Evaluation of the 

HUD Lead-Based Paint 

Hazard Control Grant Program 

Final Report 

Prepared for: 

The U.S. Department of Housing and Urban Development 

Office of Healthy Homes and Lead Hazard Control

By 

The National Center for Healthy Housing and 

The University of Cincinnati Department of Environmental Health

May 1, 2004 
 

Disclaimer 

This document was prepared under grant #MDLR005-94 from the U.S. Department of Housing 

and Urban Development. This document represents the opinions of the authors only and not 

necessarily HUDís official views. Neither the United States Government nor any of its employees 

makes any warranty, expressed or implied, or assumes any legal liability for any third partyís use 

of, or the results of such use of, any information, product, or process discussed in this document. 

Mention or illustration of company or trade names or of commercial products does not constitute 

endorsement by the United States Government. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Evaluation Study Team 

Principal Investigators: 

Dr. Warren Galke National Center for Healthy Housing 

Dr. Scott Clark University of Cincinnati Dept. of Environmental Health 

Dr. Robert Bornschein University of Cincinnati Dept. of Environmental Health 

Corresponding Author: 

Mr. Jonathan Wilson National Center for Healthy Housing 

 

Research Team: 

National Center for Healthy Housing University of Cincinnati

10227 Wincopin Circle, Suite 100 Dept. of Environmental Health 

Columbia, MD 21044 PO Box 670056 

3223 Eden Avenue 

Cincinnati, OH 45267-0056 

 Mr. Jack Anderson Dr. Robert Bornschein 

 Ms. Jill Breysse Ms. LaToya Bridgeman 

 Dr. Sherry Dixon Dr. Ralph Buncher 

 Mr. Nick Farr Dr. Mei Chen 

Dr. Warren Galke Dr. Scott Clark 

Mr. Ron Jones Ms. JoAnn Grote 

Ms. Pat McLaine Dr. Dale Johnson (deceased) 

Ms. Rebecca Morley Mr. William Menrath 

Ms. Heidi Most Mr. DeLing Nui 

Ms. Laura Titus Dr. Lee Rafales 

Mr. Jonathan Wilson Ms. Sandy Roda 

 Dr. Paul Succop 

Mr. Michael White 

Thanks to Dr. Tom Matte and Mr. Dan Pascal of the U.S. Centers for Disease Control and 

Prevention for their counsel on the design, implementation and analysis of the study. 

Thanks to the Enterprise Foundation for their support on the design and monitoring of lead 

hazard control activities, especially to Kent Buhl and Armand Magnelli and to Bob Santucci of 

URC Associates. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Participating HUD Lead Hazard Control Grantees: 

(Agency descriptions provided in Chapter 3) 

Alameda County, CA Milwaukee, WI 

Baltimore, MD State of Minnesota 

Boston, MA State of New Jersey 

State of California New York, NY 

Chicago, IL State of Rhode Island 

Cleveland, OH State of Vermont 

Commonwealth of Massachusetts State of Wisconsin 

HUD Grant Technical Representatives and Advisors 

 Dr. David E. Jacobs 

Dr. Warren Friedman Dr. Barbara Haley Dr. Joey Zhou 

Mr. Ellis Goldman (deceased) Mr. Stevenson Weitz 
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TABLE OF CONTENTS 

EXECUTIVE SUMMARYÖÖÖÖÖÖÖÖÖÖ...ÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ ES-1 

1.0 INTRODUCTION......................................................................................................... 1-1 

1.1 Background ................................................................................................................... 1-1 

1.2 Overview Of Report ......................................................................................................... 1-3 

2.0 DESCRIPTION OF GRANTEE LEAD HAZARD CONTROL PROGRAMS............... 2-2 

2.1 Overview Of Grantee ProgramsÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ....................... 2-2 

2.2 Description Of Grantee ProgramsÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖÖ.................... 2-4 

2.2.1 Alameda County .................................................................................................. 2-4 

2.2.2 Baltimore............................................................................................................. 2-5 

2.2.3 Boston ................................................................................................................. 2-5 

2.2.4 California............................................................................................................. 2-6 

2.2.5 Chicago ............................................................................................................... 2-7 

2.2.6 Cleveland............................................................................................................. 2-8 

2.2.7 Massachusetts .................................................................................................... 2-10 

2.2.8 Milwaukee ......................................................................................................... 2-10 

2.2.9 Minnesota.......................................................................................................... 2-11 

2.2.10 New Jersey ........................................................................................................ 2-12 

2.2.11 New York City................................................................................................... 2-13 

2.2.12 Rhode Island...................................................................................................... 2-14 

2.2.13 Vermont............................................................................................................. 2-14 

2.2.14 Wisconsin .......................................................................................................... 2-15

3.0 STUDY DESIGN AND QUALITY CONTROL METHODS........................................ 3-1 

3.1 Design Of The Evaluation ................................................................................................ 3-1

3.1.1 Consent and Notification Procedures.................................................................... 3-3 

3.1.2 Schedule for Data Collection................................................................................ 3-4 

3.1.3 Summary of Evaluation Protocols ........................................................................ 3-5 

3.1.4 Data Management and Storage Procedures........................................................... 3-6 

3.2 Data Quality Assurance/Quality Control (QA/QC) Summary............................................ 3-6 

3.2.1 QC Spike Sample Procedures and Results............................................................ 3-6 

3.2.2 QC Blank Sample Procedures and Results ........................................................... 3-8 

3.2.3 Substitution of Dust Wipe and Blood Sample Results at or below 

 Reporting Limits.................................................................................................. 3-9 

3.2.4 Quality Control of Inspection and Interview Data .............................................. 3-10 

3.2.5 Quality Control of Portable XRF Instruments..................................................... 3-10 

3.2.6 Substitution of XRF Results at or above Upper Measurement Level................... 3-11 

3.2.7 Quality Control of Lead Hazard Control Activities and Coding Strategies.......... 3-11 

3.2.8 Training ............................................................................................................. 3-12 

3.3 Overview of Statistical Methods Used in the Analysis of Data........................................ 3-12 

3.4 Conventions Used in Summarizing Data......................................................................... 3-13 
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4.0 PRE-INTERVENTION CHARACTERISTICS OF HOUSING UNITS AND RESIDENT 

FAMILIES .................................................................................................................... 4-1

4.1 Introduction ................................................................................................................... 4-1 

4.2 Pre-Intervention Housing Characteristics And Condition.................................................. 4-2 

4.2.1 Pre-Intervention Characteristics of Dwellings ...................................................... 4-4 

4.2.2 Pre-Intervention Physical Condition Of Dwellings ............................................... 4-7 

4.3 Pre-Intervention Lead Hazards in Dwellings..................................................................... 4-7 

4.3.1 Pre-Intervention Condition and Lead Content of Paint ......................................... 4-7 

4.3.2 Pre-Intervention Interior Dust Lead Loadings .................................................... 4-13 

4.3.3 Pre-Intervention Soil Lead Levels ...................................................................... 4-14 

4.3.4 Discussion ......................................................................................................... 4-14 

4.4 Pre-Intervention Characteristics of Enrolled Families ..................................................... 4-19 

4.4.1 Characteristics of Adults .................................................................................... 4-20 

4.4.2 Characteristics of Children................................................................................. 4-20 

4.4.2.1 Gender, Age and Racial/Ethnic Group Distribution............................... 4-20 

4.4.2.2 Length of Residence for Children. ........................................................ 4-21 

4.4.2.3 Previous Blood Lead Testing History. .................................................. 4-21 

4.5 Pre-Intervention Blood Lead Levels................................................................................ 4-25 

4.5.1 Comparison of Evaluation Blood Lead Levels with NHANES III ...................... 4-25 

4.5.2 Influence of Various Factors on Pre-Intervention Blood Lead Levels ................. 4-27 

4.5.3 Discussion ......................................................................................................... 4-30 

5.0 DESCRIPTION OF INTERVENTIONS........................................................................ 5-1 

5.1 Description of the Intervention Data Collection Plan/Definition of Terms......................... 5-1 

5.1.1 Dwelling Unit Interventions................................................................................. 5-1 

5.1.1.1 Reporting Lead Hazard Control Strategies.............................................. 5-3 

5.1.1.2 Concurrent Work.................................................................................... 5-4 

5.1.2 Individual Lead Hazard Control Treatments......................................................... 5-4 

5.2 Description of the Lead Hazard Interventions at the Dwelling Unit Level......................... 5-5 

5.2.1 Lead Hazard Control Strategies............................................................................ 5-5 

5.2.1.1 Interior Strategies. .................................................................................. 5-6 

5.2.1.2 Exterior Strategies ................................................................................ 5-12 

5.2.1.3 Site Strategies....................................................................................... 5-15 

5.2.2 Concurrent Work ............................................................................................... 5-18 

5.2.3 Summary of Strategy Selection and Interventions .............................................. 5-20 

5.3 Description of individual Lead Hazard Control Treatments............................................. 5-22 

5.3.1 Interior Treatments............................................................................................. 5-22 

5.3.2 Exterior/Site Treatments .................................................................................... 5-25 

5.3.3 Summary of Individual Treatments .................................................................... 5-26 

6.0 COSTS OF LEAD HAZARD CONTROL ACTIVITIES............................................... 6-1 

6.1 Background ................................................................................................................... 6-1 

6.1.1 Evaluation Costs .................................................................................................. 6-1 

6.1.2 Methodology........................................................................................................ 6-1 

6.2 Dwelling Unit Level Cost Estimates ................................................................................. 6-3 

6.2.1 Methodology........................................................................................................ 6-3 
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6.2.2 Interior Treatment Costs .....................................................................................6-5 

6.2.3 Exterior Costs ...................................................................................................... 6-9 

6.2.4 Site Costs........................................................................................................... 6-10 

6.2.5 Discussion ......................................................................................................... 6-10 

6.3 Factors Contributing to the Observed Variation in Interior Costs .................................... 6-12 

6.3.1 Methodology...................................................................................................... 6-12 

6.3.2 Results ............................................................................................................... 6-14 

6.3.3 Discussion of Findings....................................................................................... 6-14 

6.3.3.1 Intervention Strategy................................................................................. 6-14 

6.3.3.2 Pre-intervention Building Characteristics and Condition....................... 6-15 

6.3.3.3 Pre-intervention Occupancy Status of the Dwelling. ............................. 6-15 

6.3.3.4 Contractor Economies of Scale............................................................. 6-16 

6.3.3.5 General Requirements Placed on the Contractor. .................................. 6-16 

6.3.3.6 Regional Cost Factors for General Construction Activities ................... 6-17 

6.4 Costs of Individual Lead Hazard Control Treatments...................................................... 6-17 

6.4.1 Methodology...................................................................................................... 6-18 

6.4.2 Results ............................................................................................................... 6-19 

6.4.2.1 Walls/Ceilings ...................................................................................... 6-19 

6.4.2.2 Floors/Stairs ......................................................................................... 6-20 

6.4.2.3 Doors ................................................................................................... 6-20 

6.4.2.4 Trim ..................................................................................................... 6-24 

6.4.2.5 Windows .............................................................................................. 6-24 

6.4.2.6 Exterior Treatments.............................................................................. 6-25 

6.4.3 Discussion ......................................................................................................... 6-25 

6.5 Final Commentary on Lead Hazard Control Costs.......................................................... 6-25 

7.0 OBSERVED OUTCOMES IMMEDIATELY POST-INTERVENTION ....................... 7-1 

7.1 Introduction to Immediate Post-Intervention Period.......................................................... 7-1 

7.2 Occupant Protection Policies ............................................................................................ 7-2

7.2.1 HUD Occupant Protection Policies under the HUD LHC Grant Program............. 7-2 

7.2.2 HUD Clearance Policies under the HUD LHC Grant Program ............................. 7-3 

7.3 Treatment Effectiveness at Clearance ............................................................................... 7-4 

7.3.1 Methodology........................................................................................................ 7-4 

7.3.2 Initial Clearance Failures ..................................................................................... 7-6 

7.3.2.1 Results of Statistical Modeling: Clearance Failures ..................................... 7-9 

 7.3.2.1.1 Floors .................................................................................................. 7-9 

 7.3.2.1.2 Window Sills and Troughs................................................................. 7-12 

7.3.2.2 Results of Modeling: Clearance Dust Lead Loadings................................ 7-12 

 7.3.2.2.1 Effect of Interior Strategy ................................................................ 7-14 

7.3.3 Discussion of Findings....................................................................................... 7-18 

7.3.3.1 Treatment Effects...................................................................................... 7-18 

7.3.3.2 Other Effects............................................................................................. 7-20 

 7.3.3.2.1 Surface Condition.............................................................................. 7-20 

 7.3.3.2.2 Pre-Intervention Occupancy............................................................... 7-21 

7.3.3.3 Overview of Initial Clearance Results ....................................................... 7-21 

7.4 Occupant Protection ....................................................................................................... 7-22 
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7.4.1 Assessment Methods...................................................................................... 7-22 

7.4.1.1 Methodology for Assessing Occupant Protection ...................................... 7-22 

7.4.2 Occupant Protection Findings ............................................................................ 7-23 

7.4.2.1 Relocated Households ............................................................................... 7-23 

7.4.2.2 Non-Relocated Households ....................................................................... 7-24 

7.4.2.3 Relationship of Relocation and Treatment Strategy ................................... 7-25 

7.4.2.4 General Occupant Findings ....................................................................... 7-25 

7.4.3 Findings for All Children with Blood Lead Increases of 5 μg/dL or More .......... 7-26 

7.4.3.1 Findings for Children Fitting Evaluation Criteria....................................... 7-28 

 7.4.3.1.1 Childís Age at Pre-Intervention .......................................................... 7-29 

 7.4.3.1.2 Female Caregiverís Education ............................................................ 7-30 

 7.4.3.1.3 General Exterior Building Condition .................................................. 7-30 

 7.4.3.1.4 Season................................................................................................ 7-30 

7.4.3.2 Discussion of Findings about Blood Lead Increases .................................. 7-31 

7.5 Summary of the Observed outcomes Immediately Post-Intervention............................... 7-32 

7.5.1 Clearance Dust Lead Findings............................................................................ 7-32 

7.5.2 Occupant Protection........................................................................................... 7-33 

8.0 EFFECTS OF INTERVENTIONS ON DUST LEAD LOADINGS ............................... 8-1 

8.1 Introduction ................................................................................................................... 8-1 

8.2 Methodology ................................................................................................................... 8-3 

8.2.1 Dust Collection Methodology .............................................................................. 8-3 

8.2.2 Objectives of Data Analysis Methodology ........................................................... 8-4 

8.2.2.1 Post-Intervention Dust Lead Loadings as a Measure of Effectiveness.......... 8-5 

8.2.2.2 Changes (%) from Pre-Intervention to Post-Intervention Dust Lead 

 Loadings as a Measure of Effectiveness ...................................................... 8-5 

8.2.2.3 Percent of Dwellings with Dust Lead Loadings Above a Given Level as a 

 Measure of Effectiveness ............................................................................ 8-5 

8.2.2.4 Discussion of the Use of these Measures ..................................................... 8-6 

8.2.3 Statistical Methodology ....................................................................................... 8-6 

8.2.3.1 Repeated Measures Models......................................................................... 8-7 

8.2.3.2 Multiple Regression Models........................................................................ 8-7 

8.2.3.3 Post-Intervention Structural Equations Models............................................ 8-7 

8.3 Effectiveness of All Interventions on Longitudinal Dust Lead Loadings ........................... 8-8 

8.3.1 Dwellings Meeting the Requirements in the Base Evaluation ............................... 8-8 

8.3.2 Dwellings Meeting the Requirements in the Extended Evaluation ........................ 8-9 

8.3.3 Floor Dust Lead Findings................................................................................... 8-12 

8.3.4 Window Dust Lead Findings.............................................................................. 8-12 

8.4 Relative Effectiveness of Intervention Strategies on Dust Lead Loadings ....................... 8-19 

8.4.1 Relationships Between Interior Strategy and Post-Intervention Dust Lead 

 Loadings Without Consideration for Other Factors ............................................ 8-19 

8.4.1.1 Floor Dust Lead Loadings: One-Year Post-Intervention ............................ 8-21 

8.4.1.2 Floor Dust Lead Loadings: Three-Years Post-Intervention ........................ 8-23 

8.4.1.3 Window Dust Lead Loadings: OneñYear Post-Intervention...................... 8-26 

8.4.1.4 Window Dust Lead Loadings: Three-Years Post-Intervention ................... 8-29 

8.4.2 Relationships Between Lead Hazard Control Interventions and 
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 Post-Intervention Dust Lead Loadings When Other Factors Are Considered .... 8-32 

8.4.2.1 One-Year Post-Intervention Floor Dust Lead Loadings ............................. 8-33 

8.4.2.1.1 Intervention Effects on One-Year Post-Intervention Floor Dust 

 Lead Loadings ....................................................................... 8-34 

 8.4.2.1.2 Discussion of Intervention Effects ........................................................ 8-36 

 8.4.2.1.3 Discussion of Other Factors.................................................................. 8-37 

8.4.2.2 One-Year Post-Intervention Window Dust Lead Loadings ........................ 8-38 

 8.4.2.2.1 Intervention Effects on One-Year Post-Intervention 

 Window Dust Lead Loadings.................................................. 8-38 

 8.4.2.2.2 Discussion of Intervention Effects on Window Dust Lead .................. 8-40 

8.4.3 Pathways of Dust Lead and the Effect of Interventions on Those Pathways........ 8-42 

8.4.3.1 Pre-intervention Structural Equation Model............................................... 8-42 

 8.4.3.2 One-Year Post-Intervention Structural Equation Model............................. 8-43 

8.5 Effect of Exterior Dust and Soil on Post-intervention Dust Lead Loadings ..................... 8-47 

8.5.1 Methodology...................................................................................................... 8-48 

8.5.1.1 Sample Collection..................................................................................... 8-48 

8.5.1.2 Statistical Methodology............................................................................. 8-49 

8.5.2 Findings................................................................................................................... 8-50 

8.5.2.1 General Descriptive Statistics.................................................................... 8-50 

8.5.2.2 Model Results ........................................................................................... 8-50 

8.5.3 Summary of Findings............................................................................................... 8-56 

8.6 Treatment Longevity ...................................................................................................... 8-57 

8.6.1 Methodology...................................................................................................... 8-57 

8.6.1.1 Field Assessment Procedures .................................................................... 8-57 

8.6.1.2 Operational Issues..................................................................................... 8-58 

8.6.2 Treatment Failures................................................................................................... 8-59

8.6.2.1 Treatment Failures by Time after Clearance .............................................. 8-61 

8.6.2.2 Treatment Failures by Component Treated................................................ 8-61 

8.6.2.3 Treatment Failures by Treatment Class ..................................................... 8-63 

8.6.2.4 Examination of Failures to Individual Treatment Equivalent Categories.... 8-65 

8.6.2.5 Treatment Failures of Encapsulants........................................................... 8-65 

8.6.3 Summary of Findings............................................................................................... 8-65 

8.7 Effects on Individual Treatments on Dust Lead Loadings ............................................... 8-67 

8.7.1 Introduction ............................................................................................................. 8-68 

8.7.2 Methodology ........................................................................................................... 8-68 

8.7.2.1 Selection of Eligible Rooms for Room Level Analyses ............................. 8-69 

8.7.2.2 Selection of Treatments for Room Level Analyses .................................... 8-69 

8.7.2.3 Statistical Method of Analysis................................................................... 8-70 

8.7.3 Findings of Room Level Models.............................................................................. 8-70 

8.7.3.1 Effects of Window Treatments.................................................................. 8-72 

 8.7.3.1.1 Effect of Window Paint Lead Levels on Window Trough Dust Lead 

 Loadings ............................................................................. 8-75 

 8.7.3.1.2 Effect of Surface Condition on Dust Lead Loadings ........................... 8-77 

 8.7.3.1.3 Impact of Dust Lead Loadings Outside the Room on 

 Treatment Effects................................................................ 8-77 

 8.7.3.1.4 Impact of Window Treatments Three Years After Intervention........... 8-77 
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 8.7.3.1.5 Summary of Effects of Window Treatments on Dust Lead Loadings .. 8-78 

8.7.3.2 Effects of Paint Removal........................................................................... 8-81 

9.0 EFFECTS OF INTERVENTIONS ON CHILDRENíS BLOOD LEAD......................... 9-1 

9.1 Introduction ................................................................................................................... 9-1 

9.2 Methodology ................................................................................................................... 9-2 

9.2.1 Blood Collection Methodology.................................................................................. 9-2 

9.2.2 Statistical Methodology ............................................................................................. 9-2 

9.2.2.1 Repeated Measures Model .......................................................................... 9-4 

9.2.2.2 Post-Intervention Structural Equations Model ............................................. 9-4 

9.2.2.3 Pre-intervention Structural Equations Model............................................... 9-4 

9.3 Descriptive Statistics of Longitudinal Blood Lead Levels ................................................. 9-7 

9.3.1 One-Year Post-Intervention ....................................................................................... 9-7 

9.3.2 Two-Years Post-intervention ..................................................................................... 9-9 

9.4 Treatment Effectiveness ................................................................................................. 9-12 

9.4.1 General Characteristics of the Children and Their Homes ........................................ 9-12 

9.4.2 Effect of Interventions on Post-Intervention Blood Lead Levels Without 

 Consideration of Other Factors........................................................................... 9-13 

9.4.3 Effect of Interventions on Post-Intervention Blood Lead Levels When 

 Considering Other Factors.................................................................................. 9-15 

9.4.3.1 Effects of Interventions on One-Year Post-Intervention Blood Lead.......... 9-15 

9.4.3.2 Effects of Interventions on Changes in Post-Intervention Blood Lead........ 9-16 

9.4.4 Discussion of Intervention Findings......................................................................... 9-17 

9.4.5 Factors Modifying Treatment Effects....................................................................... 9-17 

9.4.5.1 Pre-intervention Blood Lead Levels and Parental Report of 

 Previous Lead Poisoning ..................................................................... 9-17 

9.4.5.2 Childís Race/Ethnicity .............................................................................. 9-18 

9.4.5.3 Childís Age............................................................................................... 9-20 

9.4.5.4 Sampling Phase......................................................................................... 9-24 

9.4.5.5 Date of Testing (Seasonality) .................................................................... 9-26 

9.4.6 Changes in Pathways from Pre-Intervention to Post-Intervention............................. 9-26 

9.5 Conclusions ................................................................................................................. 9-28 

10.0 CONCLUSIONS......................................................................................................... 10-1 

10.1 Overall Findings ............................................................................................................. 10-1 

10.2 Findings for Specific Intervention Strategies................................................................... 10-2 

11.0 REFERENCES............................................................................................................ 11-1
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EXECUTIVE SUMMARY 

Introduction 

Protecting children from lead-based paint hazards in housing remains an urgent need. Despite 

significant improvement, the Centers for Disease Control and Prevention estimates that nearly 

half a million children in 1999-2000 still have excessive exposures to lead. 

