it = 271 (change = -1)
estimate s.e. parameter
1 2.507 0.05812 ABAT
2 2,489 0.03536 CONT
scale parameter taken as 36.60.
! MODEL 2
Sfit + ageO +agel + age2 +age3 + ses 4- season + mouth/lhw - monthSdis eS
deviance = 7667. (change = -2252.) at cycle 4
if. = 263 (change = -8)
estimate s.e. parameter
1 2.403 0.1265 ABAT
2 2.455 0.1229 CONT
3 -0.5905 02028 AGEO
4 0.02206 0.08816 AGE1
5 -0.01211 0.08626 AGE2
6 -0.04609 0.03812 AGE3
7 -0.01077 0.002584 SES
8 0.1169 0.05460 SEAS
9 0.1192 0.04020 MOUTmXHW
10 0.1650 0.03575 MOUT(2).LHW
scale parameter taken as 29.15
! RESPONSE VARIABLE - HAND LEAD - LOG LINK
I I MODEL 3
i Syvar hwSerr nSlink 1$
w] - model changed
" Sfit <&gm$
deviance = 45120. at cycle
it = 272
SCt + abate + control - %gm$dis e$
deviance = 45107. (change = -13.) at cvcle 6
dJ". = 271 (change = -1 )
parameter
estimate s.e.
1 2.382 0.1404
2 2.427 0.08033 CONT
scale parameter taken as 166.4
MODEL4
i^Sfit 4- ageO + agel + age2 +age3 + female + seas
deviance = 41853. (change = -3255.) at cycle 6
if. = 264 (change = -7)
season + dustSdis eS
estimate
2.584
2.597
-1.414
-0.4871
0.1322
-0.01514
-02893
0.1326
-5225e-06
s.e.
02208
0.1952
0.8912
02897
0.1995
0.09106
OJ372
0.1352
parameter
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
SEAS
0.00005156 DUST
scale parameter taken as 158.5
MODEL 5
i] Sfit sex +ageO -hasel +age2 +age3 +season +dust +soil-%gm$diseS
deviance = 41850. at cycle
it = 264 J
estimate
2^86
2297
-1.420
-0.4960
0,1285
-0.01784
0.1310
-6.751e-06
s.e.
02042
02161
0.8941
02922
0.1994
0.09149
0.1342
0.00005194
parameter
*SEX(1)
SEX(2)
AGEO
AGE1
AGE2
AGE3
SEAS
0.00002605 0.0001907
scale parameter taken as
DUST
SOIL
158.5
11
-------
! ROUND 2 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i
! MODEL 1
J Syvar pbSerr nSlink IS
w] model changed
1 Sfit %gmS
deviance = 7928. at cycle 4
d.f. = 254
Sfit + abate + control - %gm£dis eS
deviance = 7924. (change = -5.) at cycle 4
d-f. = 253 (change = -1)
estimate s.e. parameter
1 2.447 0.06093 ^JBAT
2 2.420 0.03587 CONT
scale parameter taken as 3132
- MODEL 2
Sfit + ageO +a
deviance = 7(
dJ. = 245
zel + ace2 +ace3 + ses + season + mouth/lhw. mouthSdis eS
33. (change = -890.) at cycle 5
(change = -8)
estimate s.e. parameter
1 2.536 00276 ^BAT
2 2.533 0.1263 CONT
3 -0.5039 0.4675 AGEO
4 -0.1698 0.1150 AGE1
5 0.06810 0.09525 AGE2
6 -0.02168 0.03954 AGE3
7 -0.01058 0.002984 SES
8 0.03776 0.05973 SEAS
9 0.03721 0.03733 MOUjm.LHW
10 0.09119 0.03465 MOUT(2)XHW
scale parameter taken as 28.71
I RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODEL 3
_ Syvar hwSerr nStink IS
w] model changed
il$fit%gm$*
ol deviance = 98177. at cycle 6
o] d£ a 254
Sfit + abate + control - %gm$dis eS
deviance = 98154. (change = -23.) at cycle 6
dJ. = 253 (change^ -1)
estimate s.e. parameter
1 2.645 00754 *ABAT
2 2.693 0.09620 CONT
scale parameter taken as 388.0
! MODEL4
Sfit + ageO + a
deviance =
1 + age2 +age3 + female + season + dustSdis eS
6. (change = -5749.) at cycle 7
_L«_«~. ^ ^ \
dJ. = 246 (change^ -7)
estimate
2.024
2.017
-0.6411
03496
0.7973
03531
-0.1736
-0.01348
0.00009842
s.e.
03319
03047
2.740
03914
03226
00116
00623
00599
parameter
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
SEAS
0.00004482 DUST
scale parameter taken as 375.6
. MODEL 5
Sfit sex +ageO +aeel +age2 +age3 + season -f-dust +soii - %gmSdis eS
deviance = 92259. at ~a- '
dX= 246
le 7
estimate
-0.6517
03371
0.7734
03406
-0.002061
0.00009893
0.0001184
s.e.
03062
03275
2.749
03876
03219
0.1117
00597
parameter
l
0.00004401
0.0002005
SEXtt
AGE.
AGE1
AGE2
AGE3
SEAS
DUST
SOIL
scale parameter taken as 375.0
19
-------
! ROUND 3 - CHILDREN PRESENT IN ALL SIX ROUNDS
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
! MODEL 1
. Syvar pbSerr nSIink IS
w] - model changed
" Sfit %gm$
deviance = 4041.7 at cycle 4
d.f. = 129
Sfit + abate + control - <&gm$dis eS
deviance = 4038.1 (change = -4.) at cvcle 4
d.f. = 128 (change = -1)
estimate s.e. parameter
1 2.374 0.07043 ABAT
2 2.342 0.06225 CONT
scale parameter taken as 31-55
! MODEL 2
Sfit + ageO +agel + age2 +age3 + ses + mouth/lhw
deviance = 3079-0 (change = -959.0) at cycle 4
d.f. = 122 (change = -6 )
mouthSdis eS
estimate
1.933
1.940
0.000
-0.4762
0.09891
-0.02235
-0.005615
0.2220
0.3169
s.e.
0.1954
0.1928
aliased
0.9040
0.1328
0.04355
0.004524
0.06017
0.05424
parameter
*ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOurmxHW
MOUT(2).LHW
scale parameter taken as 25.24
! RESPONSE VARIABLE - HAND LEAD - LOG LINK
i I MODEL 3
i Syvar hwSerr nSHnk IS
w] model chanced
" Sfit %gm$
deviance = 8901. at cycle 5
dX = 129 J
Sfit + abate + control - %gmSdis eS
deviance = 8899. (change = -2.) at cycle 5
dJ. = 128 (change^ -1)
estimate s.e. parameter
1 2343 0.1080 ^LBAT
2 2317 0.09485 CONT
scale parameter taken as 69.52
, ! MODEL 4
i] Sfit + ageO + azel + age2 +age3 + female + dustSdis eS
deviance = 7800. (change - -1099.) at cycle 5
-------
: ROUND 3 - .ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
: RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i MODEL 1
. Syvar pbSerr nSIink IS
w] ~ model changed
Sfit <%gmS
deviance = 9068. at cvcle 4
d.f. = 228
Sfit + abate -s- control - ^cgmSdis eS
deviance = 9067. (change = -2.) at cvcle 4
d.f. = 227 (change = -1)
estimate s.e. parameter
1 2398 0.06011 ABAT
2 2.382 0.04946 CONT
scale parameter taken as 39.94
! MODEL 2
Sfit 4- ageO +aeel + age2 +age3 -s- ses + mouth/lhw - mouthSdis eS
deviance = 7630. (change = -1437.) at cycle 5
d.f. = 220 (change = -7 )
estimate s.e. parameter
1 2.279 0.1619 ABAT
2 2.284 0.1603 CONT
3 -0.08295 0.2330 AGEO
4 0.1394 0.1440 AGE1
5 0.1437 0.1133 AGE2
6 -0.04056 0.04059 AGE3
7 -0.007242 0.003742 SES
8 0.08969 0.05073 MOUTdl -LHW
9 0.1982 0.04411 MOUT(2).LHW
scale parameter taken as 34.68
I RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODEL 3
Syvar hwSerr nSUnk 1$
w] - model changed
Sfit %gm$
deviance = 15719. at cycle 5
dX = 228
oj
it Sfit + abate + control - %gm$dis eS
deviance = 15686. (change = -33.) at cycle 5
dX = 227 (change^ -1)
estimate s.e. parameter
o
o
o
o
o
0
o
iMODEL4
Sfit + ageO + agel + age2 +age3 + female + dustidis eS
1 2.215 0.09509
2 2.297 0.07116 CONT
scale parameter taken as 69.10
u
IT!