This study is the largest and most comprehensive of its kind ever. It examined over 3,000 houses 

located in over a dozen jurisdictions across the country where the U.S. Department of Housing 

and Urban Development (HUD) provided funding to address lead-based paint hazards in 

privately owned low-income housing where the risks are greatest. The study looked at virtually 

all of the modern ways of controlling lead-based paint hazards and their relative effectiveness. 

The study provides evidence that the lead hazard control activities as practiced by the 

participating programs can substantially reduce dust lead levels on floors, window sills and 

troughs and in most cases, the lead-in-dust remains well below pre-treatment levels for at least 

three years. More importantly, the activities were also associated with substantial declines in 

childrenís blood lead levels (37% two years after treatment). The findings of this study should 

be disseminated so that all those engaged in lead hazard control work can benefit from them. 

Background 

In 1993 and 1994, HUD awarded funds to 30 grant recipients (grantees) under the HUD LeadBased Paint Hazard Control Grant Program. HUD required all 11 grantees in 1993 to participate 

in an evaluation of the program. Three grantees that were awarded funds in 1994 agreed to join 

the evaluation. The participating grantees included State or local governmental agencies in the 

following locations: Alameda County, CA; Baltimore, MD; Boston, MA; California; Chicago, 

IL; Cleveland, OH; Massachusetts; Milwaukee, WI; Minnesota; New Jersey, New York, NY; 

Rhode Island; Vermont; and Wisconsin. 

Each grantee in the Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program 

collected comprehensive environmental data on all treated dwellings. Grantees also attempted to 

recruit families residing in the dwellings into the evaluation. Families that consented to 

participate agreed to be interviewed and allowed blood to be drawn from children between 6 

months and 6 years of age at enrollment were eligible. Local Institutional Review Boards in the 

jurisdictions of the grantees reviewed and approved the study designs. 

Information was gathered at four periods of time for all of the grantees: before the lead hazard 

control work, within 6 weeks after work, 6 months after work and 12 months after work. In order 

to assess the longevity of the treatments, HUD awarded funds to nine of the grantees to collect 

additional longitudinal data in approximately 40 percent of the dwellings two years and three 

years after work was completed. 

Data collection began in January 1994. Data were collected from over 3,000 dwellings; of these 

units, 2,682 dwellings were treated and had final clearance results. The last dwelling unit was 

treated in October 1997 and the last 12-month data were collected in October 1998. The last 

dwelling eligible for the 3-year evaluation was treated in June 1996 and final data were collected 

for these units in June 1999. 
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The design of the HUD Lead Hazard Control Grant Program encouraged grantees to implement 

hazard control measures of their choice and did not include the use of control groups. The 

evaluation was designed to compare the effectiveness of the different classes of interventions 

that grantees used. The primary measures of effectiveness were dust lead loadings and blood 

lead concentrations; the methodology for collecting these measures is described at the end of this 

summary as well as in the body of the report. 

Key Findings 

Pre-Intervention Conditions: 

• Dwellings in the Evaluation tended to be older and have lower occupancy rates and 

much lower market values than those in the general US housing stock. The majority of 

buildings were pre-1930, occupied rental units located in multi-unit buildings. 

• Paint lead and dust lead levels were higher than in average U.S. dwellings, as identified 

in the National Survey of Lead and Allergens in Housing. This finding was expected 

since grantees targeted higher risk housing. However, before lead hazard control (preintervention), dust lead loadings were lower than expected, especially on floors. 

Contractors voiced concerns about passing the original floor clearance standard of 200 

μg/ft2

, yet less than 25% of enrolled dwellings exceeded the standard pre-intervention. 

• Building components with higher paint lead levels were more likely to be deteriorated. 

Exterior surfaces tended to have higher paint lead levels (Median of all dwellings: 2.2 

mg/cm2

) than interior surfaces, and windows tended to have the highest paint lead levels 

(Median: 2.0 mg/cm2) of all interior surfaces. 

• Occupancy status influenced floor and window sill dust lead, especially floor dust lead, 

with larger loadings observed in vacant dwellings. For interior floors, the geometric 

mean dust lead loading in vacant dwellings was 132 μg/ft2 compared to 17 μg/ft2 in 

occupied dwellings. For window sills, the geometric mean dust lead loading in vacant 

dwellings was 1,001 μg/ft2 compared to 278 μg/ft2 in occupied dwellings. Anecdotally, 

grantees reported that vacant dwellings tended to be vacant for many months prior to 

enrollment. 

• Interior entry floors had significantly higher dust lead loadings than other interior floor 

surfaces. In occupied dwellings, the geometric mean dust lead loading on entry floors 

was 23 μg/ft2

 compared to 17 μg/ft2 on interior floors. Further analysis suggests that 

entry floors serve as a pathway of leaded dust from the building exterior to the interior. 

• Pre-intervention paint, dust and soil lead levels varied by grantee. Some of these 

differences may be explained by differences in the recruitment strategies (i.e., targeting 

higher risk communities vs. targeting units where children were lead poisoned), but some 

appear to be the result of differences from city-to-city in the application of lead-based 

paint and the availability of other lead exposure sources. The results suggest that grantees 

should consider local conditions when developing their lead hazard control strategies. 

• The enrolled population had a lower level of education, lower income and a higher 

percentage of non-white individuals than the general US population. This finding 

matches expectations for a population more at-risk of lead poisoning who predominantly 

lived in central city areas in the Northeast and Midwest. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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• Nearly half of the children in the Evaluation had an initial blood lead test that was at or 

above the CDC level of concern (10μg/dL). Pre-intervention, 46% of children tested had 

a blood lead level greater than or equal to 10 μg/dL and 15% of children had a blood lead 

level at or above 20 μg/dL. 

• A high percentage of the children enrolled in the study were previously lead poisoned. 

Seventy-seven percent of children enrolled in the Evaluation had a blood test for lead 

prior to enrollment. Forty percent of these children were reported to have been lead 

poisoned. With 85% of all children living in the enrolled dwelling more than 6 months, 

the dwelling was a potential source of lead exposure for most of these children. 

• The findings for blood lead were not based on a random sample of children in the 

communities studied, and reflect grantee enrollment strategies. Not only were the 

children in this study more at risk, but a number of them were selected because they were 

lead poisoned. Thus, it not surprising that 46% of children had blood lead levels above 

the CDC level of concern as compared with less than 5% of the US child population. 

Interventions and Costs: 

• Costs for interior lead hazard control work increased with the intensity of the 

interventions. Cost data reflect lead hazard control costs in the mid-1990s. Median costs 

were as follows: 

Interior Strategy Primary Activity Median Cost 

 02 Cleaning Only/Spot Painting $ 430 

 03 Full Paint Stabilization $ 4,930 

 04 Partial Window Treatments $ 6,120 

 05 Full Window Abatement $ 6,800 

 06 Full Lead Abatement $ 9,570 

 07 Full Lead Removal $ 4,110 

 All $ 5,960 

Interior Strategy 07 did not follow the increasing trend in costs because it was most 

commonly conducted in homes with a limited number of leaded components. Note: Partial 

window treatments include window jamb liners, sash replacement or paint removal, as well as other 

treatments.

• Grantees most often selected Interior Strategy 05 - full window abatement (window 

replacement or window paint removal) plus other interior treatments for their interior 

intervention. Fifty-five percent of dwellings were treated with Interior Strategy 05 as 

compared with: Strategy 02 (8%); Strategy 03 (13%); Strategy 04 (16%); and Strategies 

06/07 (7%).

• Costs varied widely within Interior Strategies. Factors that influenced the variability of 

costs included the size and type (single-family/multi-family) of the dwelling; the 

percentage of leaded interior paint in poor condition; the number of dwellings treated by 

the contractor for the grantee; and whether hazardous waste requirements were placed on 

the contractor. 

• Grantees treated the exterior of the buildings at 70% of the dwellings and conducted soil 

or site work at 13% of the dwellings. The most common combination of strategies was 

Interior Strategy 05 along with treatments to the exterior and no soil treatment (41%).
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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• Exterior work most frequently included paint stabilization (84% of treated buildings), 

followed by component enclosure (29%), component replacement (26%) and paint 

removal (25%). The median cost of exterior work was $1,870. 

• Site work most frequently included mulch/seed/sod/plant (90% of treated buildings), 

followed by soil enclosure (22%), soil removal (10%), and structure removal (3%). The 

median cost of site work was $1,080. 

• The following individual treatments were used over 800 times by building component: 

Component Paint 

Stabilization 

Paint 

Removal 

Enclosure Replacement 

Wall/Ceiling √ √

Floor/Stair √ √

Doors √ √

Trim √ √ √

Windows √ √ (jambs) √

Exterior √ 

Effects of Interventions on Clearance Dust Lead: 

• Seventy-six percent of all 2,842 dwellings treated by grantees passed the initial clearance 

testing (using the local dust lead standards applicable at the time). The findings offer 

strong evidence that clearance was achievable on the first attempt in the vast majority of 

interventions. During the period of the Evaluation, grantees generally used clearance 

standards of 200 μg/ft2 on floors, 500 μg/ft2 on window sills and 800 μg/ft2 on window 

troughs. 

• Dwellings that initially failed clearance testing required an average of 1.13 recleanings 

and follow-up clearance tests to achieve final clearance. Even when dwellings failed 

initial clearance, final clearance was generally successful after only one additional 

recleaning and retest. 

• Interior Strategy 05, the strategy that included window abatement, was associated with 

lower initial clearance dust lead loadings and lower failure rates on both window sills 

and window troughs, after controlling for other factors. Interior Strategy 02, the lowest 

intensity strategy that included cleaning and spot painting, performed as well or better 

than other strategies in similar models based on floor dust lead loadings and failures. 

Initial clearance dust lead loadings and failure rates did not decline with treatment 

intensity. Interior Strategy 06, full lead abatement, was associated with higher clearance 

dust lead loadings on both floors and window troughs than most other strategies, after 

controlling for other factors. As reported above, Interior Strategy 02 had lower dust lead 

loadings on floors than other strategies. This same strategy had similar effects on window 

sill dust lead loadings, as long as pre-intervention dust lead levels were below 250 μg/ft2. 

• Creating smooth and cleanable surfaces was an important determinant of lower 

clearance dust lead levels. Surfaces in better condition at clearance had lower clearance 

dust lead loadings and lower failure rates, when controlling for other factors including 

Interior Strategy. In fact on entry floors, no elements of the interior lead hazard control 

interventions other than creating good floor conditions had a significant effect on entry 

floor clearance failure rates. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Occupant Protection: 

• Grantees generally followed HUD guidance on occupant protection and occupants were 

generally adequately protected. 71% of households were relocated during the 

intervention, and when relocation did not occur, treatments tended to be of a more limited 

intensity. Twenty-two percent of relocated households reported that they returned to the 

dwellings during the intervention, although in most cases the return visits were less than 

one hour and did not include a child. Ninety-two percent of the households that did not 

relocate remained out of the work area and 80% reported that all dust and debris was 

cleaned up at the end of the day. Eighty-eight percent of relocated households and 85% of 

non-relocated households felt that they were adequately protected during the intervention. 

• Nine percent of the 869 children who had both pre-intervention and immediate postintervention blood lead samples had blood lead increases equal to or greater than 5 

μg/dL. This can be compared to a study completed in the 1980s, in which over 50% of 

children in homes that had undergone the ìtraditionalî form of lead abatement (without 

dust lead cleanup) exhibited a significant increase in blood lead (Farfel 1990). Analysis 

of children in the Evaluation with blood lead samples at pre-intervention and immediate 

post-intervention did not reveal any differential effects between interventions on the 

probability of a child experiencing a blood lead increase equal to or greater than 5 μg/dL, 

suggesting that the increase was probably not related to the intervention itself. Statistical 

analysis found that in a number of cases, the increases may simply have been a function 

of the childís age or the season in which the blood sample was drawn (blood lead levels 

tend to increase during the summer. 

• When grantees felt that households did not need to be relocated or could be partially 

relocated, the children were as protected (when measured by change of blood lead 

increases) as when grantees felt that households had to be relocated. The relocation 

status of the household did not have a significant effect on the probability that a child 

would experience a blood lead increase of 5 μg/dL or more from pre-intervention to 

immediate post-intervention. However, grantees did report that nine of the 81 children 

whose blood lead levels ìspikedî may have experienced increases because of 

breakdowns in the occupant protection system. This suggests that grantees must remain 

vigilant in enforcing occupant protection practices and offering households the necessary 

support and incentives to stay out of the work areas. 

Effects of Interventions on Dust Lead Loadings: 

• Lead hazard control activities undertaken by the grantees dramatically reduced the floor 

dust lead loadings and those levels were maintained for at least three years. The 

interventions were equally effective on window dust lead loadings. Three years postintervention geometric mean dust lead loadings on floors, window sills and window 

troughs were 9, 62 and 363 μg/ft2

, respectively. These levels represented declines of 

78%, 89%, and 95%, respectively, from pre-intervention. Substantial declines were 

observed across all 14 grantee sites. 

• Although all interior strategies resulted in average floor dust lead loadings at one-year 

post-intervention that were well below the current hazard standard of 40 μg/ft2, 

differential effects between Interior Strategies were identified. Controlling for other 

factors, full interior lead abatement (Interior Strategy 06/07) was associated with the 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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largest relative reductions in floor dust lead loadings from pre-intervention to one-year 

post-intervention, while dwellings treated with window abatement (Interior Strategy 05) 

or full paint stabilization (Interior Strategy 03) had the smallest reductions. 

• Interior Strategy 05 was as effective at reducing floor dust lead loadings as most other 

strategies at clearance, but unlike homes treated with other interventions, something 

occurred in the Interior Strategy 05 homes between clearance and six months postintervention that increased the geometric mean floor dust lead loadings. Floor dust lead 

loadings in dwellings treated with Interior Strategy 03, 04, and 06/07 declined from 

clearance to six-months post-intervention, while loadings in dwellings treated with 

Interior Strategy 02 remained constant. The Evaluation was not able to identify the reason 

for the differences between interventions. 

• As with floors, Interior Strategies had different effects on post-intervention window dust 

lead loadings. The effects more closely matched original expectations that higher 

intensity interventions would result in larger relative reductions in window dust lead 

loadings. Interventions where windows were abated (Interior Strategies 05 and 06/07) 

were associated with the largest reductions from pre-intervention to one-year postintervention, while interventions where windows were only cleaned (Interior Strategy 02) 

had the smallest reductions. 

• Dust lead loadings on window sills and troughs all increased dramatically from 

clearance to six months post-intervention and then declined through three-years postintervention, regardless of Interior Strategy. Window dust lead loadings were higher at 

three years post-intervention than at clearance, but were substantially lower than preintervention. Because similar changes occurred in both dwellings where windows were 

abated and where they were unabated, it does not appear as though the windows 

themselves were a likely source of the immediate increase in dust lead.

• While window abatement was demonstrated to be the most effective measure to reduce 

dust lead loadings on windows, this treatment must be performed in conjunction with 

other treatments that influence predictors of floor dust lead (e.g., floor surface type and 

condition, door and trim paint lead, and general interior building condition, as well as 

exterior dust/soil lead) in order to most effectively reduce floor dust lead levels. Although 

pathway analysis suggests that window dust lead influences floor dust lead, only treating 

ìup-streamî hazards would not result in substantial ìdown-streamî dust lead reductions. 

Furthermore, window dust lead loadings increased substantially shortly after clearance 

without influencing the floor dust lead loadings up to three years after treatment. These 

findings support the current requirement to address all interior, exterior and soil lead 

hazards in an integrated manner. 

• Both exterior and soil lead hazard control work influenced reductions in postintervention floor dust lead loadings. Interior floor dust lead loadings in dwellings not 

receiving exterior treatments were predicted to be 32 percent higher than the dwellings 

receiving exterior treatments, while floor dust lead loadings in dwellings not receiving 

soil work were predicted to be 45 percent higher than dwellings receiving soil treatments. 

For the average dwelling, the floor dust lead loading at one-year post-intervention was 3-

4 μg/ft2 higher if the dwelling did not receive one of the interventions to the outside of 

the building or its immediate surroundings. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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• Exterior entry dust lead loadings were found to contribute directly to interior entry floor, 

floor, and window sill dust lead loadings. This finding suggests that treatments to control 

exterior entry dust lead may reduce interior dust lead loadings. 

• Site treatments (mainly interim soil controls) were associated with lower postintervention exterior entry dust lead loadings. Because of the impact of exterior entry 

dust lead levels on interior dust lead levels, these treatments also reduced dust lead 

loadings on window sills, interior entries and other interior floors. 

• Evidence of blow-in or track-in of lead from street dust was not observed. The study 

shows that street dust does not serve as a significant source of lead in exterior entry dust 

because exterior entry dust lead concentrations were about four times as high as street 

dust lead concentrations. Therefore, street dust lead did not appear to be tracked into 

dwellings. Furthermore, street dust lead was not associated with window sill or trough 

dust lead loadings. 

• Window replacement was associated with lower window sill and window trough dust 

lead loadings one-year post-intervention compared to installation of window jamb liners, 

window paint stabilization or cleaning only. At three years post-intervention, available 

data were more limited, but window sill and trough dust lead loadings were lower in 

dwellings with window replacement than those with cleaning only, after controlling for 

other factors. 

• Although rooms treated with paint removal are likely to have more dust lead at 

clearance, there did not appear to be a long-term detrimental effect of paint removal 

activities. Rooms treated with paint removal had clearance dust lead loadings on bare 

floors that were 60% higher than loadings in rooms not treated with paint removal. 

However, at one and three years post-intervention, the geometric mean dust lead loadings 

were no longer significantly different for rooms treated with paint removal or not, after 

controlling for other factors. 

Treatment Longevity: 

• Lead hazard control treatments tended to hold up for the three-year period for which they 

were observed. The median dwelling in the Evaluation had only one physical failure two 

and three years post-intervention. Ten percent or less of the roughly 66,000 treatments 

analyzed were in a state of failure at any of the post-intervention phases (6 months: 4%, 1 

year: 6%, 2 years: 9%, and 3 years: 10%). 

• Failures appeared to level off two years after clearance. The percentage of failures rose 

quickly over the first year, then more slowly over the next two years. Since most if not all 

of the treatments were expected to least three years, the early rise in failure rates suggests 

that these failures were more attributable to poor installation or poor surface preparation 

than to product failure. 

• Components subject to abrasion, impact or weather were more likely to experience paint 

failure than other components. During each post-intervention phase, paint stabilization of 

doors, windows and exterior components was more than twice as likely to fail than paint 

stabilization of interior trim and interior walls and ceilings. 

• Installation of window jamb liners was the treatment category that had the highest 

percentage of failures in each phase. Six months after installation, 17 percent of rooms 

where jamb liners were installed had at least one jamb liner failure, while three years 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

ES-8

after intervention, nearly half of the rooms with jamb liners failed (46%). This was twice 

the failure rate of the next most frequent failure (door paint stabilization). Over half of the 

jamb liner failures were attributed to inadequate installation and 29 percent failed because 

they were physically damaged. 

• Although further study is needed, the Evaluation suggests that encapsulation does not 

perform better than paint stabilization. Strong conclusions are not possible because only 

358 trim components and just over 100 wall/ceiling components were encapsulated (as 

compared with 10,025 trim and 7,949 wall/ceiling components that were paint stabilized). 

However, by two years after clearance, encapsulants had similar failure rates as paint 

stabilization on these components. 

Effects of Interventions on Blood Lead Levels: 

• Interventions selected by grantees were quite successful in reducing blood lead levels. 

Blood lead levels were significantly lower at each successive post-intervention phase 

until three-years post-intervention, at which time blood lead levels were not significantly 

different than at two-years post-intervention. At two-years post-intervention, geometric 

mean blood lead levels were 37 percent lower than at pre-intervention. Blood lead levels 

were 18 to 30 percent lower one-year post-intervention, which corresponds to declines in 

blood lead levels observed in previous studies of lead hazard control interventions (18-

34%) (USEPA, 1995). 