4s
deviance = 13532. (change = '2154.) at cvcle 5
'*. = 221 (change^ -6 )
estimate s.e. parameter
1 2.444 0.1545 rr"""
2 2.514 0.1397 CONT
3 -0.8175 0^195 AGEO
4 -0.5363 03320 AGEl
5 -0.1403 0.1803 AGE2
6 -0.001810 0.05403 AGE3
7 -0.4892 OJ.143 FEMA
8 0.00007141 0.00002510 DUST
scale parameter taken as 61.23
! MODEL 5
Sfit sex +ageO +agel +age2 +age3 +dust ^soil- %gmSdis eS
deviance = 13550. at cycle 5
dX = 221
estimate s.e, parameter
1 2.528 0.1624 SEX(l)
2 2.034 0.1682 SEXI2)
3 -0.8501 0.6289 AGEO
4 -0.5576 03323 AGEl
5 -0.1414 0.1816 AGE2
6 -0.001366 0.05455 AGE3
7 0.00007020 0.00002490 DUST
8 -7o30e-05 0.0002004 SOIL
scale parameter taken as 6131
21
-------
! ROUND 4 - CHILDREN PRESENT IN ALL SIX ROUNDS
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i MODEL 1
Syvar pbSerr nStink IS
I - model changed
Sfit <&gmS
deviance = 3666.1 at cycle 4
d.f. = 132
Sfit + abate + control - %gm$dis eS
deviance = 3646.1 (change = -20-) at cycle 4
d.f. = 131 (change = -1)
estimate s.e. parameter
1 2250 0.07410 ABAT
2 2.164 0.06877 CONT
scale parameter taken as 27.83
! MODEL 2
Sfit 4- ageO +agel + age2 +age3 -f ses + mouth/Ihw- mouthSdis eS
deviance = 29242 (change = -722.) at cycle 4
d.f. = 126 (change = -5 )
estimate
1.951
2.010
0.000
0.000
0.2920
-0.05242
-0.004553
0.2063
03181
s.e.
0.1878
0.1790
aliased
aliased
0.4930
0.03254
0.004846
0.06053
0.05760
parameter
ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOUTtt).LHW
MOUT(2)XHW
scale parameter taken as 23.21
RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODEL 3
^ Syvar hwSerr nSIink IS
w] - model changed
" Sfit %gm$
deviance = 11344. at cvcle
d.f. = 132
Sfit + abate + control - %gmSdis eS
deviance * 11087. (change = -257.) at cycle
dX * 131 (change = -1)
estimate s.e. parameter
1 2.234 0.1317 --VBAT
2 1.875 0.1608 CONT
scale parameter taken as 84.63
! MODEL 4
Sfit + ageO + agel + age2 +age3 + female + dustSdis eS
deviance = 10847. (change = -240.) at cycle 6
dJf. = 127 (change = -4 )
estimate
2.128
1.806
0.000
0.000
0.05572
0.07056
-02873
0.00002508
s.e.
02723
02852
aliased
aliased
1.148
0.07651
02166
parameter
0.00005435
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
scale parameter taken as
MODEL 5
DUST
85.41
Sfit sex +ageO -fagel -f age2 +age3 +dust -fsoil -
deviance = 11051. at cycfe 6
d J. = U7
eS
estimate
1.966
1.670
0.000
0.000
-0.06426
0.07684
0.00003270
s.e.
02837
0.3288
aliased
aliased
1.149
0.07769
0.00005458
0.0003937
parameter
SEXm
SEX(2)
AGEO
AGE1
AGE2
AGO
DL'ST
SOIL
scale parameter taken as 87.02
22
-------
: ROUND 4 - .ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
: RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i MODEL 1
Syvar pbSerr nSIink IS
I - model changed
Sfit %gmS
deviance = 4812.0 at cycle 4
d.f. = 174
Sfit + abate + control - <%gmSdis eS
deviance = 4757,0 (change = -55.) at cycle 4
d.f. = 173 (change = -1)
estimate s.e. parameter
1 2291 0.05645 ABAT
2 2.171 0.06388 CONT
scale parameter taken as 27.50
! MODEL 2
Sfit + ageO +agel + age2 +age3 + ses + mouth/lhw - mouthSdis eS
deviance = 3451.4 (change = -1305.6) at cycle 4
dJf. = 167 (change = -6 )
estimate s.e, parameter
1 2.089 0.1486 ABAT
2 2.147 0.1419 CONT
3 0.000 aliased AGEO
4 0.01229 0.1562 AGE1
5 -0.07677 0.1418 AGE2
6 -0.06590 0.02756 AGE3
7 -0.007680 0.003837 SES
8 0.1819 0.05093 MOUTftt-LHW
9 02991 0.04308 MOUT(2)iHW
scale parameter taken as 20.67
RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODEL 3
Syvar hwSerr nSIink IS
w] model changed
" Sfit %gmS
deviance = 15495. at cycle 5
dJ. = 174
Sfit + abate + control - %gm$dis e$
deviance = 15094. (change = -401.) at cycle 5
dJl = 173 (change = -1)
estimate s-e. parameter.
1 2.248 0.1039 ^BAT
2 1463 0.1552 CONT
scale parameter taken as 8725
.. ! MODEL 4
il Sfit + ageO + aeel + age2 +age3 + female -f* dustSdls eS
deviance = 14686. (change = -408.) at cycle 6
df. = 168 (change = -5 )
estimate s.e. parameter
1 2.066 02301 ""
w
M!
ilJ
2 1.763 02538 CONT
3 0.000 aliased AGEO
4 04035 03219 AGE1
5 02068 03624 AGE2
6 0.03784 0.06821 AGE3
7 -0.01816 0.1745 FEMA
8 0.00002509. 0.00004828 DUST
scale parameter taken as 87.42
MODELS
Sfit sex +ageO +agel +ace2 +age3 -tdust +soil - %gmSdis eS
deviance = 1489V. at cycle 6
dJ. = 168 J
estimate s.e. parameter
1 1.956 02405 SEXfl)
2 1.929 02526 SEX(2)
3 0.000 aliased AGEO
4 04948 03253 AGE1
5 02846 03681 AGE2
6 0.04194 0.06973 AGE3
7 0.00003205 0.00004883 DUST
8 -0.0002164 0.0003756 SOIL
scale parameter taken as 88.63
23
-------
! ROUND 5 - CHILDREN PRESENT IN ALL SIX ROUNDS
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i
! MODEL 1
. Syvar obSerr nSlink 1$
'] -- model changed
1 Sfit %gm$
deviance = 4338.9 at cycle 4
d.f. = 135
Sfit -J-abate + control - %gmSdis eS
deviance = 4304.0 (change = -35.) at cycle 4
d.f. = 134 (change = -1 )
parameter
estimate s.e.
1 2324 0.07189
2 2.219 0-07007 CONT
scale parameter taken as 32.12
MODEL 2
Sfit + ageO +a;
deviance = 29'.
d£ = 130
»1 + aee2 +aae3 + ses + mouth/lhw mouthSdis eS
£3.7 (change =-13803) at cycle 4
(change = -4 )
estimate
1.666
1.453
0.000
0.000
0.000
-0.05008
-6.182e-05
0.2765
0.4192
s.e.
0.2027
0.2229
aliased
aiiased
aliased
0.03033
0.004533
0.05560
0.05588
parameter
*ABAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOUT(1)XHW
MOUT(2)XHW
scale parameter taken as 22.49
! RESPONSE VARIABLE - HAND LEAD - LOG LINK
t
! MODEL 3
Syvar hwSerr nSIink IS
w] model changed
" Sfit %gmS
deviance = 26111. at cycle 5
dX = 135
Sfit + abate + control - %gm$dis eS
deviance = 25563. (change = -547.) at cycle 5
dX = 134 (change = -1)
estimate s.e. parameter
1 2.668 0.1248 ABAT
2 2.915 0.08526 CONT
scale parameter taken as 190.8
! MODEL 4
SGt + ageO + agel + age2 +age3 + female + dustSdis eS
deviance = 24543. (change = -1020.) at cycle 5
vinnr0 = 25121. af rvr& *?
fill, J^A I «£*.» I OgVA T OK^l
deviance = 25123. at cycle 5
dX = 131
estimate
2.695
2.444
0.000
0.000
0.000
0.04697
s.e.