• Children with pre-intervention blood lead levels as low as 10 μg/dL (the CDC level of 

concern) experienced substantial declines in blood lead level following interventions. 

Previous studies had not observed substantial declines unless a childís pre-intervention 

blood lead level was above 20 μg/dL. 

• The results support the hypothesis that declines in residential dust lead loadings (as well 

as correction of deteriorated lead-based paint) resulted in lower blood lead levels. 

Although the link between dust lead and blood lead that was observed pre-intervention 

was not significant one-year post-intervention, it is likely that the relationship could not 

be observed because the childís body burden of lead became a better predictor of postintervention blood lead. The correlation between pre-intervention blood lead levels and 

floor dust lead loadings (0.29, p<0.01) was very similar to the correlation one-year postintervention (0.32, p<0.01). 

• No differential interior strategy effect was noted for declines in blood lead. The 

hypothesis that differences in lead hazard control intervention intensity would yield 

differences in blood lead levels was not demonstrated. For the four interior strategies that 

were examined in the one-year post-intervention blood lead models (Interior Strategies 

02-05), window sill and window trough dust lead loadings were significantly lower in 

dwellings where windows were abated (Interior Strategy 05). However, interior floor 

dust lead loadings were not significantly lower in these same dwellings. Assuming 

interior floor dust lead is the primary exposure pathway of dust lead to a child, as 

established by the pre-intervention model and previous research, this finding may suggest 

a reason why Interior Strategy 05 did not prove to be more effective than the other 

interior strategies. 

• Exterior lead hazard control in the presence of high exterior paint lead loadings was 

related to differences in one-year post-intervention blood lead. Children living in 

dwellings where the exterior paint lead levels were above 7 mg/cm2

 and the exteriors 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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were treated had lower post-intervention blood lead levels than children living in 

dwellings without these conditions. 

• Important factors that modified the effects of strategies on blood lead levels included preintervention blood lead levels, parental report of previous lead poisoning, childís age, 

and season. When controlling for all other factors, children who were reported to be lead 

poisoned prior to enrollment and/or had higher pre-intervention blood lead levels also had 

higher post-intervention blood lead levels. Even after intervention, childrenís blood lead 

levels tended to peak for children 24 months of age and when children were tested in the 

summer. This supports the finding that body burden is significantly related to blood lead 

level.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Measures of Effectiveness 

Dust Lead Loading

Inspectors trained in the Evaluationís standard single-surface dust wipe collection protocol collected floor samples 

from the interior entry to the dwelling, and doorways in the youngest childís playroom (or living room), that childís 

bedroom, a second childís bedroom and the kitchen. Interior window sill samples were collected from the youngest 

childís bedroom and kitchen. Window trough samples were collected from the childís playroom and second childís 

bedroom. The inspector determined the exact sampling locations based on the availability and operability of 

windows and the presence of a second childís bedroom. Inspectors returned to the same sampling locations in each 

phase of the evaluation. Inspectors alternated the exact location of the sampling from one side to the other of the 

doorway or window in each phase, to reduce the possible influence of the previous sampling. 

Each grantee selected its own laboratory (or laboratories) to analyze the dust samples. Each laboratory provided 

evidence that it was proficient under the American Industrial Hygiene Associationís Environmental Lead Proficiency 

Analytical Testing Program. Laboratories were not required to be accredited under the EPA National Lead 

Laboratory Accreditation Program because the study began early in that programís existence and few laboratories 

were as yet recognized. Lead was measured by flame atomic absorption, graphite furnace atomic absorption, or 

inductively coupled plasma-atomic emission spectrometry. 

Grantees submitted both blank wipe samples and double-blind quality control samples to the laboratories on a regular 

basis. The quality control samples were prepared by the Wisconsin State Occupational Health Laboratory by 

applying set quantities of NIST Standard Lead Paint Dust (Standard 1578) to a wipe. Dust samples analyzed during a 

period when a laboratoryís values exhibited a pattern of deviation by more than 20 percent from the target values are 

excluded from this report.

The method detection limits of the laboratories varied from 1 to 25 μg/ft2. Midway through the evaluation, it was 

determined that many dust lead results (e.g., about one-half of the post-intervention floor dust lead values) were 

falling below the limits of detection. Because the values would restrict the observations of changes in dust lead 

levels, the evaluators asked the laboratories to provide the instrument reported value for future samples and 

previously reported samples. The instrument value, when available, is used in this report. Where the instrument 

value was not available, values below detection limits were assigned a value using imputation. 

Blood Lead Concentration

Trained phlebotomists obtained blood specimens from participating children, primarily by venipuncture. On a caseby-case basis, a phlebotomist could make a determination that a venous sample was unattainable and collect a 

capillary sample instead. Three grantees received approval to use capillary sampling (fingerstick) as their primary 

blood collection method. Phlebotomists at these sites received training in proper fingerstick techniques. 

Each grantee selected its own laboratory (or laboratories) to analyze the blood specimens. Each laboratory was 

required to meet the proficiency standards set under the Clinical Laboratory Improvement Act of 1988. Lead was 

measured by either graphite furnace atomic absorption spectrophotometry or anodic stripping voltammetry. The 

limits of detection varied by laboratory from 1 to 5 μg/dl. Undetectable levels were assigned a value using 

imputation. 

Grantees submitted blinded quality control samples to the laboratories on a regular basis. CDC prepared the quality 

control samples from whole bovine blood pools. The evaluation quality control officer worked with any laboratory 

whose performance fell outside of the quality control standards set in the study protocols (more than 3 μg/dl different 

from the target value). Blood samples analyzed during a period when a laboratory fell outside of the standards are 

excluded from this report. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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1.0 INTRODUCTION 

1.1 BACKGROUND

The Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program (the Evaluation) is 

the largest and most comprehensive study of lead hazard control in housing ever undertaken in 

the United States. Data collection efforts were initiated in 1994 by Grant recipients (grantees) 

from 14 State and local governments across the nation and continued until the fall of 1999. With 

over 200 jurisdictions participating in the Grant Program as of the end of FY2001, the number of 

dwelling units and families served by the program is much larger than the numbers contained in 

this report. The Evaluation is a cooperative effort of these 14 grantees, the National Center for 

Healthy Housing (the Center, formerly known as the National Center for Lead-Safe Housing) 

and the University of Cincinnati Department of Environmental Health (UC). The Center, a 

nonprofit organization devoted to helping public and private entities find effective and affordable 

ways to reduce lead hazards in housing, has overall responsibility for the Evaluation. The United 

States Centers for Disease Control and Prevention (CDC) also contributed to the design and 

implementation of the Evaluation. 

Using standard forms and procedures developed for the Evaluation, the grantees have collected 

extensive data on environmental, biological, demographic, housing, cost and hazard 

identification and hazard control aspects of their activities. Under grants from HUD, the Center 

and UC designed the data collection forms and procedures and provided training and technical 

assistance to the grantees. UC performed the central data management role, including training 

and technical guidance in forms completion and submittal, quality control of laboratory and other 

data, and development and management of central data files and design and execution of an 

exterior dust and soil lead project for selected Evaluation housing. The Center and UC worked 

jointly on data analysis and reporting. 

Planning for the Evaluation began in 1993, at the outset of the HUD grant program, to provide 

the earliest possible information to lead hazard control policy makers and program managers.1

 

The Evaluation is broad and complex, as are the programs it was designed to evaluate. 

The overall goal of the HUD grant program is to prevent childhood lead poisoning by reducing 

lead hazards in privately owned low-income housing. The main objectives of the program, as 

stated in the 1992 Notice of Funding Availability (NOFA) (HUD 1992), are to: 

 " (a) Encourage State and local governments to initiate or expand lead-based paint 

inspection, abatement, and training certification programs in order to reduce the 

health hazards associated with exposure to lead-based paint and lead dust, 

especially as these hazards affect young children in low- and moderate income 

households; 

 (b) Encourage State and local governments to plan and implement cost-effective 

testing, abatement, and financing programs, including the testing of innovations 

that can serve as models for other jurisdictions interested in addressing this 

problem. Because of the high costs of eliminating lead-based paint hazards, 

 

1

 Interim reports with findings were issued in March 1996, February 1997 and March 1998. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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particular encouragement is offered for programs that can safely reduce average 

per-unit abatement costs; and 

 (c) Document the health effects of lead-based paint abatement activity by testing 

blood-lead levels of young children before and after abatement has taken place." 

In addition: 

 "grantees will be afforded considerable latitude in designing and implementing 

the methods of [lead-based paint] LBP hazard reduction to be employed in their 

jurisdictions. HUD is interested in promoting innovative and creative approaches 

that result in the reduction of this health threat for the maximum number of lowand moderate-income residents, and that demonstrate replicable techniques that 

are better, faster, less expensive or more effective than current practices." 

Congress, which initiated funding for the grant program as part of the Fiscal Year (FY) 1992 

HUD appropriations bill, specified that the first round of funding constituted a demonstration 

program to examine the efficacy of various lead hazard control strategies. Congress stated that 

pre- and post-intervention dust-wipe sampling as well as initial and follow-up blood tests of 

occupantsí children be conducted in order to assist in quantifying the health benefits of 

intervention. Congress also wanted intervention and cost information to be collected on a houseby-house basis. 

Approximately one year later, Congress passed the Title X of the 1992 Housing and Community 

Development Act, which required HUD to conduct research on: 

• the efficacy of interim controls in various hazard situations; 

• the relative performance of various abatement techniques; 

• the long-term cost-effectiveness of interim control and abatement strategies; 

and 

• the effectiveness of hazard evaluation and reduction activities funded by this 

act. 

The overall purpose of the Evaluation was to measure the relative cost and effectiveness of the 

various methods used by State and local government grantees to reduce lead-based paint hazards 

in housing. The effectiveness in individual granteeís programs was not part of the Evaluationís 

purpose. The nine objectives of the Evaluation were to identify and describe the: 

1. Dwelling unit level costs of applying various environmental intervention strategies and the 

relationship between those costs and the pre-intervention characteristics of the dwelling unit; 

2. Costs of various lead hazard control treatments for different building components; 

3. Proportion of dwelling units undergoing environmental interventions that exceed initial postintervention dust clearance standards, the treatments (including cleanup methods) and 

strategies associated with these exceedances, and the nature and costs of remedial treatments 

required to meet clearance standards; 

4. Changes in dust lead loadings that occur from immediately post-intervention to 6 and 12 (and 

in some cases 24 and 36) months post-intervention and the strategies and treatments 

associated with variation in dust lead re-accumulation rates; 
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5. Factors (such as pre-intervention housing characteristics) that appear to modify the effect of 

different hazard control treatments and strategies on short-term and longer-term changes in 

dust lead loadings; 

6. Changes in the integrity of paint, encapsulants, and enclosures that occur from immediately 

post-intervention to up to 36 months post-intervention; 

7. Changes in blood lead levels among children living in dwelling units before and after 

intervention and among children who move into or are born into dwellings after intervention; 

8. Factors associated with significant (i.e., greater than or equal to 5 micrograms per deciliter 

(μg/dL)) changes in blood lead levels between pre-intervention and immediate postintervention measurements; and 

9. Relationship between changes in dust lead loading and changes in blood lead levels between 

pre-intervention and 6-, 12-, 24- and 36-month post-intervention measurements. 

1.2 OVERVIEW OF REPORT

This final report of the Evaluation offers findings based on data that grantees submitted as of 

June 1, 2000 and updates preliminary findings reported in previous interim reports, presentations 

and in an interim publication (Galke 2001). 

The Evaluation report is organized as follows: 

• Section 2.0, Description of Grantee Lead Hazard Control Programs. A description of the 

lead hazard control programs of each of the 14 grantees is presented, including grant 

administration, enrollment methods and targeted communities, and general types of 

interventions. These descriptions are of the programs as they existed at the time of the 

Evaluation and do not necessarily represent their current designs. 

• Section 3.0, Study Design and Quality Control Methods. The design of the Evaluation is 

summarized. The description includes discussion of the enrollment, informed consent and 

data collection procedures; the data management process; and the data quality assurance and 

quality control plan and outcomes. The statistical analysis plan is summarized. 

• Section 4.0, Pre-Intervention Characteristics and Conditions of Housing and Families. The 

distribution of and variability in pre-intervention housing and demographic characteristics 

and pre-intervention exposure-related factors potentially impacting the effectiveness of 

various interventions are summarized and discussed, and compared with those of the nation 

in general. 

• Section 5.0, Description of Interventions. Methods used to collect testing and intervention 

data are summarized, and the different strategies that categorize lead hazard control work are 

described. Concurrent non-lead construction work is also discussed, including potential 

interaction between such work and lead hazard control interventions. 

• Section 6.0, Costs of Lead Hazard Control Activities. The costs for work done during the 

Evaluation are summarized at two different levels, overall lead hazard control costs for 

dwelling units and specific lead treatment costs. 
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• Section 7.0, Observed Outcomes Immediately Post-Intervention. The outcomes of the 

Evaluation that were observed immediately post-intervention are explored. These outcomes 

include the effects of interventions on initial clearance dust lead loadings and the rates of 

clearance failure, and the success of grantee occupant protection plans. In addition, changes 

in blood lead levels of children within six weeks of the lead hazard control intervention are 

investigated to determine if ìsignificantî increases (set at greater than or equal to 5 :g/dl for 

the purposes of this report) occurred, and if so, why they occurred. 

• Section 8.0 Effects of Interventions on Dust Lead Loadings. The longitudinal effectiveness of 

different intervention strategies on dust lead loadings is investigated. Various analytical 

models are used to identify factors that significantly affect dust lead loadings up to three 

years post-intervention. For a subset of the dwellings, the influence of exterior dust lead and 

soil lead on interior post-intervention dust lead loadings is explored. Although data 

limitations prevented counts of treatment failures to be included in the dust lead models, 

descriptions of treatment failures are presented. 

• Section 9.0, Effects of Interventions on Childrenís Blood Lead Levels. The longitudinal 

effectiveness of different intervention strategies on blood lead levels is investigated. Various 

analytical models are used to identify factors that significantly affect average postintervention blood lead levels and changes in blood lead levels up to two years postintervention. As in the dust lead discussion in Section 8, data limitations prevented counts of 

treatment failures to be included in the blood lead models. 

• Section 10.0, Conclusions: Cost-Effectiveness of Interventions. An overview of the 

effectiveness findings of the previous two chapters is presented, and the advantages and 

disadvantages of the lead hazard control strategies are summarized, including their costs. 

• Appendix A. Evaluation Data Collection Forms.

• Appendix B Summary of Laboratory Quality Assurance/Quality Control (QA/QC) Results. 

Laboratory performance on blood and environmental sample analyses is examined and 

decisions based on such performance are presented. The results of QA/QC checks on 

collected data are presented. This appendix also describes efforts to address laboratory results 

that were initially reported as below the detection limits of the laboratory. These efforts 

included obtaining laboratory instrument output data where available and developing a 

statistical method for estimating remaining below detection limit data. 

Additional Materials include: 

• Compendium to the Final Report. The compendium includes over 100 tables reporting 

findings by grantee. It also contains more details on statistical analysis methods and results. 

• Public Use Dataset Resource Document. This documents contains the updated Evaluation 

protocols and the data dictionary for use with the public use dataset. It also includes the 

quality control/quality assurance plan for the study. 

• Public Use Dataset. A public use dataset will be made available to researchers and other 

people interested in examining these data in new or alternative ways. 
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2.0 DESCRIPTION OF GRANTEE LEAD HAZARD CONTROL PROGRAMS 

 

OVERVIEW OF GRANTEE PROGRAMS

This report is a testament to the hard work of the 14 grantees and the contributions of thousands 

of families in this Evaluation. Although national in scope, this Evaluation was locally driven and 

implemented. Once trained in the protocols specifically prepared for this Evaluation, grantees 

designed their own lead hazard control programs, including the methods of recruitment and the 

treatments that were implemented. This was done so that at the end of the project, the data would 

not only provide the basis for the findings of the Evaluation, but could allow grantees to use their 

data to inform their own programs. 

Although the Evaluation was locally driven, in its NOFA, HUD listed several conditions that 

each grantee was required to meet in implementing its lead hazard control program, including: 

• Written procedures for all phases of testing and abatement; 

• Abatement waste disposal procedures in accordance with EPAís Resource Conservation 

and Recovery Act (RCRA) of 1976; 

• Worker protection procedures in accordance with the Interim Guidelines for Hazard 

Identification and Abatement in Public and Indian Housing (HUD 1990); 

• Occupant protection requirements in accordance with the Uniform Relocation Assistance 

and Real Property Acquisition Policies Act of 1970 (URA); and 

• Compliance with post-abatement dust wipe test clearance thresholds contained in the 

HUD Interim Guidelines. 

Grantees were also prohibited from utilizing dangerous methods of paint removal, including 

open-flame burning and uncontrolled abrasive blasting, or machine sanding without HEPA 

attachments. 

Eleven of the 14 grantees were from the first round of Grant awards (FY 1992 appropriations), 

and three were from the second round (FY 1993 appropriations). Under the Congressional 

mandate, HUD required all first round recipients to participate in the Evaluation. Three grantees 

from the second round (Chicago, New York City and Vermont) were invited to participate on a 

voluntary basis. They were chosen to increase representation in the Evaluation of rural areas, and 

of large urban areas with multi-unit housing. A list of participating jurisdictions is found in Table 

2-1. Although Milwaukee was a subgrantee of the State of Wisconsin, its program differed in 

structure and timing from that of Wisconsin; therefore, it was treated as a separate site for 

Evaluation purposes. Therefore, although there were only ten Grant awards in the first round, 

there were 11 Round I grantees in the Evaluation. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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TABLE 2-1:Funding Amounts and Jurisdictions for Grantees 

Participating in the Evaluation 

 HUD FUNDING 

GRANTEE FUNDING JURISDICTION ROUND 

 (In Millions) 

Alameda County, CA $4.41 Local 1st 

Baltimore, MD 5.85 Local 1st 

Boston, MA 3.66 Local 1st 

California 6.20 State 1st 

Chicago, IL 6.93 Local 2nd 

Cleveland, OH 3.88 Local 1st 

Massachusetts 6.00 State 1st 

Minnesota 2.79 State 1st 

New Jersey 4.25 State 1st 

New York City, NY 6.75 Local 2nd 

Rhode Island 4.07 State 1st 

Vermont 3.20 State 2nd 

Wisconsin 6.34 State 1st 

 Milwaukee* Local 1st 

Total $64.33

*Milwaukee is a subgrantee of the State of Wisconsin, but it was treated as a separate site for 

Evaluation purposes. 

Because the Evaluation is national in scope, results for the 14 grantees have generally been 

grouped together in this report to summarize findings and identify trends on a national basis. 

However, because grantees were given considerable latitude in designing and implementing their 

lead programs, it is important to summarize each granteeís program so that grantee-specific 

impacts on Evaluation outcomes can be highlighted as appropriate. Each of the 14 grantee 

programs are briefly summarized below, including department(s) responsible for administering 

the program, a description of cities/neighborhoods targeted for inclusion (if any), dwelling unit 

enrollment methods, and general types of lead hazard control interventions selected. Major 

changes or evolutions that may have occurred in grantee programs over the course of the 

Evaluation are noted. Figure 2-1 lists the number of dwelling units treated and cleared in the 

Evaluation by grantee. 

Early results regarding the effectiveness of lead hazard control interventions indicated that, as 

expected, treatments had not failed at 12 months post-intervention. HUD felt that longer periods 

of follow-up measurement were needed to evaluate effectiveness, so in 1995 HUD initiated an 

extension to the basic 12-month Evaluation. The collection of data at 24 and 36 months postintervention is known as the extended Evaluation. In order to collect data in a timely manner, 

eligible grantees were required to have a target number of dwelling units with interventions 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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completed by June 1995. Nine grantees--Alameda County, Baltimore, Boston, California, 

Milwaukee, Minnesota, Rhode Island, Vermont, and Wisconsin--became participants in the 

extended Evaluation. Resource constraints and the desire to get representation from as many of 

the original 14 participating grantees as possible meant that, for some of the grantees, not all 

dwelling units treated by the deadline were funded for the extended Evaluation. 

In a later project that was separately funded, data on post-intervention exterior dust and soil 

levels were collected from selected locations. Chapter 8 provides details on the design, 

methodology and results for this project. 

Descriptions of the lead hazard control interventions use the terms ìabatementî and ìinterim 

controlsî as they are used in Title X of the 1992 Housing and Community Development Act. 

Abatement denotes a class of treatments that permanently removes or encloses/encapsulates 

lead-based paint hazards. HUD defines permanent treatments as treatments expected to last at 

least 20 years. Building component removal, surface enclosure, and complete paint removal are 

common methods of abatement. Interim controls include treatments that eliminate lead-based 

paint hazards, but do so in a manner that is not expected to last 20 years. Wet scraping and 

repainting, friction reduction on windows and doors, and cleaning are common interim control 

methods. 