0.1899
0.2244
aliased
aliased
aliased
0.04960
7 0.00004013 0.00003609
8 0.0001875 0.0002432
scale parameter taken as
parameter
FSEX<1)
SEX(2)
AGEO
AGE1
AGE2
AGE3
SOIL
24
-------
! ROUND 5 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
| RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
! MODEL 1
Syvar pfaSerr nSIink IS
w] model changed
' Slit %%m$
deviance = 6069. at cycle -4
d.f. = 172
Sfit + abate + control - c^gmSdis eS
deviance = 5951. (change = -118.) at cycle 4
d.f. = 171 (change = -1 )
estimate s.e. parameter
1 2.402 0.05775 ABAT
2 2.240 0.06674 CONT
scale parameter taken as 34.80-
o
o
o
o
0
0
o
Vl MODEL 2
il Sfit + ageO + agel + age2 +age3 -4- ses + moutb/lhw - mouthSdis eS
deviance = 3886.5 (change =-2064.35) at cycle 4
d.f. = 165 (change = -6 )
estimate s.e. parameter
1 1.948 0.1676 4BAT
2 1.692 0.1888 CONT
3 0.000 aliased AGEO
4 -0.1224 0.1807 AGE1
5 0.05580 0.1328 AGE2
6 -0.07039 0.02710 AGO
7 -0.005773 0.003639 SES
8 0.2505 0.05088 MOUTmXHW
9 03866 0.04965 MOUT(2) .LHW
scale parameter taken as 23.55
RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODEL 3
., Syvar hwSerr nSIink IS
w] model changed
o] deviance = 30104. at cycle 5
o] d.f. = 172
8
o
o
0
o
o
o
o
o
IT
i IS fit + ageO + agel + age2 +age3 + female + dustSdis eS
Sfit + abate + control - %gmSdis eS
deviance = 29005. (change = -1099.) at cycle 5
dX = 171 (change = -1 )
estimate s.e. parameter
1 2.599 0.1050
2 2.917 0.07507 CONT
scale parameter taken as 169.6
MODEL 4
deviance = 27286. (change = -1719.) at cycle 5
d-f. = 166 (change = -5 )
estimate s.e. parameter
1 2.456 0.1718
2 2.827 0.1568 CONT
3 0.000 aliased AGEO
4 0.8396 0.2917 AGE1
5 -0.03772 03525 AGE2
6 0.04899 0.04127 AGE3
7 -0.1868 0.1203 FEMA
8 0.00005162 OJMM03131 DUST
scale parameter taken as 164.4
MODEL 5
i] Sfit sex +ageO +agel +age2_+age3 +dust +soil- %gmSdis eS
deviance = 28434. at cycle 5
dX = 166
estimate s.e. parameter
1 2.626 0.1598
2 2.424 0.1797 SEX(2)
3 0.000 aliased AGEO
4 0.7185 03203 AGE1
5 -0.1258 03766 AGE2
6 0.04822 0.04215 AGES
7 0.00004338 0.00003301 DUST
8 0.0002567 0.0002150 SOIL
scale parameter taken as 1713
25
-------
: ROUND 6 - CHILDREN PRESENT IN ALL SIX ROUNDS
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i
! MODEL 1
Syvar pbSerr nSlink IS
I model changed
Sfit fcgmS
deviance = 3810.1 at cycle 4
d.f. = 132
Sfit + abate + control -
-------
! ROUND 6 - ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
! RESPONSE VARIABLE - BLOOD LEAD - LOG LINK
i
! MODEL 1
Syvar pbSerr nSlink IS
I - model changed
Sfit %gmS
deviance = 4797.8 at cvcle 4
d.f. = 169
Sfit 4- abate + control - ^graSdis eS
deviance = 4727.6 (change = *70.) at cycle 4
d.f. = 168 (change = -1)
estimate s.e. parameter
1 2.403 0.05173 ABA-T
2 2.279 0.05910 CONT
scale parameter taken as 28.14-
! MODEL 2
Sfit + ageO +agel -t- age2 +age3 + ses + mouth/lhw - mouthSdis eS
deviance = 3135.6 (change = -1592.0) at cycle 4
dJ. = 163 (change = -5 )
estimate
2.106
2.054
0.000
0.000
-0.2047
-0.08500
-04)1106
0.2628
03485
s.e.