Figure 2-1: Number of Treated and Cleared Dwelling Units by Grantee

167

393

68

103

120

152

134

223

143

27

420

160

391

181

0

50

100

150

200

250

300

350

400

450

Alameda County

Baltimore

Boston

California

Chicago

Cleveland

Massachusetts

Milwaukee

Minnesota

New Jersey*

New York City

Rhode Island

Vermont

Wisconsin

Data as of: June 1, 2000 - restricted to units that passed clearance

Data from: Forms 01, 11, 15, 19, 20

Data source: UC Table 12

*See Section 2.2.10 for details conserning the low enrollment in New Jersey Number of Dwelling Units
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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DESCRIPTION OF GRANTEE PROGRAMS

Note: The following descriptions are of the programs as they existed at the time of the 

Evaluation, and do not necessarily represent their current designs. 

Alameda County 

Administration. Administration of the lead hazard control program was the responsibility of the 

Alameda County Lead Poisoning Prevention Program (ACLPPP), which collaborated with 

Community Block Development Grant (CDBG) programs in the four participating cities. 

ACLPPP is part of the countyís Community Development Agency. The program utilized a multidisciplinary approach incorporating case management, community education and health 

marketing, environmental and housing services, economic development and training, and data 

management. The program developed a custom software system to monitor and manage services 

and to collect and analyze data through the various stages of case management, hazard 

assessment, and follow-up. 

Targeted Areas. ìHigh riskî census tracts in four Alameda County cities, Alameda, Berkeley, 

Emeryville, and Oakland, were targeted for inclusion in the Evaluation. 

Enrollment Methods. Two types of properties were targeted for inclusion. The first group 

consisted of properties where children with elevated blood lead levels resided or spent significant 

amounts of time. After receiving reports of children with elevated blood lead levels, the program 

conducted public health investigations to determine the source of the lead poisoning. If the 

dwelling was the source, the property was slated for recruitment. Properties and owners were 

then eligible for financial and technical assistance. Additional incentives (e.g., forgivable loans) 

were also offered to owners if they agreed to participate in the Evaluation. 

The second group of properties was identified in a target area consisting of ìhigh riskî census 

tracts in the four participating cities. High risk was determined by assessing the correlation 

between percentage of median income, age of housing and ethnicity. A census tract was 

considered to have a significant risk factor if 50 percent of families had incomes below 80 

percent of the area median income, if 50 percent of housing units were older than 1950, and if 

more than 65 percent of the population were minorities. Medical case management data indicated 

that these census tracts had the largest percentage of lead poisoning cases. 

General Types of Intervention. Initially, ACLPPP developed four general levels of intervention 

based on identified risks. Level 1 focused on immediate dust hazards, especially on friction 

surfaces and in carpet on the interior of the house; Level 2 addressed defective paint conditions, 

especially on interior friction surfaces, but also exterior lead paint hazards on a limited scale and 

soil lead hazards around the house; Level 3 tested paint-on encapsulants on several surface types 

and clean up of driveways and sidewalks (potential sources of interior dust); and Level 4 

involved comprehensive treatment of lead hazards through extensive replacement of interior 

trim, enclosure of deteriorated wall surfaces and encapsulation of lead paint hazards on exterior 

siding. 

As these levels began to be implemented, ACLPPP refined them into a minimum standard that 

required all hazards to be addressed. This often required a mix of intervention strategies from 

cleaning, paint stabilization and permanent abatement. This modified process helped the program 

achieve a minimum standard across all properties while allowing property owners to select more
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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extensive treatments if they desired. Buildings that were treated using this modified process 

received similar treatments, which included a mix of abatement and interim control work on 

interiors, minimal exterior work, and extensive treatment of the soil at some properties. 

Baltimore 

Administration. The Baltimore City Health Department had overall responsibility for 

Baltimoreís Round 1 Grant, under a program entitled the Lead Abatement Action Project 

(LAAP). A substantial portion of the operational functions was subcontracted to Baltimore City 

Healthy Start, Inc., a quasi-public corporation under the Health Department. Healthy Start staff 

enrolled houses, addressed occupant needs, tested houses, developed work specifications, 

provided quality control, and conducted post-intervention hazard control monitoring and testing. 

The Health Department also partnered with Baltimore Department of Housing and Community 

Development staff, who assisted in the development of owner and contractor documents 

concerning lead hazard control and who conducted grant settlements with owners and

contractors. 

Targeted Areas. LAAP originally targeted three neighborhoods in the city. Two of these areas, 

Sandtown-Winchester and Middle East, contain a large percentage of investor-owned properties 

with histories of childhood lead poisoning. The third, Belair Edison, has predominantly owneroccupied units. The grant ultimately expanded to enroll homes citywide. 

Enrollment Methods. LAAP recruited units by providing public information through property 

owner organization, community and neighborhood organizations, health providers, advocacy 

organizations, environmental enforcement program referrals, promotions at community fairs, and 

word of mouth. To enroll a house, the owner needed to request an initial screen and, if the house 

was approved, the owner completed a standard enrollment application. Selection of a qualified 

lead hazard control contractor was the responsibility of the owner, with advice, referral and 

approval by LAAP. 

Baltimore enrolled predominantly scattered site, single-unit rowhouses. The majority of units 

were turnover rental or homeowner conversion projects (in association with a local Habitat for 

Humanity organization). Owner-occupied units and rental occupied units were also funded, and 

relocation benefits were provided to the occupants. 

General Types of Intervention. Owners were required to bring buildings up to basic housing 

standards before work could begin. Many owners made a substantial out-of-pocket investment to 

meet these requirements. The LAAP intervention primarily consisted of intensive level 

treatments to eliminate lead hazards. The typical unit received window replacement, partial floor, 

wall and ceiling treatments, door adjustments or replacements, paint stabilization (interior and 

exterior), basement floor treatments, and cleaning treatments consisting of high efficiency 

particulate (HEPA)-vacuum and wet wash. No soil treatments were undertaken. A small number 

of units underwent substantial rehabilitation resulting in permanent abatement of lead hazards. 

 

Boston 

Administration. The City of Bostonís Department of Neighborhood Development was the lead 

agency with overall responsibility for the Round 1 Grant and associated Evaluation activities. 

The Departmentís Lead Safe Boston (LSB) program was responsible for all programmatic and 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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construction activities including, but not limited to, project enrollment, commitment, contract 

closing, construction management and contractor oversight, testing and reporting. 

LSB partnered with Bostonís Department of Health and Hospitals (DHH) to undertake all 

Evaluation-specific data collection and transmittal activities, including family interviews, blood 

draws, dust sampling and overall management of the data. 

Targeted Areas. The majority of projects enrolled in the Evaluation were in the neighborhoods of 

Dorchester, Roxbury, and Mattapan, which have the highest percentage of lead-poisoned 

children in the city; however, overall, LSB drew projects from the entire city, which is comprised 

of twelve distinct neighborhoods. 

Enrollment Methods. Every project that met the funding eligibility requirements set by HUD and 

Boston for the LSB program was targeted for possible enrollment in the Evaluation. This method 

cast the widest possible net to capture the highest number of eligible units, allowing a direct 

outreach effort by DHH staff in the field. Most dwelling units that were enrolled in the program 

had received an order to abate based on the identification of a lead-poisoned child residing in the 

building. 

General Types of Intervention. In general, the LSB program interventions were governed by the 

Massachusetts Lead Law (105 Code of Massachusetts Regulations 460 and 454 CMR 22). Each 

enrolled project received a comprehensive lead paint inspection report, which met both state and 

Evaluation requirements. Based on inspection findings, specifications were developed for the 

lead hazard control work and the resulting work write-up was reviewed and approved by the 

property owners whose units were being deleaded. Interior treatments included component 

replacement using new wood trim milled to match historic trim, wet scraping of surfaces full 

height, off-site dipping and covering, and a full paint job to ensure that surfaces would be 

cleanable and easy to maintain. Some building exteriors were treated with vinyl siding, others 

were fully painted. Exterior trim was covered with aluminum coil stock if windows were not 

replaced. Many exterior porches were completely demolished and re-built due to the accelerated 

levels of decay, largely as a result of deferred homeowner maintenance. No soil treatments were 

performed. 

California 

Administration. The California Department of Community Services and Development (CSD) 

had overall responsibility for Californiaís Round 1 Grant, which was administered by CSDís 

Lead Hazard Control Program. CSD managed contracts with community-based organizations 

(CBOs) and an interagency agreement with the Department of Health Services (DHS). Initially, 

CSC and DHS worked with the CBOs to identify and screen eligible units. However, the 

impractability of that process soon became evident. 

So as not to hamper the progress of the program, participants began to focus on particular tasks. 

While maintaining overall responsibility for the grant, CSD began to focus on the environmental 

tasksóidentifying and testing units, developing work plans, and completing clearances. DHS 

focused on health-related tasks, i.e., collecting the family and blood data, and on performing data 

management tasks. The CBOs took primary responsibility for intake, education, and completion 

of the lead hazard control work according to the work plans. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Targeted Areas. The grant program focused its efforts in low-income neighborhoods in six 

counties through four CBOs. The CBOs and the areas they targeted were: (1) the Maravilla 

Foundation, which provided services in Los Angeles County including the neighborhoods of 

East Los Angeles, South Central Los Angeles, City of Los Angeles ìKorea Town,î North 

Hollywood and San Pedro; (2) the Metropolitan Area Advisory Commission (MAAC), which 

served San Diego County, with the largest number of units included in the study located in 

National City, and other units located in the Logan neighborhood in the City of San Diego; (3) 

the San Francisco Economic Opportunity Commission (SFEOC), which served San Francisco 

County and had predominantly single-unit structures; and (4) Proteus Incorporated, which 

primarily served migrant and seasonal farm workers in the Central Valley including Fresno, 

Kings, and Tulare Counties. Only a handful of units for the extended evaluation came from this 

CBO. While the information about the work plans for the units from Proteus were included in the 

study, a problem with the results from the laboratory used at that time caused these units to be 

dropped from further study in the extended Evaluation. 

Enrollment Methods. The exact enrollment methods varied by CBO but were generally based on 

finding target age children (i.e., 6 years old or less). In Maravillaís area, CSD met with the local 

health and housing departments to coordinate referrals of children with elevated blood lead 

levels living in units known to have lead-based paint. These units were then referred to Maravilla 

for enrollment. In SFEOCís area, SFEOC coordinated with its Head Start and child care 

programs to find units with children. These units were tested, and if lead was found, they were 

enrolled in the program. In MAACís area, MAAC coordinated with owners of low-income rental 

property that it had previously served through its weatherization program. 

General Types of Intervention. At the start of the program, abatement techniques (e.g., enclosure 

of exterior siding with T1-11 or encapsulants and window and door replacement) were utilized, 

with very high associated costs (i.e., $10,000 to $15,000 per unit). The program changed to a less 

costly method that entailed the stabilization and repainting of many surfaces (including exterior 

siding), thus allowing the completion of more units. The program, however, continued to replace 

windows and doors, frequently integrating weatherization funding to complete such 

replacements. Soil work was infrequently performed. 

Chicago 

Administration. The Chicago Department of Public Health (CDPH) had overall responsibility for 

Chicagoís Round 2 Grant, formally known as the ìChicago Lead-Safe Homes Initiativeî (the 

Initiative) and housed in CDPHís Lead Poisoning Prevention Program (CLPPP). With the 

exception of grant/loan approval, the Grant program used CLPPP staff for all program activities, 

including program administration and budgeting, identification and inspection of housing units, 

construction specification development, contractor bidding and awards, construction 

management and contractor oversight, and final clearance testing. The Chicago Department of 

Housing (CDH) administered the grants and loans made to participating owners. The program 

entered into subcontracts with five local community organizations to provide assistance in 

targeted neighborhoods. Two of the five later dropped out of the program, with one other agency 

and CLPPP assuming their duties. The community agencies coordinated blood sampling of 

enrolled children, arranged for relocation of the enrolled families during construction, scheduled 

and conducted Evaluation interviews with enrolled family adults and caregivers, provided lead 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

2-8

poisoning prevention information to resident families, and worked with property owners during 

construction. 

Targeted Areas. The grant program focused its efforts in 12 city neighborhoods: Austin, East 

Garfield Park, West Garfield Park, Englewood, West Englewood, West Town, Humboldt Park, 

Logan Square, Lower West Side, North Lawndale, South Lawndale, and New City. 

Enrollment Methods. Chicago targeted homes with children having elevated blood lead levels. 

After being notified of a child having a blood lead level above 20 μg/dL, CLPPP sent one of 

their lead inspectors to perform a lead paint inspection and collect dust samples. If lead hazards 

were identified, CLPPP issued a violation notice to the owner based on a Chicago ordinance. 

Owners were required to appear at a compliance hearing and repair deteriorated lead-based paint 

within a certain timeframe. At the hearing, owners were given the opportunity to enroll in the 

grant program, including mandatory participation in the Evaluation. If owners agreed, then 

CLPPP attempted to enroll the household (i.e., family of the poisoned child). This compliancedriven system provided a ready supply of units and households for the Grant program and 

Evaluation. 

General Types of Intervention. After some initial delays in defining a construction strategy, a 

construction specialist subcontractor was hired to oversee all aspects of lead hazard control 

interventions, and helped CLPPP settle on a fairly uniform construction specification that 

combined abatement and interim controls for both interior and exterior surfaces. At first, the 

program experimented with window repair but then found that full window replacement was 

more efficient and not much more expensive. The program also began enclosing damaged plaster 

surfaces with gypsum board (i.e., drywall), rather than repairing them. Other wooden 

components, such as doors and trim, were replaced if simple paint stabilization was deemed 

insufficient. All other interior painted surfaces, including enclosed rear porches, were then 

stabilized and repainted with a high quality latex paint. On the exterior, particularly on 

uncovered porches and stairways, deteriorated surfaces were stabilized and repainted. The 

program did not treat exposed soil. 

Cleveland 

Administration. The Cleveland Department of Public Health administered and managed the lead 

hazard control program, including overall program design, enrollment, medical monitoring, 

inspections, specification approval, abatement monitoring and clearance. The lead program 

subcontracted with three non-profit housing rehabilitation agenciesóCleveland Housing 

Network (CHN), Union-Miles Development Corporation (UMDC), and Famicos Foundationóto 

write specifications and manage abatements. Environmental Health Watch (EHW), a local nonprofit environmental education and advocacy group, managed the evaluation component, 

entering data, managing the evaluation database, and conducting post-intervention inspections. 

Targeted Areas. There were two lead hazard control projects: the Scattered-Site Project (SSP) 

and the Intensive Neighborhood Project (INP). For the SSP, households throughout the city were 

targeted for enrollment based on the presence of a lead-poisoned child identified through 

Clevelandís screening and case management system. Based on an analysis of lead poisoning 

rates and the willingness and capacity of local non-profit housing agencies to participate, the INP 

targeted households in two neighborhoods, Union-Miles and St. Clare-Superior. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Enrollment Methods. Approximately 42% of Cleveland units were enrolled under the SSP, with 

the remaining 58% enrolled under the INP. In addition to targeting households with leadpoisoned children, SSP further focused resources on enrolling any owners who lived within the 

city limits. Once these criteria were met, field staff visited owners and tenants, if applicable, to 

determine interest and low-income eligibility (80% of median income for both owners and 

tenants). Non-profit owners were exempt from the low-income requirement. Once the target 

household was enrolled, residents of other units within the same building were enrolled. 

Buildings had to have no more than four units and the scope of work had to be within the budget 

of the project. 

The INP had two components. The first was the Union-Miles INP, which was located in a small 

area of often contiguous houses and had a significant emphasis on resident education and 

involvement. Field staff conducted door-to-door surveys to identify dwellings that had child 

residents or frequent child visitors, gross exterior hazards, or were located adjacent to a home 

with child residents or visitors. Once these criteria were met, field staff re-visited dwellings to 

determine if owners and tenants met low-income eligibility requirements. Owners did not have to 

be Cleveland residents. Once a target household was enrolled, other residents in the same 

building were enrolled. 

The other component, the St. Claire-Superior INP, involved additional lead remediation in 

previously or concurrently rehabilitated units managed by Famicos, a large non-profit 

community development agency. All occupied units, including a 29-unit low-income apartment 

building, were enrolled by Famicos staff and chosen based on rehabilitation opportunity points, 

in which lead funds could be added to other rehabilitation funds that had already been spent or 

allocated for the building. 

General Types of Intervention. The original SSP treatment strategy usually involved interim 

controls such as interior and exterior spot scraping and priming (no finish painting), enclosure of 

window wells, final cleaning, and covering or seeding of bare soil. At the end of the first year of 

intervention activities, this strategy was modified, primarily to more permanently treat exterior 

paint and windows. In addition to final cleaning and covering/seeding of bare soil, interventions 

were modified to include vinyl siding, window replacement, enclosure of lead-painted floors, 

and finish-painting of interiors. Throughout the SSP, CHN was sometimes able to arrange for 

concurrent workódesigned to address problems such as weatherization, moisture, heating, 

electricalóto be paid for by other funding sources. 

INP treatment strategy utilized a range of less intensive and less costly interventions including 

vinyl siding, replacement windows, final cleaning, and/or covering or seeding of bare soil. The 

above activities were conducted singly or in combination depending on the housing condition 

and project priorities. In the Famicos INP, lead work was coordinated with other previous or 

planned rehabilitation activities. 

Under the Union-Miles INP, prior to the start of work, residents were required to attend two 

classes that addressed childhood lead poisoning issues, proper cleaning techniques, preparation 

of homes for lead hazard reduction work, and maintenance of a lead-safe home. Participants 

returned for additional classes and transformed the class into a regularly scheduled neighborhood 

meeting. They took responsibility for distributing prevention information and teamed up to 

conduct lead-safe cleaning in homes that were not eligible for the program. Some owners of 

treated homes made non-abatement improvements on their own. UMDC arranged for some free 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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materials and paint to be provided and gave technical assistance for such work. In some 

instances, owners of non-abated homes also made visible improvements to their own properties. 

Massachusetts 

Administration. The Department of Housing and Community Development (DHCD) had 

primary responsibility for administering the lead hazard control grant program and worked with 

four subgrantees: Brockton, Chelsea, Lawrence, and Worcester. DHCD also collaborated with 

the Department of Public Health and the CLPPP, which managed the overall Evaluation data 

collection effort and coordinated the work of the four subsites and two large building programs. 

Targeted Areas. Four cities were involved in the Evaluation in neighborhood-based programs: 

Brockton, Chelsea, Lawrence, and Worcester. Also included was a large building program 

involving two large multi-unit complexes in Gloucester and Roxbury. 

Enrollment Methods. Dwelling units were recruited by subgrantees through advertising in local 

publications, conferences with owners, community presentations, and contacts with other 

community groups. Enforcement of the Massachusetts Lead Law also played a role in 

recruitment, generally as referrals through local CLPPP programs or heath care providers. Many 

of the buildings were under existing orders to abate their units because of the presence, at some 

time, of a lead-poisoned child. After dwellings had been recruited, program staff approached 

occupants for recruitment into the Evaluation. Properties with occupants enrolled were included 

in the Evaluation. 

General Types of Interventions. In accordance with the Massachusetts Lead Law, substantial 

abatement was performed on all units. In some situations, this law allowed a form of interim 

control, in which some selected surfacesói.e., those that were not protruding and abrasion or 

friction surfaces--were made intact. All other surfaces, however, had to be abated by paint 

removal, enclosure, approved liquid encapsulants, or component replacement. All of the methods 

were used, although the most typical were paint removal and component replacement. No soil 

treatments were conducted. 

Milwaukee 

Administration. The Milwaukee Department of Health was responsible for the administration of 

the lead grant. They received support from Milwaukeeís Department of Housing and Community 

Development (DHCD), which was responsible for writing scopes of work and working with 

contractors for buildings undergoing high levels of intervention (defined below). The 

collaboration with DHCD on these higher treatment levels was difficult due to the lengthy time 

required to bring buildings receiving federal rehabilitation funds into the lead program. Later in 

the Evaluation, the number of buildings receiving these high treatment levels was reduced, and 

the number of units receiving lower intervention levels was increased. 

Targeted Areas. Milwaukeeís program did not formally target specific neighborhoods but 

conducted work in several of the lowest income neighborhoods in the city, focusing on treating 

older housing in deteriorated condition. 

Enrollment Methods. The city had four levels of lead hazard intervention, as defined below. For 

the two lowest intervention levels, the Health Departmentís Stellar database was used to identify 

children with elevated blood lead levels. For the third and fourth levels of intervention, 

applications for federal general rehabilitation funds were used to enroll buildings. Milwaukee did 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

2-11

take referrals within the Health Department if someone called but did not conduct any direct 

outreach. 

General Types of Intervention Performed. The cityís four levels of intervention were: 

• Level 1: Cleaning intervention and education provided by Health Department staff. 

• Level 2: Interim controls, including minimal-to-moderate lead hazard control measures 

(e.g., minimal scraping and painting of paint hazards, limited encapsulation) with no 

concurrent work. 

• Level 3: Some abatement strategies, including intensive scraping and painting and 

enclosure/encapsulation; deteriorated and non-deteriorated lead-based paint treatment; 

and variable concurrent work. 

• Level 4: Substantial housing rehabilitation and abatement, including intensive scraping 

and painting, extensive component encapsulation and/or enclosure, and intensive 

concurrent work. 

Although some pre-intervention soil samples were collected, no soil treatments were performed. 

Milwaukeeís program was unique in its conscious decision to have these four distinct levels of 

lead hazard control Efforts were made to assign these four treatment levels in housing with 

similar conditions so that the effectiveness of the levels could be compared. Milwaukee also had 

one of the lowest cost intervention levels. Their Level 1 cleaning intervention involved mainly 

the cost of cleaning materials and staff time required to visit a unit, show residents how to clean, 

and provide other education on lead safety. 

Minnesota 

Administration. Although the grant was administered by the Minnesota State Housing Finance 

Authority, most of the programmatic responsibilities were delegated to three subgrantees: St. 

Paul Department of Health, Minneapolis Department of Health and Family Support, and Duluth 

Housing and Redevelopment Agency. 

Targeted Areas. Specific neighborhoods were not targeted in any of the three subgrantee cities. 

Enrollment Methods. St. Paul and Minneapolis targeted homes with children having elevated 

blood lead levels. Although Duluth originally planned to address children having elevated blood 

lead levels, no children with blood lead levels exceeding 19 μg/dL were found. Therefore, the 

Duluth program switched to a direct outreach to low-income families, targeting low-income 

families with deteriorated housing conditions in areas that were identified in the Community 

Action Programís database, with mailings and advertisements in the local newspaper. People 

who applied to use funds under Duluthís CDBG program were informed about the lead program 

and encouraged to apply. 

General Types of Intervention. All three grantees addressed all deteriorated lead paint hazards 

using some type of interim control, including paint stabilization and friction control. Treatments 

included the repair or replacement of all friction surfaces (e.g., windows, doors, and 

floorboards), repair or covering of interior lead-based paint, some exterior repair (e.g., enclosure 

with vinyl siding or other coverings) and repainting of leaded surfaces, repair or replacement of 

floor coverings, and some soil remediation. In Minneapolis, thirty units underwent a clean-only 

intervention. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Both St. Paul and Minneapolis signed a fixed-price contract with one contractor to perform all 

lead hazard control work; each directly paid the contractor. The contractor and the program 

manager agreed on the scope of work for each home from a set of specifications that were 

developed precisely for the program. This system proved efficient in the beginning when only a 

few contractors were certified. As more certified contractors became available, the cost of the 

bidding approach decreased, and the two grantees moved to bidding out the work to more 

contractors, including community action programs and non-profit weatherization groups. On the 

other hand, Duluth bid out their lead jobs. To ensure that the homes of lead-poisoned children 

were at least cleaned of immediate lead hazards in a timely manner, Minnesota state law required 

that such homes be addressed with a SWAB team within a week of being identified. St. Paul 

found that in most cases the contractor could respond just as quickly so did not use a SWAB 

team approach. 

New Jersey 

Administration. The Division of Housing and Community Resources in the New Jersey 

Department of Community Affairs (DCA) had responsibility for New Jerseyís Round 1 Grant. 

Targeted Areas. Although the Grant originally included 11 subgrantee cities: Asbury Park, 

Beverly, Camden, Elizabeth, Englewood, Irvington, Jersey City, Newark, Paterson, Pemberton 

Township, and Woodbine. Subsequently, however, Asbury Park, Beverly, and Pemberton 

Township withdrew. 

Enrollment Methods. The primary focus of this Grant program was to integrate lead hazard 

control with moderate to comprehensive housing rehabilitation in the subgrantee cities. Property 

owners already eligible for rehabilitation funding were also offered the opportunity to obtain 

funding for lead hazard control. The presence of an elevated blood lead child was not a factor in 

enrolling either dwelling units or households. Many units were already vacant when enrolled. 

Although new families who moved in upon completion of the work were asked to participate, 

none did. 

DCA worked hard to convince the local subgrantees of the merit of including lead in their 

rehabilitation programs and made presentations at property owner meetings convened by the 

subgrantees; however, only 28 units were enrolled in the Evaluation--26 in a garden-style 

apartment building in Paterson and two in a duplex in Irvington. 

General Types of Intervention. Once units were identified, a subcontractor to DCA performed a 

lead paint inspection and collected dust samples according to the HUD Evaluation Protocol and 

developed lead-related construction specifications based on the programís goal of making 

dwelling units lead free or to abate all lead hazards. Interior and exterior surfaces in the 23 

enrolled units were fully abated. There were no soil treatments or interventions. 

The construction process was slow, in part due to the fact that DCAís abatement contractor 

regulations were not signed until 1995 and did not become effective until January 1996. It then 

took at least six months before a cadre of contractors was trained and approved for the programís 

contractor bidding list. Housing rehabilitation programs in the subgrantee cities experienced an 

overall slow down in work during this period. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

2-13

New York City 

Administration. Although the New York City Department of Housing Preservation and 

Development (HPD) was responsible for the administration of the Grant, duties were split 

between HPD and the City Health Department. HPD inspectors performed initial x-ray 

fluorescence (XRF) testing, initial visual inspections and dust wipe sampling. Health Department 

staff collected blood samples, conducted household interviews, and performed some postintervention dust wipe sampling. Outside contractors performed the interventions. Both 

departments were involved in quality assurance/quality control (QA/QC) of forms, but the 

Health Department was responsible for data entry. While many staff changes occurred, these 

basic departmental responsibilities remained constant over the course of the Evaluation. 

Targeted Areas. HPDís program blended lead grant funds with their ongoing housing 

rehabilitation program and generally made funds available in various neighborhoods throughout 

the city. One initiative, however, called the Primary Prevention Program (PPP), targeted 

neighborhoods having a high incidence of elevated blood lead levels, including Bedford 

Stuyvesent and portions of Crown Heights, Fort Greene, and Bushwick. 

Enrollment Methods. Although the PPP originally intended to use local health clinics to identify 

expectant or new mothers and help focus on families with newborn babies living in deteriorated 

housing, progress was very slow and insufficient units were identified; therefore, HPD switched 

to a more direct and aggressive outreach program, focusing on three enrollment methods: 

1. Buildings that were receiving funds through the Neighborhood Reinvestment Program (NRP) 

for total rehabilitation received $10,000 per unit in lead funds for lead-safe demolition and 

renovation. 

2. Two buildings that were receiving funds for moderate rehabilitation through the Participation 

Loan Program (PLP) also received $5,000 per unit for lead hazard control. 

3. Under the PPP, notices were sent to all owners of buildings with three or more units built 

prior to 1960 in the target neighborhoods explaining the program and asking for their 

participation. Notices were also sent to community organizations and churches, and flyers 

were widely distributed. HPD and the Health Department staff held several public meetings 

at HPD to explain the program and began to build a database of potential buildings. This 

publicity generated many word-of-mouth referrals, and in the end, more buildings were 

identified through word-of-mouth than from informational meetings. 

General Types of Interventions Performed. The NRP involved gut rehabilitation, where the entire 

interior of the unit was removed, including a sizeable percentage of the plaster walls. If the 

plaster was not removed, it was covered by wallboard. Lead funds were used to gut the building 

in a lead-safe manner and to provide funds for the windows, doors and other features of the unit 

that would contribute to lead safety. In the PLP, units were moderately rehabilitated, i.e., only 

very deteriorated plaster was removed or covered with wallboard, and most windows were 

replaced. The scope of work for the PPP was more limited: all interior surfaces were scraped 

and painted, some windows were replaced if very deteriorated, and emphasis was put on 

reducing lead on deteriorated, friction, and impact surfaces. New York did not conduct any soil 

work. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Rhode Island 

Administration. For most of the Round 1 grant period, the program was administered by the 

Rhode Island Department of Health. The Health Department managed all aspects of the project 

including housing related activities. A unique characteristic of the Rhode Island program was its 

reliance on outside contractors to do the inspections, risk assessments and job specifications as 

well as lead hazard control work. Program officials consciously chose this method in order to 

help ìgrowî the industry in Rhode Island. 

When the Rhode Island Housing and Mortgage Finance Corporation was awarded a Round 3 

Grant in late 1997, they also assumed responsibility for program administration for the 

Evaluation. At that time, all Round 1 interventions were complete, but follow-up inspections and 

data management were ongoing. Inspectors transferred to the Housing agency, while the project 

manager and data manager continued to function out of the Health Department. Responsibilities 

for phlebotomy were contracted out to a local hospital to complete post-intervention sampling. 

Targeted Areas. Rhode Island worked through 22 local housing offices located across the state. 

Enrollment Methods. Eighty percent of the children in the Rhode Island Evaluation were 

recruited because they had elevated blood lead levels. Owners of buildings were cited for 

violations due to this lead poisoning. The Providence Housing Court had information on the lead 

program and ordered participation if owners were brought to the court for violations. In addition, 

local housing offices identified some houses through their housing rehabilitation programs. For a 

unit to be enrolled, it had to meet Section 8 Housing Quality standards, and the owner could not 

own more than 12 units. 

The program originally intended that local housing agencies would take an active role in 

identifying potential properties. When this did not occur, the program changed its focus to fixing 

the homes of lead-poisoned children. 

Over the course of the Evaluation, the program also changed its relocation policy from one of 

using hotels to one of using transitional housing operated by a non-profit group. Instead of 

paying for alternative housing, they also gave stipends to people who stayed with friends and 

family. 

General Types of Interventions Performed. The typical lead hazard reduction activities included 

replacement of windows, doors, and molding; interior and exterior scraping and painting or 

siding of exteriors; and soil remediation. The average cost was approximately $8,000 to $10,000 

per unit. Scopes of work were prepared by outside risk assessors and approved by program staff. 

Vermont 

Administration. The Vermont Housing and Conservation Board was responsible for program 

administration. Community nurses from the Health Department conducted household interviews, 

drew blood samples, and collected some dust wipe samples. 

Targeted Areas. Vermontís funds were available and used throughout the state. In accordance 

with Act 156 of the 1996 Vermont Lead Law, one low-level program targeted the Old North 

End of Burlington for a special low-level project utilizing ìEssential Maintenance Practices 

(EMP),î as described below. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Enrollment Methods. Vermont enrolled units from several different sources, including the 

Vermont Health Department, which referred families with lead-poisoned children; non-profit 

housing developers that learned of the program when they applied for federal HOME funds; and 

unsolicited applications. The EMP units were recruited through a mailing to owners in the target 

neighborhood. 

General Types of Interventions Performed. Vermont performed a wide range of treatments. Most 

of the units receiving HOME funds underwent moderate to full rehabilitation, while other units 

generally underwent only those treatments necessary to reduce lead hazards, typically including 

window treatments (replacement or repair), treatment of friction surfaces, stabilization of loose 

and flaking lead-based paint, and exterior repainting. EMP units were cleaned, limited areas of 

paint were stabilized, and caps were installed over window troughs. A unique aspect of 

Vermontís program was that almost every private homeowner undertook at least part of the 

intervention work, most often repainting, but sometimes rebuilding and other more extensive 

renovation work. Although some pre-intervention soil samples were collected, Vermont rarely 

performed soil treatments. 

Vermont originally intended to spend only $1,599 per unit on intervention but soon discovered 

that this amount was insufficient and increased it to $3,000 by the end of Round 1. By the end of 

the Evaluation, excluding the EMP project, interventions cost between $7,000 and $8,000 for an 

apartment in a multi-family building and between $8,000 and $10,000 for a single-unit home. 

Wisconsin 

Administration. Although the program was administered by the Wisconsin Division of Health, 

whose staff inspected, tested and completed preliminary specifications on the units, many of the 

program design decisions were made locally by 12 subgrantees. (For the purposes of the 

Evaluation, Milwaukee was treated as separate grantee, and is not one of the 12 Wisconsin 

subgrantees.) These subgranteesóChippewah Falls, Eau Claire, Madison, Manitowoc, Oshkosh, 

Richland, Rockland, Seboygan, Superior, Wausau, West Allis, and Wisconsin Rapidsóselected 

the units, negotiated the final specifications with the owners, put the specification packages out 

for bid and picked the contractor, then notified the local health departments to begin household 

interviews and dust wipe sampling. One of the subgrantees dropped out of the program during 

the Evaluation. Because of the decentralization of the program, State staff had to increase their 

monitoring of contractors to ensure that the work was done according to specifications. The 

Wisconsin Department of Housing was responsible for paying the contractors. 

Targeted Areas. The twelve subgrantees were distributed across the state. 

Enrollment Methods. Since local housing departments were responsible for selecting units, 

criteria for recruitment and selection of dwelling units differed from place to place. Some of the 

methods included: (1) units participating in federally funded rehabilitation projects; (2) housing 

units having children with elevated blood lead levels; and (3) outreach to owners of housing 

identified as high risk (i.e., older housing in deteriorated condition). 

General Types of Interventions. Types of interventions varied from city to city, depending on the 

condition of housing and the extent of lead hazards present. The type of treatment also depended 

on how the units were brought into the program and if the city combined the lead grant with 

other housing rehabilitation funds. Typical treatments included repair of deteriorated paint, 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

2-16

replacement or repair of friction surfaces (e.g., windows, doors, and baseboards), floor (carpet, 

linoleum, or painted) repair or replacement, and exterior repainting. Although no subgrantee 

performed any soil remediation, some did collect pre-intervention soil samples.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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3.0 STUDY DESIGN AND QUALITY CONTROL METHODS 

3.1 DESIGN OF THE EVALUATION 

A challenge for the Evaluation designers was to develop a way to judge the cost-effectiveness of 

treatments without the use of control groups, random selection, or random assignment of 

treatments. Such research techniques were not compatible with the programmatic intent to have 

flexible, locally designed treatment strategies. Without these research techniques, the study had 

to collect additional data to determine whether changes in the principal outcome measuresódust 

lead loadings and blood lead levelsómight be the result of the lead hazard control work or other 

factors. Because children can be exposed to both lead-based paint in their homes and lead from 

other sources, the study tried to collect as much information about other sources as feasible. 

Standard protocols and 23 data collection forms were developed (Appendix A), covering ten 

major variables of interest (Figure 3-1) in fulfilling the nine objectives of the Evaluation (see 

Section 1.1). 

The study evaluated the environmental intervention (i.e., the scope of work and its costs), as well 

as two principal outcome measures (i.e., dust lead loadings and blood lead levels). Data about 

another variable, soil lead levels, were collected at the option of each grantee. Grantees in 

Alameda County, California, Cleveland, Milwaukee, Minnesota, Rhode Island, Vermont, and 

Wisconsin obtained soil information from some of the properties that they treated. A summary of 

environmental sampling procedures for dust, paint, and soil is provided in Figure 3-2. Data about 

the remaining variables were collected by all grantees so that the possible effects of these 

variables could be assessed. 

In a later project that was separately funded, data on post-intervention exterior dust and soil were 

collected from selected locations. Chapter 8 describes the design and methods used for this 

separate project. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Figure 3-1 

Ten Factors of Interest in the Evaluation 

 

1. Baseline Program Information - basic characteristics of the dwelling unit and the 

resident household (e.g., age of dwelling, tenure) at the time of enrollment into the 

study. 

2. Dwelling Condition/Visual Inspection of Exterior/Interior - assessment of the 

general condition of the dwelling before and after intervention, including visual 

assessment of treatment integrity. 

3. Paint Inspection and Testing - description of the location and condition of all 

painted building components and measurement of the paint lead levels on those 

components. 

4. Dust Sampling - measurement of dust lead levels on selected floors, interior 

window sills and window troughs (wells). 

5. Soil Sampling [optional] - description of the ground cover and measurement of soil 

lead levels at the building perimeter and at likely play areas. 

6. Environmental Intervention - description of all lead hazard control strategies and 

treatments. 

7. Environmental Intervention Cost - determination of costs associated with treatment 

of lead hazards. 

8. Family Interview - documentation of activities of the resident household that could 

confound or modify dust and blood lead levels. 

9. Occupant Protection/Relocation Questionnaire - documentation of the experience 

of the household during intervention. Information may identify possible exposure 

of the resident child to lead hazards at the time of intervention. 

10. Blood Lead Testing - measurement of blood lead levels of children between the 

ages of six months and six years who are enrolled in the study. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Figure 3-2 

Summary of Environmental Sampling Protocol 

 

Dust - Dust was collected from 7-9 locations in a dwelling unit during each phase of 

the Evaluation. Single-surface dust wipe* samples were collected from the: 

 Floor: Interior Entry 

 (bare or Kitchen 

 carpeted*) Childís Play Room (or Living Room) 

 Youngest Childís Bedroom (or Smallest Bedroom) 

 Next Youngest Childís Bedroom [if present] 

 Int. Window Sill: Kitchen 

 Youngest Childís Bedroom (or Smallest Bedroom) 

 Window Trough: Childís Play Room (or Living Room) 

 (Well) Next Youngest Childís Bedroom [if present] 

 *Grantees had the option of collecting samples on carpet using a prescribed 

vacuum collection procedure. 

Paint - X-ray fluorescence (XRF) paint tests were conducted on all interior and 

exterior painted component systems prior to intervention. When tests were 

inconclusive, or components were inaccessible by XRF, up to 10 laboratory 

paint chip tests per unit were required. 

Soil - Soil sampling was conducted at the option of the Grantee. When conducted, 

composite soil samples were collected from two locations during each phase 

of the Evaluation: 

 

 Perimeter of Building (i.e., foundation or drip line) 

 Childís Play Area in Yard 

3.1.1 Consent and Notification Procedures 

As discussed in Section 2.1, grantees determined how best to recruit and enroll property owners 

and residents who lived in eligible dwellings. Participation in the lead hazard control grant 

program itself did not require the consent of the family living in the unit(s). However, 

participation in the Evaluation required the informed consent and voluntary participation of both 

the property owner and the resident. Each grantee prepared its own written consent form to 

participate in the Evaluation, outlining reasons for the Evaluation, its risks and benefits and the 

conditions of participation. Each consent was designed to meet local Institutional Review Board 

(IRB) requirements. These IRBs, often from universities or medical institutions, reviewed and 

approved these forms. Grantees were permitted to consider the use of incentives to retain 

families in the Evaluation. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Grantees were responsible for obtaining informed consent from each participating property 

owner as a condition of enrollment in the lead hazard control grant program to participate in the 

Evaluation. Grantees did not deny hazard control services to property owners if resident families 

did not agree to participate, or subsequently dropped out of the Evaluation. Grantees were also 

responsible for obtaining, during the initial contact with the family, signed informed consent of 

the resident household (e.g., parent/legal guardian) to participate in the Evaluation. Children 

between the ages of 6 months and 6 years at the time of enrollment of the family were eligible to 

participate. The parents or legal guardians of each participating child were asked to consent to 

pre- and post-intervention blood lead monitoring and the release of relevant medical information. 

In addition, grantees were to ask parents/legal guardians to participate in structured interviews 

and to allow inspectors access to the dwelling for collection of required pre- and postintervention environmental measurements. Grantees were free to determine how their programs 

managed families who did not want their children tested. 

Grantees were directed to notify participating families of blood lead and environmental lead 

measurements. They were also directed to notify property owners of environmental lead 

measurements. 

3.1.2 Schedule for Data Collection 

As summarized in the data collection schedule (Table 3-1), information was gathered at four 

times during the Evaluation: prior to intervention (Phase 01), immediately after intervention 

(Phase 02), and 6 and 12 months post-intervention (Phases 03 and 04). With this information, it 

was possible to evaluate the costs and effectiveness of the intervention over a one-year period. 

Because HUD felt that longer periods of follow-up were needed to fully assess the costs and 

benefits of the different strategies, it provided support to nine grantees to collect information 

from selected dwelling units at 24- and 36-months post-intervention (i.e., Phases 05 and 06). 

Grantees who participated in this 24/36-month post-intervention study were Alameda County, 

Baltimore, Boston, California, Minnesota, Rhode Island, Wisconsin, Milwaukee, and Vermont. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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Table 3-1:Data Collection Schedule In Relation 

To Environmental Intervention 

DATA COLLECTED ≤4 

MONTHS 

BEFORE 

(Phase 01) 

≤6 

WEEKS 

BEFORE 

(Phase 01) 

≤3 DAYS 

AFTER REOCCUPANCY 

(Phase 02) 

≤6 

WEEKS 

AFTER 

6 

MONTHS 

AFTER 

(Phase 03) 

12, 24, 36 

MONTHS 

AFTER 

(Phases 04,05, 06) 

Baseline Program Information X 

Dwelling Condition 

Visual Inspection 

Exterior/Interior 

X x x x 

Paint Lead Inspection & 

Testing Exterior/Interior 

X 

Dust Lead Sampling x1 x x x x 

Soil Lead Sampling (Optional) X x x x 

Environmental Intervention 

Description 

X x3

 

Environmental Intervention 

Cost 

x2

 x3 

Family Interview x x x 

Occupant Protection/ 

Relocation Questionnaire 

 

x4 x4

Blood Lead Test/Child x x x x 

1

Required only if educational information was given to residents before the 6-week dust sampling phase. Pre-intervention dust sampling had to 

occur before educational information was transmitted to residents to establish true baseline conditions. 2

Estimate (optional) 

3

Actual intervention and cost as soon as possible after clearance 

4

If Project personnel visited the home to draw the child's blood after the intervention, the Occupant Protection Interview should have been 

conducted. If not, this questionnaire was included in the 6-month post-intervention visit. 