0.1535
01598
aliased
aliased
0.1267
0.02330
0.003403
0.04184
0.04418
parameter
\BAT
CONT
AGEO
AGE1
AGE2
AGE3
SES
MOurmxHw
MOUT(2).LHW
scale parameter taken as 1924
RESPONSE VARIABLE - HAND LEAD - LOG LINK
! MODELS
.j Syvar hwSerr nSIiok IS
wl model changed
" Sfit %«mS
deviance = 30454. at cycle 5
dX = 169
Sfit + abate + control - %gm$dis eS
deviance = 30453. (change = -1.) at cycle
d£ = 168 (change = -1 )
parameter
estimate s.e,
1 2.660 0.1013
2 2^71 OJ016 CONT
scale parameter taken as 1813
. MODEL 4
Sfit + aceO + agel + age2 +age3 + female + du:
deviance = 29031. (change = -1422.) at cycle 5
d-f. = 164 (change = -4)
dustSdis eS
estimate
2.743
2.765
0.000
0.000
03241
0.03419
-03817
-2.185e-05
s.e.
0.1876
01940
aliased
aliased
03086
04M758
01483
parameter
0^)0005357
CONT
AGEO
AGE1
AGE2
AGE3
FEMA
scale parameter taken as
DUST
177.0
if! MODEL 5
il Sfit sex +ageO +agel +ace2 +age3 +dust +soil-%gm$dis eS
oj deviance = 28976. at cycle 5
d.£= 164
estimate
2.718
2333
0.000
0.000
032-29
0.03328
-1.891e-05
s.e.
0.1849
0.2134
aliased
aliased
03089
0.04755
0.00005309
parameter
*SEX(1)
SEXh)
AGEO
AGE1
AGE2
AGE3
0.0001546 0.0002639
scale parameter taken as
DUST
SOIL
176.7
27
-------
: MODELS USING BASELINE MEASUREMENT .AS A COVAR1ATE
i
! CHILDREN PRESENT IN .ALL SIX ROUNDS
t
! RESPONSE VARIABLE - ROUND 4 LOG BLOOD LEAD
Swar IpbSerr nS
Slit %mS
deviance = 34.477
d.f. = 132
Sfit blpb -f abate -f control ^mSdis eS
deviance = 9.8278
d.f. = 130
estimate s.e. parameter
1 0.9802 0.05457 BLPB
2 -02169 0.1350 ABAT
3 -0.2303 0.1296 CONT
scale parameter taken as 0.07560
RESPONSE VARIABLE - ROUND 4 LOG HAND LEAD
M Syvar IhwSerr n$
w] ~ model changed
* Sfit %em$
deviance = 80.971
d.f. = 132
Sfit blhw + abate _+ control -.<%gm$dis eS
deviance = 67.157
d.f. = 130
estimate
1 0.4771
2 0.8403
3 0.5512
s.e.