3.1.3 Summary of Evaluation Protocols 

Because the quality of the Evaluation was dependent on the grantees reporting information that 

would be comparable across all sites, the Center and UC developed data collection protocols and 

forms that were used by all grantees. The Federal Office of Management and Budget approved 

the data collection forms and protocols in October 1993. All interview forms were translated into 

Spanish by the Center and the state of California. These forms were available for all grantees to 

use. Translators were used to conduct interviews with enrollees speaking other languages. The 

protocols summarized the rationale and procedures for data and sample collection on each of the 

ten major variables of interest (see Section 3.1), including baseline program information, 

dwelling unit inspection and lead paint testing, dust sample collection and analysis, soil sample 

collection, documentation of the type and cost of lead hazard control intervention implemented, 

post-intervention inspections of treatments, initial and post-intervention household interviews, 

blood lead sample collection and analysis, and special instructions for multi-unit housing (see 

Section 3.1). These forms are provided in Appendix A. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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3.1.4 Data Management and Storage Procedures 

UC developed a customized computer database system to handle the data collection needs. The 

grantees then worked with the Center and UC to determine how the different agencies and 

private contractors participating in the Evaluation would collect the data. The database was 

decentralized, with all grantees entering data into their own computers. Once a month, grantees 

copied data files onto diskettes and mailed them to the Evaluationís data center at UC, along 

with hardcopies of forms. At the data center, these files were copied onto diskettes and loaded 

onto two separate computers. Hardcopy forms were organized and filed using a batch system 

(i.e., each single set of forms submitted by a grantee was considered a batch). As an additional 

backup measure, data stored on computer hard drives were periodically saved on magnetic tape. 

Unless otherwise indicated, data recovered from the original diskettes sent by grantees were 

subsequently used for statistical analyses. Prior to statistical analyses, data were converted from 

files stored in an Apple MacIntosh format to a Microsoft Windows Statistical Analysis System 

(SAS) format. The Center used a computer application (ìSpecmasterî) developed by the 

Enterprise Foundation to collect a component-specific and treatment-specific scope of work for 

the lead hazard control activities for each dwelling unit. Like the UC database, the Specmasterô 

database was decentralized and could be used by grantees to design their interventions. Monthly, 

the grantees used a utility application specifically developed for the Evaluation to export the 

treatment/cost data to a file for submission to the Evaluation data center. The treatment/cost data 

were reviewed by the Center prior to inclusion in the central data files. 

3.2 DATA QUALITY ASSURANCE/QUALITY CONTROL (QA/QC) SUMMARY

Detailed QA/QC results are provided in Appendix B. The Evaluation QA/QC program was 

established to detect and rectify errors in the collection and management of data. The overall 

goal was to increase the accuracy and sensitivity of measurements and outcomes by minimizing 

systematic bias or reducing variability. QA/QC procedures were divided into three broad 

categories: (1) those related to analytical laboratory bias and field sampling activities; (2) those 

related to hazard control intervention; and (3) those related to inspection and interview data 

collected by the grantees. 

QC data on dust lead, blood lead, and soil lead samples were obtained by grantees and submitted 

by facsimile directly to the Evaluationís QC officer at UC. The QC officer transcribed and stored 

QC data in an Excel format on IBM-type desktop computers. Certain laboratory results were 

directly supplied by laboratories and were transcribed by data center personnel. 

3.2.1 QC Spike Sample Procedures and Results 

To aid in assessing the ability of laboratories to accurately and reliably measure lead content, 

grantees had their participating laboratories analyze QC ìspikeî samples, i.e., samples prepared 

with known quantities of lead. QC dust samples were prepared by the Wisconsin State 

Occupational Health Laboratory (WSOHL); QC soil and dust vacuum spikes by the Hematology 

and Environmental Laboratories at UC; QC blood samples by the US Centers for Disease 

Control (CDC) and the WSOHL. The spike submittal schedule is shown in Table 3-2. QC 

sample materials, containers and labels were identical to those of regular samples of the same 

matrix, and were included with regular samples when submitted to the laboratories. Laboratories 

did not know the actual lead content of these QC samples. For dust and soil spikes, results that 
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Table 3-2: Scheduled Frequency For Submittal of 

External (Spike) QC Samples 

Type of Sample Recommended Submittal Frequency 

Blood 2 per month minimum or 5% of estimated monthly sample volume, 

whichever was higher 

Dust (wipes) 1 per 50 regular samples 

Dust (vacuum) 1 per 5 dwelling units 

Soil 1 per 50 regular samples 

 

deviated from their true value by more than 20% were considered to be in error. For blood 

spikes, results that deviated from their true value by more than 3 μg/dL were considered to be in 

error. 

• Dust Wipe Spike Results. Over the entire Evaluation period, all but four of the grantees 

submitted spikes at a rate equal to or exceeding the 1:50 (2%) rate required by the protocols. 

However, when looking at compliance on a quarterly basis, only Chicago submitted spikes at 

the required rate in over 90% of the quarters; three other grantees submitted at the required 

rate in 70% or more of the quarters, and an additional four in 50% or more of the quarters. 

The six remaining grantees complied with spike submittal protocols in less than 50% of the 

quarters, yielding less information available for gauging the performance of the participating 

analytical laboratories. 

Most laboratories infrequently had dust wipe QC samples with percent recoveries outside the 

acceptable range. The seven laboratories experiencing systematic problems had their 

analytical findings closely monitored. The Evaluation QC manager worked with the grantees 

and the laboratories to bring performance back to protocol requirements. When a laboratoryís 

performance was characterized by excessive variability, all dust lead loadings from that 

laboratory for the period in question were excluded. A total of 1,996 samples from six 

laboratories were excluded. This represents 2% of the evaluation field samples collected. In 

some cases, grantees were advised to stop using problem laboratories and arrange for the use 

of other laboratories. 

Laboratories sometimes under-estimated the actual lead content of samples, often because a 

particular laboratory method was unable to fully extract the lead from samples. When the 

period and magnitude of values being under-reported could be estimated, an adjustment 

factor was applied to all dust lead loadings reported by the laboratory during the period in 

question. A total of 2,327 samples from two laboratories were adjusted. This represents 2% 

of the evaluation field samples collected. For one laboratory, the QC officer was able to 

identify why the extraction was less than optimal and made suggestions for improving the 

laboratory method. 

• Blood Spike Results. Grantees were asked to submit a minimum of two spiked blood QC 

samples per month (6 per quarter) or 5% of their estimated monthly volume, whichever is 

greater. Massachusetts and Vermont submitted spikes at the required rate in over 90% of the 

quarters; three other grantees submitted at the required rate in 70% or more of the quarters, 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

3-8

and an additional five in 50% or more of the quarters. Three grantees complied with spike 

submittal protocols in less than 50% of the quarters, while one grantee (New Jersey) 

collected only two blood samples and submitted no spiked blood QC samples. 

As with the dust wipe QC samples, occasionally a blood spike sample result was outside the 

acceptable recovery range. However, only 23 blood samples from two laboratories were 

excluded due to poor lab performance. This represents less than 1% of all blood lead samples 

reported. Twenty-five other blood samples were adjusted upward. In one case, the QC officer 

recommended that a grantee stop sending samples to a poorly performing laboratory and to 

use another laboratory for blood analyses. Some blood samples were analyzed for lead by 

laboratories that did not participate in the Evaluationís QC program; these results were used 

in subsequent analyses only if no other source of information was available. 

The QC report in Appendix B offers more details regarding grantee compliance, as well as 

specific information on data that were considered to be suspect and subsequently excluded from 

statistical analyses. 

3.2.2 QC Blank Sample Procedures and Results 

Evaluation protocols required that a ìblankî QC wipe sample be prepared and submitted for 

every 50 field wipe samples collected. All grantees submitted blank samples more frequently, 

with most submittal rates on the order of 1 blank for every 10 or fewer samples. Blank samples 

were prepared in the field using the same materials as those used for regular samples. The 

presence of significant lead on these samples would indicate that lead attributed to a particular 

surface may in fact be due to cross-contamination from an inspectorís glove, a contaminated 

sample container, or other sources not under experimental control. Measured quantities of lead in 

ostensibly ìblankî samples would also potentially reflect cross-contamination in the laboratory, 

or laboratory measurement procedures that were in error. 

Field blanks were prepared and the results monitored by the grantees. According to HUD 

Guidelines (HUD 1995), if more than 50 μg/wipe is detected in a field blank, the field samples 

associated with that blank should be collected again. Practical considerations precluded the revisiting of tested dwellings to collect additional samples. Because re-sampling was not 

conducted, we examined the number of contaminated blank wipe media to determine if field 

sampling results should be disqualified because of presumed contamination. 

Eleven thousand eight hundred and eighty nine (11,889) field blank samples were submitted by 

the various grantees and were analyzed by participating laboratories during periods when their 

QC performance was acceptable. Overall, high blank values occurred only sporadically (only 58 

blanks (0.48%) were above 50 μg/wipe). Slightly less than 1% exceeded 25 μg/wipe. Only 7.1% 

of blanks exceeded 5 μg/wipe. Because (1) so many blank results were reported to be below the 

laboratory detection limit, (2) the detection limits used by the participating laboratories were 

highly variable, and (3) the overall levels encountered on these samples were low, no meaningful 

average value for the blank results could be derived. While the overall percentage of blank 

results greater than 50 μg/wipe was 0.48%, only three grantees exceeded that percentage: 

Massachusetts, Milwaukee, and New York City, with rates of 1.4%, 0.96% and 0.95%, 

respectively. These results were also considered part of the evaluation of the overall quality of 

the field sample data and thus did contribute to the exclusions of field wipe data based on overall 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

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laboratory performance. They were not used to exclude individual field wipe results associated 

with individual high blank levels. 

These results on field blank samples also indicated that the use of multi-packaged wipe material 

in large containers by grantees such as those in the Evaluation contributed no contamination 

problems. 

3.2.3 Substitution of Dust Wipe and Blood Sample Results at or below 

Reporting Limits 

Many initial dust wipe sample results were reported to be below the reporting limits of certain 

laboratories (Table 3-3). Since reporting limits were sometimes as high as 25 μg, and because 

dust re-accumulation rates (one of the most important measures of intervention outcome) were 

often below these reporting limits, laboratories were asked to supply the actual machine values 

for samples with lead content below reporting limits. When machine values could not be 

obtained, dust lead values were imputed according to the methods delineated in Succop et al., in 

order to obtain the feasibly lowest results (Succop 2004). 

Similar issues arose for blood lead data that were reported to be below reporting limits. 

Therefore, laboratories analyzing blood samples were asked to supply actual machine values, and 

in the absence of these machine values, blood lead values were imputed according to Succop et 

al. 

 

Table 3-3: Initial Dust Wipe Sample Results Reported 

Below Laboratory ìReporting Limitsî 

Surface 

% Below 

Reporting 

Limita

PreIntervention 

Immediate 

PostIntervention 

6 Months 

PostIntervention 

12 Months 

PostIntervention 

Floor Average % 29.3% 49.1% 50.7% 52.2% 

Highest % 66.7% 92.7% 95.8% 86.8% 

Window Average % 13.0% 52.7% 36.4% 35.9% 

Sill Highest % 46.4% 95.1% 78.6% 57.7% 

Window Average % 2.4% 44.1% 10.3% 11.1% 

Trough Highest % 15.0% 85.7% 87.5% 21.6% a

Average % = percentage as the average across all Grantees; highest % = percentage based on Grantee with the 

most frequent ìbelow reporting limitî values. 

Data as of: August 1997 

Data from: Form 19 

Data source: QA/QC Summary, October 23, 2000 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

3-10

3.2.4 Quality Control of Inspection and Interview Data 

Several different approaches were used to determine the accuracy and reliability of these data at 

one or more stages of the data review process. These included: 

• Visual review of all incoming hardcopy forms; 

• Check for valid codes, multiple choice options, dates, and certain calculations; 

• Check to be certain that records did not duplicate those already received in earlier data 

submissions; 

• Comparison between first and second key entries to check the accuracy of transcription; 

• Forms progress report to help identify forms still needed to have a complete set; and 

• Special reports to detect discrepancies and data inconsistencies between two or more 

forms. 

Details concerning these approaches are provided in Appendix B. The method most often used to 

correct known data errors was a re-submittal request. This request contained sufficient 

information to identify a particular error, the form on which the error occurred, and the month 

and year in which the form containing the error was originally submitted. A detailed error 

message was provided that indicated the nature of the error and the needed correction. Resubmittal requests were compiled for all errors identified within a single batch of forms and were 

made both after an initial review of a form containing errors and after submittal of unsatisfactory 

corrections by the grantee. Re-submittal requests were included as part of a monthly mailing to 

each grantee. 

Using these methods, an early overall error rate of more than 25 percent was reduced to less than 

1 percent by the end of the data collection process. The Evaluation team concluded that there 

were no systematic biases in the major study outcome variables based on remaining errors. 

3.2.5 Quality Control of Portable XRF Instruments 

Before conducting paint inspections on wood substrates, Grantees were instructed to obtain an 

average of three readings for a National Institute for Standards and Testing (NIST) standard in 

the range of 0.5 to 1.5 milligrams per square centimeter (mg/cm2). If they were unable to obtain 

an acceptable reading after two attempts, they were to defer the paint inspection of the unit until 

the XRF machine had been serviced or until a new machine was acquired. When tested prior to 

use, 1.1 percent of XRF instruments failed their pre-inspection calibration tests. This level was 

considered negligible and XRF data were not excluded on the basis of such violations. 

Grantees were also instructed to confirm XRF calibration before the instrument was turned off, 

i.e., at the conclusion of an inspection or series of inspections. In approximately 1.2 percent of all 

calibration tests, instruments were found to be out of calibration post-inspection even though 

they were in calibration pre-inspection. For another 2.2 percent of inspections, instruments that 

met pre-inspection calibration requirements were not re-tested at the conclusion of an inspection 

to verify that they remained calibrated during the period of use. This level of compliance with 

QC requirements was considered acceptable; therefore, no XRF data were excluded. 

In addition to calibration checks, grantees were to re-visit 5% of the dwelling units and repeat 

XRF measurements for a minimum of 10 surfaces. To pass re-inspection, the average of these 10 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

3-11

repeat measurements was to be within 1% of the original average values (e.g., 1 mg/cm2 if the 

initial average was less than 10 mg/cm2). Five of 154 repeat inspections failed to meet this 

criterion. This level of compliance was considered acceptable; therefore, no data were excluded 

based on repeat XRF measurements. 

3.2.6 Substitution of XRF Results at or above Upper Measurement Level 

XRF instruments varied in the upper range at which lead paint concentrations could be 

measured. Some instruments peaked at 9.9 or 10.0 mg/cm2

 while others could measure higher 

levels. Data for instruments that had maximum readings of 9.9 or 10.0 were normalized by 

substituting a calculated value for the maximum reading. Calculated values were determined by 

estimating the geometric mean and geometric standard deviation for each of the painted 

components measured by a particular instrument. Tables for right-censored data provided in 

Cohen, 19611 were then used to calculate values, which were then randomly substituted for peak 

instrument readings and used in subsequent analyses. Of the 333,223 XRF readings taken on 

interior surfaces, 2.3% are substituted values, while 8% of the 34,240 readings taken on exterior 

surfaces are substituted values. 

3.2.7 Quality Control of Lead Hazard Control Activities and Coding Strategies 

Oversight of construction activities was implemented through field audits and a visual review of 

written specifications for lead hazard control treatments and their associated costs. Field audits 

were conducted by Evaluation project managers and focused on different aspects of the 

construction process, including preparation of the scope of work, management of the 

construction process and completion of construction-related paperwork. Each field audit was 

followed by a written report provided to the grantee by the person conducting the audit. 

SpecmasterÆ, a specification writing and cost-estimating software program, was used by 

grantees to document the types of lead hazard control treatments implemented. Although 

designed for uniformity, grantees sometimes selected certain specifications in error or in a nonstandard way. The Evaluation team reviewed all Specmaster reports to correct errors, standardize 

codes (where possible) and identify dwelling units to be excluded from statistical procedures 

when the recorded specifications did not attain minimal data quality standards. The Evaluation 

team also compared Specmaster reports with data recorded by grantees on the Strategy 

Assignment Form (Form 23) to determine if the treatment strategy assignment was appropriate 

for the scope of work reported in Specmaster. A total of 488 dwelling units required revisions of 

their strategy codes based on this visual review. 

Room identification data recorded on the floor plan/sketch (Form 12) were compared with 

similar information given on the XRF Paint Inspection and Testing Forms (Forms 14-16) to 

ensure correspondence and to ensure that each location was consistently assigned to one of the 

three ìregion codesî for each housing unit (i.e., interior, exterior, and site). Data on these forms 

were sometimes ambiguous and occasionally contradictory. Consequently, data from both types 

of forms were used to establish a region and room/location for treatments as recorded in 

 

1

 Cohen, Jr., A Clifford. Tables for maximum likelihood estimates: singly truncated and singly censored samples. 

Technometrics, Volume 3, Nov. 1961, pg 535-541. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

3-12

Specmaster. Regions were subsequently designated as interior, exterior, unknown or in error. 

Regions designated as ìunknownî or ìin errorî were excluded from certain statistical analyses. 

Construction cost data for each specification and for total lead hazard control costs were also 

reviewed as part of the review of Specmaster data. Region separation by room location was used 

to categorize the individual specification costs into interior, exterior site work and general 

requirements. Specification costs were then summed by region, resulting in four summary costs. 

3.2.8 Training 

The Center and UC carried out a number of activities related to monitoring and assuring data 

quality. They provided training and re-training to grantee field staff and data managers in data 

collection, forms completion, data entry, and data review. Periodic site visits, which included 

direct observation of data collection, were carried out to reinforce training and identify problems. 

Center and UC staff members were available as needed to answer questions related to the 

protocols. 

3.3 OVERVIEW OF STATISTICAL METHODS USED IN THE ANALYSIS OF DATA

Statistical models utilized to evaluate data obtained in this study were: 

• Structural Equation Modeling (SEM). This model was fit to the blood lead and dust lead 

loading data at pre-intervention, 12-months post-intervention, and 36-months postintervention (dust only) in order to explore the interrelationships among factors potentially 

influencing these dependent variables. Post-intervention models included variables used to 

test hypotheses regarding the stability of or change in blood lead and/or dust lead from those 

observed at pre-intervention. Since the equations for the outcome variables were modeled 

simultaneously, the SEM approach was used to explore the direct and indirect effects of 

different factors on all the outcome variables in the causal chain. The factors explored 

included dust lead loadings at various locations, paint lead levels and condition, intervention 

strategies, as well as other housing and demographic factors. The SAS program PROC 

SYSLIN was used to fit the SEMs. 

• Repeated Measures Analysis. This was a longitudinal model, applied to the post-intervention 

blood and dust lead data in the base evaluation (phases 03-04 for blood, phases 02-04 for 

dust) and the extended Evaluation (phases 03-06 for blood, phases 02-06 for dust) in order to 

examine predictors of the outcome of interest. This modeling could not be used to separate 

indirect and direct effects on lead outcomes. Separate models were developed for blood lead 

and for dust lead loadings at four separate locations (entries, interior floors, window sills and 

window troughs). Within-phase (i.e., concurrently measured) and pre-intervention lead 

loadings were tested to determine the significance of their effects on the post-intervention 

lead loadings. The possibilities of declinations in blood lead or re-accumulation of dust lead 

were also tested in the simple models for change. Both the repeat measure and simple models 

for change were fit by the SAS PROC MIXED program. 

• Logistic regression and generalized estimating equation (GEE) models. These models were 

fit to the post-intervention data to identify predictors of clearance failure. The logistic model 

was used at one phase, for one observation per dwelling. The GEE was also used to 

investigate whether recontamination of the residences caused greater failure on the various 

surfaces where dust was collected or whether it caused a lessened decrease or ìbottoming 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 

3-13

outî of expected declines in post-intervention blood lead levels. GEE models were both 

longitudinal and cross-sectional and used the SAS procedures PROC LOGIST and PROC 

GENMOD (with a logit link) to model the clearance failure data. 

• Linear regression models. This type of modeling was used in many investigations. One 

investigation was to determine the impact of several environmental factors, building-related 

factors, and intervention-related factors on the cost of lead hazard abatement. Using phase 2 

dust lead loading data, a linear regression model was also used to identify the predictors of 

dust lead loadings measured immediately post-intervention. Room-level analyses, in which 

the impact of the intervention on various structural elements within each room of treated 

dwellings, were also conducted using linear regression modeling. The majority of the linear 

regression models employed could also be called ìanalysis of covariance modelsî because at 

least one continuous predictor is included in the model. Simple linear regression models and 

analysis of variance models were used for a wide range of analyses. The SAS procedure 

PROC GLM was used for all linear regression modeling. 

Details concerning these models are provided in appropriate sections throughout this document 

and in the Compendium to the Final Report. 

3.4 CONVENTIONS USED IN SUMMARIZING DATA

The following set of conventions were used in summarizing data for this report: 

• Because of their limited use, results for the following parameters are not used to evaluate 

treatment effectiveness, although some data may be summarized in the report: 

- Laboratory paint chip sample results (pre-intervention); 

- Interior common area environmental sampling results and treatments; 

- Results for dust samples collected using vacuum sample methods; 

- Grantee-collected soil samples 

• Many of the tables and figures present combined data from all grantees, as well as granteespecific data; however, grantee-specific data are mentioned in the text only when such data 

indicate a deviation from trends identified based on combined data and only when 20 or more 

observations are available for the grantee. 

• All laboratory data that did not meet Evaluation quality assurance/quality control (QA/QC) 

requirements were excluded (see Section 3.2.1). QA/QC results are discussed in detail in the 

Appendix B. 

• When environmental sample results are presented by phase of collection, the phase is based 

on the data recorded on the appropriate forms even if the collection dates may indicate 

miscoding. When descriptive statistics are presented, no restrictions were placed on sample 

dates (i.e., samples that were outside the time requirements stated in the protocols were 

included). For statistical models, eligibility was restricted to data within collection dates 

described in further detail in this report. 

• Except where specifically noted, bare floor lead wipe sample results were not evaluated 

separately from those for carpets. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

4-1

PRE-INTERVENTION CHARACTERISTICS OF HOUSING UNITS AND RESIDENT 

FAMILIES 

4.1 INTRODUCTION

Any interpretation of the effectiveness of lead hazard control activities must be conducted with 

reference to the pre-intervention characteristics of the enrolled dwellings and residents. The 

HUD Lead Hazard Control Grant Program focused on low- income housing that had lead-based 

paint hazards. Because of these general enrollment requirements and the specific enrollment 

criteria that grantees used, the dwellings in the Evaluation and the people who lived in those 

dwellings differ from the general population. The costs and effectiveness of the lead hazard 

control activities performed in the Evaluation may have differed had they been applied to a 

different set of dwellings. 

Key pre-intervention characteristics of buildings, dwelling units and households varied greatly 

by grantee. These variations reflect both regional differences and the differences in the granteesí 

specific enrollment plans (see Section 2.2). The wide variation in key characteristics may have 

affected pre-intervention paint lead, dust lead loadings, and soil lead levels and may have 

contributed to or interfered with the effectiveness of certain interventions. 

The pre-intervention housing and family characteristics described in this chapter refer to 

characteristics present in the 2,682 dwelling units (1,486 buildings) that had dust samples 

collected immediately post-intervention and had dust lead loading results that were below 

grantee-specific clearance criteria.1 The discussion of pre-intervention family characteristics 

focuses on the 1,548 households and 1,766 children living in dwelling units occupied prior to 

intervention (1,857 of the 2,682 units). 

The 2,682 dwelling units with evidence of ìpassing clearanceî are a subset of the 3,835 dwelling 

units enrolled and the 2,920 dwellings treated during the Evaluation (Figure 4-1). Although all 

2,920 treated dwellings were expected to pass clearance under the requirements of the HUD 

Lead Hazard Control Grant program, clearance could not be verified for 238 dwellings due to 

laboratory problems, potentially missing data or discrepancies in interpreting clearance 

requirements. The 238 dwellings include: 

 92 that failed the initial clearance test, and no further clearance tests were reported to the 

 evaluators; 

76 that had immediate post-intervention dust lead data that failed laboratory QC standards; 

31 that did not demonstrate clearance based on the follow-up clearance tests; 

37 for which all follow-up tests were below standards, but samples were not taken in the 

required locations; and 

2 that had clearance dust forms that were missing all results. 

 

1

 Most grantees used the floor clearance value of 200 μg/ft2 that existed at the start of the Evaluation; however, 

Cleveland, New Jersey and New York City used 100 μg/ft2

 and Minnesota used 80 μg/ft2. Clearance criteria for sills 

and troughs were 500 and 800 μg/ft2

, respectively, for all grantees. A complete discussion of clearance requirements 

can be found in Chapter 7. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

4-2

Without verification that the 238 dwellings met the requirements of the Grant program, they 

were excluded from further detailed evaluation. Data available for the 2,682 dwellings with 

evidence of ìpassingî clearance are presented in this chapter and are the focus for the remainder 

of this report. 

4.2 PRE-INTERVENTION HOUSING CHARACTERISTICS AND CONDITION

A primary feature of the Evaluation was the latitude grantees were given by HUD to design their 

own programs. As summarized below, local recruitment methods, as well as regional differences 

in housing stock, yielded a wide variation in the characteristics and condition of Evaluation 

housing. When reviewing the information presented in this section, it is important to keep in 

mind that the number of dwellings in the Evaluation varied greatly by Grantee. Grantees with 

higher numbers of dwellings likely exerted relatively greater influences on several of the 

variables. For example, as noted in Chapter 2, Baltimore, New York City and Vermont (393 

units, 420 units, and 391 units, respectively) each treated and cleared approximately twice the 

average number of dwellings per grantee (192). In some cases, the relative influence of dwellingrelated information from these three grantees may have been greater than the influence of 

grantees that treated and cleared a smaller number of dwellings. 

In the discussion below, relevant 1995 US housing statistics as found in the reference, American 

Housing Survey for the United States in 1995 (HUD 1997), are used to place Evaluation housing 

characteristics in context with those of the United States in general. The AHS collects national 

data every other year, returning to the same homes to gather data, with a national sample 

covering an average of 55,000 homes. AHS data for 1995 were chosen because most preintervention housing data were collected between 1994 and 1996. 

At pre-intervention, the majority of units in the Evaluation were pre-1930, occupied rental units 

located in multi-unit buildings (Table 4-1). Dwellings in the Evaluation tended to be older and 

have lower occupancy rates and much lower market values than those of the general US housing 

stock. These differences are likely due to the emphasis of the grant program on low-income 

housing, the need for grantees to enroll dwelling units of a certain age in order to find lead-based 

paint, grantee-specific differences in unit selection and regional characteristics of the study areas. 
Data as of: June 1, 2000-restricted to units that passed clearance 

Data from: Forms 01, 11, 15, 19, 20 Data Source: UC Table 012 

Figure 4-1: Number of Dwelling Units by Evaluation Activity

3835

2920

2682

2353

2463

826

695

0

500

4000350030002500200015001000

Enrolled Treated Through Clearance 6 Months PostIntervention 12 Months Post- Intervention 24 Months Post- Intervention 36 Months Post- Intervention

Evaluation Activity

Number of Dwelling Units

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

4-3
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 4

4.2.1 Pre-Intervention Characteristics of Dwellings 

Dwelling units in the Evaluation had a greater tendency to be vacant than 1995 US housing 

(HUD 1997): almost a third of the dwellings were vacant rental units at pre-intervention, while 

only 11 percent of 1995 US housing fell in this category. Almost half of the dwellings were 

occupied rental units (1,312 or 49%), while 20 percent were owner-occupied. Baltimore and 

Vermont tended to have a higher proportion of vacant units (73% and 46%, respectively) than 

other grantees. 

The types of buildings in the Evaluation ranged from single-unit structures (828 (31%) of the 

2,682 units) to small, 2-to-4-unit multi-unit buildings (1,069 units (40%)) to larger multi-unit 

buildings (784 units (29%)) (Table 4-1). This distribution is somewhat the reverse of the national 

distribution of building types, in which 68 percent were single-family structures and 25 percent 

were multi-family structures (HUD 1997). Most dwellings had their entry on the first floor of 

their buildings. Several granteesóAlameda County, Cleveland, Minnesota, and Wisconsinó

primarily enrolled single-unit detached structures, while rowhouse was the primary structural 

type only for Baltimore (Table 4-2). By contrast, 97 percent of the dwelling units in New York 

City were in large multi-family buildings with many units more than 4 stories above the building 

entry, reflecting the cityís larger and taller style of housing. Boston, Massachusetts, and Rhode 

Island primarily enrolled ìtriple-deckerî type housing (a common construction style in urban 

areas of New England) with a majority of units having entries located on the second or third 

floors. Chicago and Milwaukee primarily enrolled smaller two-family type buildings, or ìtwoflats,î common in those cities. 

Unlike building type, there was little variability in the age of buildings in the Evaluation, with 

2,270 (84%) units built before 1930. Due to the focus of the study, Evaluation units tended to be 

much older than the general 1995 US housing stock (HUD 1997), in which only 14 percent of 

houses were built before 1930. This homogeneity of Evaluation units is not surprising given that 

lead-based paint was heavily used in residential painting before the 1940s. New Jersey was the 

only grantee to enroll predominantly post-World War II dwellings, with 93 percent of dwellings 

built between 1960-69. 

Reflecting the fact that two-thirds of the dwellings were located in multi-family buildings, over 

half (60%) of the dwelling units (1,594) had 1,000 square feet or less living space. Market values 

for dwellings tended to be low, with 2,058 (78%) reportedly worth $10,000 to $50,000 at preintervention, and only 73 (less than 4%) worth more than $100,000. Because dwellings tended to 

be more deteriorated than the general US housing stock and/or were located in more depressed 

areas of the country, market values were generally much less than the US at large in 1995, where 

less than 20 percent were worth $10,000 to $50,000, and 44 percent were worth more than 

$100,000 (HUD 1997). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 5

TABLE 4-1: Summary of Pre-Intervention Housing Characteristicsó 

All Grantees Combined 

Category 

Total Number (Percent) 

of Evaluation Dwellings 

within Category 

Percentage of Dwellings 

within Category, 1995 

American Housing Survey 

Occupancy and Ownership Status:

Occupied by Owner 545 (20%) 31% 

Occupied Rental 1,312 (49%) 58% 

Vacant Rental 812 (30%) 11% 

Other 13 (1%) -- 

Total Dwellings: 2,682 (100%) 100% 

 

Building Type: 

Single Detached 470 (18%) 68% 

Rowhouse 358 (13%) 6% (single attached) 

2 to 4 units 1069 (40%) 10% 

>4 Units 784 (29%) 16% 

Total Dwellingsa: 2,681 (100%) 100% 

 

Construction Period: 

Pre-1910 1,133 (42%) 

1910-1919 517 (19%) 

9% (1919 or earlier) 

1920-1929 620 (23%) 5% 

1930-1939 130 (5%) 6% 

1940-1949 160 (6%) 8% 

1950-1959 88 (3%) 13% 

1960-1969 32 (1%) 15% 

Total Dwellingsb 2,680 (100%) 100% 

 

Living Space, Square Footage: 

<600-1,000 1,594 (60%) 14% (<1,000 ft2)

e 

>1,000 1,070 (40%) 86% (1,000 or more) 

Total Dwellingsc 2,664 (100%) 100% 

 

Market Value: 

1,000-10,000 210 (8%) 3%e 

>10,000-50,000 2058 (78%) 18% 

>50,000-100,000 292 (11%) 35% 

>100,000 73 (3%) 44% 

Total Dwellingsd 2,633 (100%) 100% a

One dwelling was excluded due to coding as ìother.î 

b

Two dwellings were excluded due to coding as post-1969 units. 

c

Eighteen dwellings were excluded 17 due to missing Form 11s, one due to missing data for this variable. 

d

Forty-nine dwellings were excluded because those units were funded by non-HUD agencies. 

e

AHS square footage data for single family detached and mobile homes only. Market values for occupied housing units only. 

Data as of: June 1, 2000-restricted to units that passed clearance 

Data from: Form 01 

Source of data: UC Tables 004, 005, 011, 021, 503 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 6

Table 4-2: Summary Of Selected Housing Characteristics―By Grantee 

Grantee Name Building Type Floor of Bldg. 

Where Dwelling 

Entry is locateda

 

Dwelling Size (ft2

) Occupancy Statusb 

All Grantees Single family: 31% 

2-4 units: 40% 

>4 units: 29% 

1: 66% 

2 to 3: 27% 

4 or more: 7% 

<600-800: 41% 

801-1,200: 35% 

>1,200: 24% 

Vacant: 30% 

Occup-Owner: 20% 

Occup-Rental: 49% 

Alameda 

County 

Single family: 36% 

2-4 units: 43% 

>4 units: 21% 

1: 86% 

2 to 3: 12% 

4 or more: 2% 

<600-800: 54% 

801-1,200: 31% 

>1,200: 15% 

Vacant: 13% 

Occup-Owner: 26% 

Occup-Rental: 61% 

Baltimore Single family: 89% 

2-4 units: 10% 

>4 units: 0.5% 

1: 96% 

2 to 3: 4% 

4 or more: 0% 

<600-800: 16% 

801-1,200: 62% 

>1,200: 22% 

Vacant: 73% 

Occup-Owner: 11% 

Occup-Rental: 13% 

Boston Single family: 15% 

2-4 units: 85% 

>4 units: 0% 

1: 49% 

2 to 3: 51% 

4 or more: 0% 

<600-800: 0% 

801-1,200: 63% 

>1,200: 37% 

Vacant: 16% 

Occup-Owner: 43% 

Occup-Rental: 41% 

California Single family: 39% 

2-4 units: 14% 

>4 units: 47% 

1: 85% 

2 to 3: 15% 

4 or more: 0% 

<600-800: 78% 

801-1,200: 14% 

>1,200: 8% 

Vacant: 27% 

Occup-Owner: 20% 

Occup-Rental: 53% 

Chicago Single family: 21% 

2-4 units: 62% 

>4 units: 17% 

1: 59% 

2 to 3: 37% 

4 or more: 4% 

<600-800: 15% 

801-1,200: 40% 

>1,200: 45% 

Vacant: 2% 

Occup-Owner: 37% 

Occup-Rental: 61% 

Cleveland Single family: 43% 

2-4 units: 29% 

>4 units: 28% 

1: 63% 

2 to 3: 25% 

4 or more: 12% 

<600-800: 4% 

801-1,200: 49% 

>1,200: 47% 

Vacant: 11% 

Occup-Owner: 31% 

Occup-Rental: 58% 

Massachusetts Single family: 7% 

2-4 units: 80% 

>4 units: 13% 

1: 42% 

2 to 3: 56% 

4 or more: 2% 

<600-800: 21% 

801-1,200: 22% 

>1,200: 57% 

Vacant: 11% 

Occup-Owner: 31% 

Occup-Rental: 58% 

Milwaukee Single family: 29% 

2-4 units: 71% 

>4 units: 0.4% 

1: 81% 

2 to 3: 19% 

4 or more: 0% 

<600-800: 42% 

801-1,200: 37% 

>1,200: 21% 

Vacant: 8% 

Occup-Owner: 27% 

Occup-Rental: 65% 

Minnesota Single family: 39% 

2-4 units: 48% 

>4 units: 13% 

1: 73% 

2 to 3: 25% 

4 or more: 2% 

<600-800: 24% 

801-1,200: 41% 

>1,200: 35% 

Vacant: 11% 

Occup-Owner: 37% 

Occup-Rental: 52% 

New Jersey Single family: 4% 

2-4 units: 4% 

>4 units: 92% 

1: 92% 

2 to 3: 8% 

4 or more: 0% 

<600-800: 63% 

801-1,200: 33% 

>1,200: 4% 

Vacant: 29% 

Occup-Owner: 4% 

Occup-Rental: 67% 

New York City Single family: 0% 

2-4 units: 3% 

>4 units: 97% 

1: 22% 

2 to 3: 46% 

4 or more: 32% 

<600-800: 96% 

801-1,200: 4% 

>1,200: 0% 

Vacant: 34% 

Occup-Owner: 0.2% 

Occup-Rental: 66% 

Rhode Island Single family: 11% 

2-4 units: 76% 

>4 units: 13% 

1: 43% 

2 to 3: 55% 

4 or more: 2% 

<600-800: 23% 

801-1,200: 39% 

>1,200: 38% 

Vacant: 22% 

Occup-Owner: 22% 

Occup-Rental: 56% 

Vermont Single family: 10% 

2-4 units: 54% 

>4 units: 36% 

1: 72% 

2 to 3: 26% 

4 or more: 2% 

<600-800: 41% 

801-1,200: 36% 

>1,200: 23% 

Vacant: 46% 

Occup-Owner: 10% 

Occup-Rental: 44% 

Wisconsin Single family: 48% 

2-4 units: 49% 

>4 units: 3% 

1: 83% 

2 to 3: 11% 

4 or more: 6% 

<600-800: 29% 

801-1,200: 40% 

>1,200: 31% 

Vacant: 17% 

Occup-Owner: 47% 

Occup-Rental: 36% a

Number of floors that an enrolled unitís entry is above the entry to the whole building; not equivalent to number of floors within a building. b

Baltimore had 3% of units with occupancy status ìother;î therefore, total percents for Baltimore and all Grantees do not sum to 100%.

Data as of: June 1, 2000órestricted to units that passed clearance Data from: Form 01 Source of data: UC 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 7

Exhibit 4-1 offers a brief overview of twelve ìtypicalî styles of housing that were treated and 

cleared in the Evaluation. Approximately 60 percent (1,603) of the 2,682 dwellings fit into one 

of these 12 typical housing styles. For each typical type of housing, the exhibit includes a list of 

defining characteristics (i.e., construction period, type of exterior, number of bedrooms, and (for 

multi-unit structures), number of units within a building), as well as a description of the dwelling 

units contained within the housing. In both the single and multi-unit categories, diverse types of 

housing were represented. Typical multi-unit buildings included 2-family, triplex and fourplex 

units, as well as small and large multi-unit buildings with varying exteriors. Typical singlefamily housing included frame, colonial and ranch style homes, as well as rowhouses. 

4.2.2 Pre-Intervention Physical Condition Of Dwellings 

As shown in Figure 4-2, 41 percent of dwelling units had visibly obvious and extensive 

deterioration of interior dwelling component systems (i.e., walls/trim/doors and floors). Fortyone percent of dwelling units had similar deterioration of exterior building component systems 

(i.e., roofs, siding, windows, porches and foundations). The degree of interior and exterior 

deterioration differed between grantees. For example, while less than half of the dwelling units 

had interior deterioration, 70 percent of Baltimoreís dwellings and 82 percent of New Jerseyís 

had one or more interior components with deterioration reported. 

Conditions of building component systems were assessed by inspectors who received training to 

rate the component systems according to a single protocol. Some variation between the rating 

systems of the inspectors existed; however, overall, any variation in rates of building component 

deterioration between grantees likely reflected actual differences in condition at the time of 

enrollment. 

4.3 PRE-INTERVENTION LEAD HAZARDS IN DWELLINGS

4.3.1 Pre-Intervention Condition and Lead Content of Paint 

Title X, as well as most states, defines lead-based paint as applied paint that contains 1 mg/cm2

or more of lead. In the Evaluation, painted components were tested for lead by a certified lead 

inspector using an X-ray fluorescence (XRF) lead-based paint analyzer. Deteriorated lead-based 

paint is considered to be a hazard because it can directly contribute to blood lead levels of 

children who ingest pieces of the paint or indirectly by contributing to the contamination of 

house dust and soil; therefore, most grantees prioritized deteriorated lead-based paint for 

treatment. Grantees rated the levels of deterioration by recording the condition (i.e., good, fair, or 

poor) of each surface that was XRF-tested at pre-intervention2

. 

 

2 Good (Code=1): <? ft2

 of deteriorated paint on large areas (e.g., walls) and <1% on small areas (e.g., trim); Fair 

(code=2): 1⁄2 to 2 ft2

 of deteriorated paint on large areas or 1% to 10% on small areas; Poor (code=3): >2 ft2 of 

deteriorated paint on large areas or >10% on small areas. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 8

Figure 4-2a: Percentage of Inspected Dwelling Units with 

Reported Building System Deterioration by Grantee 

Interior 

Percentage of Dwellings with Any Interior Building System Deterioration

28%

70%

36%

34%

28%

32%

32%

42%

41%

82%

43%

24%

37%

32%

41%

0

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Alameda County (166)

Baltimore (390)

Boston (67)

California (99)

Chicago (120)

Cleveland (152)

Massachusetts (133)

Milwaukee (220)

Minnesota (143)

New Jersey (27)

New York (414)

Rhode Island (160)

Vermont (391)

Wisconsin (181)

All Grantees (2,663)

Note: Total number of dwelling units in parentheses 

(restricted to those that passed clearance) 

Data from: Form 10 (Phase 01) and Form 11 (Phase 01)

Data as of: June 1, 2000 

Source of Data: UC Tables 66-E and 67-B 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 9

Figure 4-2b: Percentage of Inspected Dwelling Units with 

Reported Building System Deterioration by Grantee 

Exterior 

Percentage of Dwellings with Any Exterior Building System Deterioration

41%

47%

43%

23%

30%

40%

37%

41%

38%

100%

40%

47%

39%

39%

41%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Alameda County (166)

Baltimore (392)

Boston (68)

California (90)

Chicago (120)

Cleveland (152)

Massachusetts (134)

Milwaukee (216)

Minnesota (141)

New Jersey (26)

New York City (420)

Rhode Island (160)

Vermont (391)

Wisconsin (181)

All Grantees (2,657)

Note: Total number of dwelling units in parentheses 

(restricted to those that passed clearance) 

Data from: Form 10 (Phase 01) and Form 11 (Phase 01)

Data as of: June 1, 2000 

Source of Data: UC Tables 66-E and 67-B 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 10

In the discussion below, relevant information on the condition and lead content of paint in US 

housing as found in the reference, The National Survey of Lead and Allergens in Housing (HUD 

2001), is used to place measurements obtained during the Evaluation in context with those of the 

United States in general. The principal lead-related purpose of the NSLAH was to develop a 

scientific description of the existing lead levels in paint, dust and soil in the nationís housing. A 

total of 831 occupied homes from all construction-year categories were recruited and completed 

the survey, with field surveys conducted in 1998-1999. 

Interior XRF results are grouped into ìdoors/trim,î ìwindow,î and ìotherî components, 

primarily because each component system had similar paint lead concentrations. XRF results for 

all exterior components (except windows) are grouped together because they had similar paint 

lead levels. The Evaluation team determined the arithmetic mean paint lead level and paint 

condition for all tested components within each component system at each dwelling. The 

arithmetic mean paint lead level within each dwelling is approximately normally distributed. The 

median of mean values for all dwelling units are presented in Table 4-3. 