0.1052
02483
02381
parameter
BLHW
ABAT
CONT
scale parameter taken as 0.5166
.ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
RESPONSE VARIABLE - ROUND 4 LOG BLOOD LEAD
Svyar IpbSerr nS
Sfit %gm$
deviance = 43.665
d.f. = 174
Sfit blpb + abate + control %gm$dis eS
deviance = 17.S46
d.f. = 172
estimate s.e. parameter
1 0.8487 0.05477 BLPB
2 0.1663 0.1337 ABAT
3 0.1021 0.1295 CONT
scale parameter taken as 0.1044
! RESPONSE VARIABLE - ROUND 4 LOG HAND LEAD
deviance =
d.f. = 174
Sfit blhw + abate -f control %gmSdis eS
deviance = 102.87
d.f. = 172
estimate s.e, parameter
1 0.4027 0.09151 BLHW
2 1.059 02002 ABAT
3 0.6968 02097 CONT
scale parameter taken as 0.6016
28
-------
MODELS USING BASELINE MEASUREMENT AS A COVARIATE
CHILDREN PRESENT IN ALL SIX ROUNDS
RESPONSE VARIABLE - ROUND 5 LOG BLOOD LEAD
Swar IpbSerr nS
Slit %gm$
deviance = 36.226
d-f. = 135
Sfit blpb + abate + control - <5gmSdis eS
deviance = 11341
dJl = 133
estimate s.e. parameter
1 0.9728 0.05726 BLPB
2 -0.1332 0.1413 ABAT
3 -0.1620 0.1366 CONT
scale parameter taken as 0.08527
0
o
0
0
o
0
0
0
T! RESPONSE VARIABLE - ROUND 5 LOG HAND LEAD
] Syvar IhwSerr nS
w] model changed
II Sfit%gmS
ol deviance = 84.115
o dX = 135
-^
o
0
0
o
o
o
0
0
0
o
deviance = 67340
dX 133
-
estimate s.e. parameter
1 0.5527 0.1015 HJLHW
2 1.178 0.2406 ABAT
3 1.447 0.2296 CONT
scale parameter taken as 0.5063
ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
RESPONSE VARIABLE - ROUND 5
Syvar IpbSerr nS
$fit%em$
deviance = 47.901
ol dX = 172
OJ
it Sfit blpb + abate + control - %gm$dis eS
ol deviance = 20.120
0
0
0
0
0
0
0
0
dX = 170
estimate s.e. parameter
1 0.8853 0.05922 BLPB
2 0.1570 OJ457 ABAT
3 0.07810 0.1405 CONT
scale parameter taken as OJL198
it ! RESPONSE VARIABLE - ROUND 5
LOG BLOOD LEAD
LOG HAND LEAD
II I
i] Syvar IhwSerr nS
w] model changed
deviance = 9&27S
dX = 172
Sfit blhw + abate + control %gm$dis eS
deviance = 82300
dJ. = 170
estimate s.*. parameter
1 0.4167 0.08135 ^LHW
2 1.509 0.1825 ABAT
3 1.749 0.1870 CONT
scale parameter taken as 0.4899
-------
MODELS USING BASELINE MEASUREMENT AS A COVARUTE
CHILDREN PRESENT IN ALL SIX ROUNDS
RESPONSE VARIABLE - ROUND 6 LOG BLOOD LEAD
vvar IpbSerr nS
deviance= 35.245
d i = 132
Sfit blpfa + a bate + control - %gm$dis eS
deviance = 12338
d£ = 130
estimate s.e. parameter
1 0.9297 0.06115 BLPB
2 -0.004740 0.1525 ABAT
3 -0.04171 0.1471 CONT
scale parameter taken as 0.09645
! RESPONSE VARIABLE ROUND 6 LOG HAND LEAD
t
. Syvar IhwSerr nS
w]_ modeiAchanged
deviance = 55.742
dX = 132
Sfit blhw + abate + control - %gm$dis eS
deviance =_ 53,108
estimate s.e. parameter
1 0.2249 0.09465 BLHW
2 1.867 0^197 ABAT
3 1.972 0.2154 CONT
scale parameter taken as 0.4085
ALL CHILDREN SAMPLED THROUGHOUT EXPERIMENT
RESPONSE VARIABLE - ROUND 6 LOG BLOOD LEAD
yyar IpbSerr nS
fit%em$
o] deviance = 42.698
(Lf. = 169
control - %gmSdis e$
Sfitblpb
deviance = 20.472
dX = 167
estimate
1 0.7966
2 0.4007
3 03090
s.e.
0.06122
0.1513
OJ455
parameter
*BLPB
ABAT
CONT
scale parameter taken as 0.1241
RESPONSE VARIABLE - ROUND 6 LOG HAND LEAD
,. Syvar IhwSerr n$
w] - model changed
il SfitfogmS
,ol deviance =
[o] dX = 169
Sfit blhw + abate + control - %gm$dis eS
deviance = 69.832
dX = 167
estimate
1 0^118
2 1.959
3 2.003
.
0.07726
0.1699
0.1774
parameter
*BLHW
ABAT
CONT
scale parameter taken as 0.4232
30
GOVERNMENT PRINTING OFF!:=: 1993 - 75;-06g/60018
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Center for Environmental Research Information
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Part 2
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