Data provided in Table 4-3 indicate that building component systems with higher lead levels tend 

to be more deteriorated. This tendency may be due at least in part to the fact that lead paint was 

used in older buildings. The median of mean lead contents for windows and exterior components 

were 6.5 and 6.2 mg/cm2

, respectively, and tended to be in fair to poor condition (i.e., median of 

mean paint condition of 2 and 2.2, respectively). Interior doors/trim had a lower lead content 

(median of mean=2.7 mg/cm2) and were in good-to-fair condition (1.3). Other interior 

components (which include walls, ceilings and floors) had an even lower lead content (1.4 

mg/cm2) and were also in good-to-fair condition (1.4). 

The lead content of all exterior surfaces (median of mean=6.2 mg/cm2

) was higher than that of 

all interior surfaces (median of mean=3.3 mg/cm2

) (Table 4-3). This relationship concurs with 

the findings of the NSLAH, in which lead content values for the exterior of surveyed units were 

greater than those for the interior. However, for both the interior and exterior, lead content values 

for Evaluation units were much higher than those found in the NSLAH, likely because NSLAH 

surveyed housing of all ages, while the Evaluation targeted older housing. 

As shown in Figure 4-3, the lowest lead-based paint levels on both interior and exterior surfaces 

were found in California (median of mean=1.0 and 3.5 mg/cm2

 for interior and exterior, 

respectively), New Jersey (0.4 and 1.8 mg/cm2 for interior and exterior, respectively), and New 

York City (1.1 and 1.0 mg/cm2

 for interior and exterior, respectively). Buildings in the former 

two locations were of more recent construction, while buildings in all three locations had 

predominantly masonry or stucco exteriors. The highest interior and exterior lead-based paint 

levels were observed in Boston (6.2 and 11.2 mg/cm2

, respectively), Rhode Island (7.0 and 15.4 

mg/cm2

, respectively) and Milwaukee (6.6 and 11.2 mg/cm2, respectively). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 11

TABLE 4-3: Summary Of Lead Content And Condition Of Interior And 

Exterior Painted Surfaces At Pre-Intervention 

Type of Component Number of 

Dwellings d

Median of Mean 

Paint 

Conditiona,b 

Median of Mean 

Lead Content 

(mg/cm2

)

b,c 

NSLAHe Arith. 

Mean Lead 

Content (mg/cm2

) 

All Interior 

Components 

2,627 1.5 3.3 NA 

 Interior 

Doors/Trim 

2,625 1.3 2.7 0.5-1.1 

 Interior Window 2,615 2.0 6.5 0.9-2.5 

 Interior ìOtherî 2,627 1.4 1.4 0.2-0.4 

All Exterior 

Components 

2,609 2.2 6.2 0.9-1.6 

a

Lead paint condition ratings: 1=good (<1/2 ft2 of deteriorated paint on large areas and <1 ft2 on 

small areas); 2=fair (1/2 to 2 ft2

 of deteriorated paint on large areas or 1% to 10% on small 

areas); 3=poor (>2 ft2 of deteriorated paint on large areas or >10 ft% on small areas). b

Median of mean values were calculated by first calculating the mean of either lead content or 

paint condition within each dwelling unit for all surfaces tested, then using these dwellingspecific means to calculate the median values across all dwelling units. 

c

Lead paint is defined by HUD and most states to be paint having a lead concentration of 1 

mg/cm2

 or more. 

d

55 units excluded due to missing forms. For ìinterior doors/trimî and ìinterior window,î 2 and 

12 additional units, respectively, were excluded due to missing data for variable. For ìall exterior 

components,î 73 units were excluded, 51 due to missing forms and 22 because exterior surfaces 

were not tested. 

e

NSLAH=National Survey of Lead and Allergens in Housing (HUD 2001). 

Data as of: June 1, 2000, restricted to units that passed clearance. 

Data from: Forms 14, 15, 16 

Data source: UC Tables 99, 101 and 527 
Figure 4-3: Median of Meana Lead Content (mg/cm2) of Interior and Exterior Painted Surfacesby Grantee

2.3

4.3

6.2

1.0

3.4

3.2

5.2

6.6

5.1

0.4

1.1

7.0

3.2

4.4

3.3

5.9

7.7

11.2

3.5

9.3

5.0

9.7

11.2

9.8

1.8

1.0

15.4

5.9

5.6

6.2

8.06.04.02.00.0

18.016.014.012.010.0

Alameda Coun yt

Balt mi

ore

Boston

California

Chicago

Cleve and l

Massachusetts

Milwaukee

Minnesota

New Jersey

New York City

Rhode Is al nd

Vermont

Wisconsin

All Grantees

Grantee

Median of Meana Lead Content (mg/cm2)

Median of Mean InteriorMedian of Mean Exterior

aMedian of mean=using dwelling-specific means to calculate median values across all dwellings 

Data as of: June 1, 2000-restricted to units that passed clearance 

Data from: Forms 01, 14, 15, 16 Data Source: UC Tables 099, 101 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

4-12 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 13 

As expected, for both interior and exterior surfaces, higher geometric mean lead content values 

were found in older dwelling units. Paint with the highest lead content was found in units 

constructed before 1910, and paint with the lowest lead content was found in units constructed 

after 1949 (Figure 4-4). 

4.3.2 Pre-Intervention Interior Dust Lead Loadings 

In this report, dust lead results are reported as ìloadings,î expressed as the mass (in micrograms, 

μg) of lead per square foot of surface area (μg/ft2

). Dust lead loadings from the playroom, 

kitchen, and bedrooms were considered together because sample results in these locations 

generally were not distinct from one another. Entry floors, however, were grouped separately 

from interior floor data collected from other locations after statistical evaluation indicated that 

entry floor dust lead loadings were consistently higher than those from other floor sample 

locations. Because the entry is in the path leading from the exterior to the interior of the 

dwelling, it is logical to keep results for this location separate. Although wipe samples collected 

from carpets tended to result in lower loadings than those collected from bare floors, carpet wipe 

samples were grouped with bare floor wipe samples because collection and analytical methods, 

as well as clearance standards, were the same. This grouping also resulted in a more 

representative illustration of pre-intervention dust lead loadings in units having both carpets and 

bare floors. 

Pre-intervention dust lead loading measurements followed the expected trend, with the highest 

loading values detected in window troughs, followed by window sills, then entry floors, and 

finally interior floors (Figure 4-5). Geometric mean dust lead loadings, shown in Table 4-4, were 

quite similar to median dust lead loadings for all surfaces, indicating that within-dwelling 

loadings are log-normally distributed (Figure 4-5). For all sample locations, pre-intervention 

dust lead loadings tended to be higher in vacant dwellings than in occupied dwellings; this 

finding was most dramatic for floors, whose median loadings on entry and interior floors in 

vacant dwellings (151 μg/ft2 and 139 μg/ft2, respectively) were six to eight times larger than 

those in occupied dwellings (20 and 16 μg/ft2, respectively). Dust lead loadings on window sills 

and window troughs also tended to be greater in vacant than in occupied dwellings; however, the 

difference was less dramatic than for floors. These results may reflect the impact of routine 

cleaning common to occupied dwellings, or it may be due to differences in characteristics of 

vacant and occupied dwellings, or some combination of the two. Occupancy status will be 

further considered later in this report when evaluating the impact of lead hazard reduction on 

post-intervention dust lead loadings. 

The NSLAH (Jacobs 2002) reported median dust lead loadings in occupied homes (0.9 μg/ft2

 for 

floors, 8.3 μg/ft2

 for sills, and 89.1 μg/ft2 for troughs) that were much lower than Evaluation 

results from these locations in occupied units (16 μg/ft2

, 237 μg/ft2 and 4,486 μg/ft2, 

respectively). These differences are likely due to the fact that NSLAH dust wipe samples were 

collected from dwellings built in all age categories, while the Evaluation collected wipe samples 

primarily from pre-1930 housing. 

Interestingly, pre-intervention dust lead loading values on floors were lower than expected. 

Indeed, the pre-intervention median dust lead loadings for interior floors, entry floors and sills in 

occupied units (Figure 4-5) were less than the dust lead standards for risk assessment 

recommended by EPA in 1995: 100 μg/ft2

 for floors and 500 μg/ft2 for sills (EPA 1995a). (EPA 

has since lowered the floor standard to 40 :g/m2

.) The pre-intervention median for troughs in 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4- 14 

occupied units (4,486 μg/ft2), however, was well above the Evaluation clearance standard of 800 

μg/ft2. 

Pre-intervention dust lead loadings differed among grantees (Table 4-4). In Baltimore, Boston, 

New York City and Rhode Island, geometric mean interior floor dust lead loadings in both 

vacant and occupied units tended to be higher than those for all grantees together. On the other 

hand, Minnesota, New Jersey, Alameda County and California tended to have lower interior 

floor dust lead loadings. For entry floors, geometric mean dust lead loadings in vacant and 

occupied units tended to be higher in Baltimore, Boston, Vermont and Rhode Island, while those 

in Minnesota, New Jersey and Massachusetts tended to be lower. 

For window sills, higher geometric mean dust lead loadings were found in both occupied and 

vacant units in Milwaukee, Baltimore, Rhode Island and Boston, while those in New Jersey, 

Alameda County, Minnesota and Vermont tended to be lower than all grantees together. 

Milwaukee, Wisconsin and Rhode Island tended to have higher window trough geometric mean 

dust lead loadings in both vacant and occupied units, while Chicago, Alameda County, 

California and New Jersey tended to have some of the lowest dust lead loading values for 

troughs. 

4.3.3 Pre-Intervention Soil Lead Levels 

As discussed in Section 2.2, seven granteesóAlameda County, California, Cleveland, 

Milwaukee, Minnesota, Rhode Island, Vermont, and Wisconsinósubmitted soil lead data from 

enough premises to be included in this report. Two soil samples were generally collected from 

each property: a sample from the building perimeter/dripline (i.e., next to the foundation of the 

building) and a sample from a childís play area (or likely play area). Soil samples were collected 

from both bare and covered soil. 

On average, regardless of the amount of soil cover, samples collected from building perimeters 

had higher lead concentrations than those collected from play areas, perhaps due to the 

deposition of lead particles from weathered exterior paint onto perimeter soil. Overall, the 

geometric mean perimeter and play area soil concentrations were 1,104 ppm and 504 ppm, 

respectively (Figure 4-6). The two geometric mean dripline bare soil sample results reported in 

the NSLAH (HUD 2001) were 44.5 and 49 ppm, much lower than levels in Evaluation perimeter 

samples. The two NSLAH geometric mean soil results reported for mid-yard bare soil samples 

were 28.1 and 29.9 ppm, much less than the Evaluationís play area geometric mean. 

Soil lead concentrations tended to be higher at the building perimeter when soil cover was 

limited (from half bare to all bare) than when the soil had no bare areas or only small areas bare. 

A relationship between soil lead concentrations and the amount of soil cover was not apparent 

from the samples taken at play areas (Figure 4-6). 

4.3.4 Discussion 

The highest prevalence with lead paint was found on exterior surfaces and interior windows, 

with about half of the units tested having lead-based paint in fair or poor condition. Building 

component systems with higher lead levels also tended to be more deteriorated and were found 

in older dwelling units. This tendency may be due at least in part to the fact that lead paint was 

used in older buildings. 
Figure 4-4: Geometric Mean Paint Lead Content (mg/cm2) and 95% Confidence Interval for the 

Geometric Mean--by Building Construction Period

0.9

1.7

0.6

1

0.6

1.5

0.7

1.6

0.4

1.3

0.3

0.9

0.7

1.4

2.502.001.501.000.500.00

interior exterior interior exterior interior exterior interior exterior interior exterior interior exterior interior exterior

<1910 1910-1919 1920-1929 1930-1939 1940-1949 >1949 All Years

Construction Period

Paint Lead Content (mg/cm2)

upper 95% CI boundgmlower 95% CI bound

Data as of: June 1, 2000-restricted to units that passed clearance Data from: Forms 14, 15, 16 Data source: UC Tables 099, 101, 529-I07, 532-E03 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

4-15 
Figure 4-5: Overall Dust Lead Loading Results (ug/ft2) (Logarithmic Scale)

(Based on dwelling unit arithmetic mean of all wipes for a specified surface type. Data presented are 5th, 25th, median, 75th and 

95th percentiles)

16 20

1093

237

4486

139 151

5975

1

10

100

1000

10000

100000

1000000

Vacant Occupied Vacant Occupied Vacant Occupied Vacant Occupied

Int. Floors Entry Floors Sills Troughs

Sample Location and Occupancy

Dust Lead Loading (ug/ft2)

median

Data as of: June 1, 2000-restricted to units that passed clearance Data from: Forms 01, 19 Data source: UC Tables 27A, 27B, 33A, 37A, 37B, 538A, 538B 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

4-16 
TABLE 4-4: Pre-Intervention Geometric Mean Dust Lead Loading (ug/ft2

)

a by Type, Occupancy, and Grantee

Dust Lead Loading Results (ug/ft2) 

Interior Floorsb Entry Floorsb Window Sills Window Troughs 

Grantee Vacant Occup. Vacant Occup. Vacant Occup. Vacant Occup. 

Alameda County GM (GSD) 

# DUs 

32 (7) 

18 

6 (4) 

139 

133 (3) 

12 

17 (5) 

78 

181 (6) 

18 

116 (5) 

139 

614 (4) 

10 

846 (7) 

79 

Baltimore GM (GSD) 

# DUs 

246 (4) 

288 

48 (5) 

92 

233 (5) 

267 

30 (6) 

88 

2,480 (4) 

286 

854 (8) 

91 

3,783 (7) 

282 

1,444 (9) 

90 

Boston GM (GSD) 

# DUs 

165 (4) 

11 

26 (5) 

57 

152 (8) 

11 

33 (4) 

57 

1,242 (5) 

11 

358 (6) 

56 

22,731 (5) 

13 

6,193 (10) 

56 

California GM (GSD) 

# DUs 

41 (6) 

25 

12 (4) 

64 

61 (5) 

25 

14 (4) 

64 

686 (5) 

26 

319 (5) 

57 

995 (4) 

13 

774 (6) 

33 

Chicago GM (GSD) 

# DUs 

38 (6) 

3 

28 (5) 

117 

40 (4) 

3 

20 (4) 

111 

278 (2) 

3 

302 (6) 

113 

303 (8) 

2 

834 (15) 

101 

Cleveland GM (GSD) 

# DUs 

44 (8) 

16 

16 (6) 

126 

50 (6) 

16 

29 (6) 

126 

173 (9) 

16 

387 (7) 

125 

631 (9) 

14 

3,084 (17) 

114 

Mass.c GM (GSD) 

# DUs 

51 (6) 

15 

18 (4) 

119 

51 (7) 

15 

16 (5) 

117 

645 (5) 

15 

302 (7) 

119 

12,032 (5) 

14 

5,452 (12) 

112 

Milw. GM (GSD) 

# DUs 

85 (7) 

16 

15 (3) 

198 

110 (5) 

15 

30 (5) 

197 

2,646 (11) 

67 

437 (6) 

197 

45,524 (7) 

14 

20,962 (11) 

194 

Minnesota GM (GSD) 

# DUs 

21 (11) 

14 

14 (4) 

127 

20 (8) 

14 

18 (5) 

127 

141 (7) 

13 

359 (6) 

123 

1,145 (35) 

13 

11,077 (8) 

116 

New Jersey GM (GSD) 

# DUs 

37 (8) 

8 

3 (2) 

18 

56 (14) 

8 

2 (2) 

18 

137 (6) 

8 

14 (3) 

18 

-- -- 

25 (1) 

2 

New York City GM (GSD) 

# DUs 

208 (7) 

103 

21 (4) 

225 

190 (11) 

100 

23 (4) 

223 

779 (6) 

99 

155 (4) 

223 

1,967 (9) 

86 

669 (4) 

204 

Rhode Island GM (GSD) 

# DUs 

129 (4) 

35 

24 (4) 

124 

214 (5) 

35 

31 (5) 

122 

1,396 (6) 

32 

598 (6) 

124 

12,661 (7) 

32 

13,753 (8) 

117 

Vermont GM (GSD) 

# DUs 

64 (7) 

130 

26 (5) 

174 

91 (7) 

130 

43 (6) 

174 

275 (12) 

118 

206 (8) 

167 

10,610 (7) 

116 

7,472 (7) 

153 

Wisc.c GM (GSD) 

# DUs 

129 (10) 

29 

12 (5) 

151 

149 (11) 

29 

15 (5) 

148 

1,339 (6) 

29 

204 (5) 

148 

40,054 (4) 

28 

7,504 (8) 

139 

All Grantees GM (GSD) 

# DUs 

132 (6) 

711 

17 (5) 

1,731 

147 (7) 

680 

23 (5) 

1,650 

1,001 (8) 

687 

278 (6) 

1,700 

4,849 (9) 

635 

4,049 (12) 

1,510 aLab data out of QC excluded, vacuum samples excluded; no restrictions on sample date. Each data point used to calculate geometric mean is the dwelling unit arithmetic mean of all wipes for 

a specified surface type for all rooms listed on Form 19, page 1. 

bFor floors, samples less than 6 inches on one side excluded. cPost-education samples collected close to intervention were used when available for Massachusetts and Wisconsin. Data as of June 1,2000órestricted to units that passed clearance Data from: Forms 01, 19 Source of data: UC Tables 027-A, 027-B, 33-A, 33-B, 37-A, 37-B, 538-A, 538-B. 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

4-17
Figure 4-6: Geometric Mean and 95% Confidence Intervals for Pre-Intervention Soil Lead 

Concentration (ppm) by Average Soil Cover & Area Sampled

811 814 862

485

1647

843

2029

961

1956

586

1211

574

675 630

796

389

1370

637

1729

719

1385

453

1104

504 562 487

735

312

1140

481

1473

538

981

350

1007

443

0

500

2500200015001000

perimeter play perimeter play perimeter play perimeter play perimeter play perimeter play

1-1.5 1.51-2.5 2.51-3.5 3.51-4.5 4.51-5 Overall

Sample Location & Soil Cover Code

Soil Lead Concentration (ppm)

upper 95% CI boundgmlower 95% CI bound

Soil Cover Code: 1=no bare soil; 2=small amount bare; 3=half bare; 4=mostly bare; 5=all bare. Data as of: June 1, 2000-restricted to units that passed clearanceData from: Form 21 Data source: UC Table 508 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

4-18
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4-19 

The highest dust lead loadings were found on window troughs, then sills, followed by entry 

floors and interior floors (which had lower pre-intervention loadings than originally expected). 

Occupancy status influenced dust lead, especially floor dust lead, with larger loadings observed 

in vacant dwellings. The findings of multivariate statistical modeling of the effects of preintervention variables on dust lead loadings are presented in Chapter 8. 

Pre-intervention dust lead loadings measured in the Evaluation were generally greater than those 

reported in the NSLAH (Jacobs 2002), likely due to the sizeable presence of younger housing in 

the NSLAH versus predominantly pre-1930 housing in the Evaluation. Soil from building 

perimeter areas had higher lead concentrations than those collected from play areas. Soil from 

perimeter areas also had higher lead concentrations when soil cover was limited. All of these 

exposure factors potentially influence the magnitude of lead hazards in a dwelling unit and may 

contribute to childrenís lead-related exposure. 

 

4.4 PRE-INTERVENTION CHARACTERISTICS OF ENROLLED FAMILIES

Information presented in this section is based primarily on initial interviews conducted prior to 

the start of the lead hazard control intervention. All households in enrolled dwellings were 

eligible for participation in the Evaluation. Using procedures approved by their Institutional 

Review Boards, the grantees were required to enroll the household by obtaining informed 

consent to participate from an adult household member prior to conducting an interview. In some 

dwellings, multiple households were present and each household was enrolled. A household 

member could refuse to participate without loss of benefits from the HUD Lead Hazard Control 

Grant Program. 

The number of households and the number of children enrolled in the Evaluation varied greatly 

by grantee. While Baltimore, New York City and Vermont treated the most dwellings, over onethird of each of these granteesí dwellings was vacant prior to intervention. The number of young 

children in the enrolled households also varied by grantee: enrolled households in Minnesota, 

Baltimore, Chicago and Massachusetts averaged 1.5 or more children under 6 years of age per 

household, while households in New York and New Jersey averaged less than 0.5 children per 

household. 

As a result of the varying occupancy rates, recruitment levels and household sizes, the rankings 

of grantees by the number of households or children enrolled per grantee differed from the 

rankings by number of dwellings treated per grantee. The number of households enrolled in the 

Evaluation from New York City and Milwaukee (221 and 194, respectively) was nearly double 

the average number of households enrolled per grantee (110). The number of children enrolled in 

the Evaluation from Milwaukee and Minnesota (263 and 212, respectively) was substantially 

larger than the average number of children enrolled per grantee (126). These grantees with 

higher numbers of enrolled households and children likely exerted relatively greater influences 

on the overall findings of several of the variables discussed in this section. 

In the discussion below, relevant statistics for the US population in general are used to place 

demographic information for enrolled families in context. These statistics were obtained from 

using 1995 data from the American Housing Survey (see description in Section 4.2) and US 

Census data for July 1, 1995. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4-20 

Pre-intervention family characteristics generally show an enrolled population that had a lower 

level of education, lower income, and higher percentage of non-white individuals than the 

general US population (Census 1996, HUD 1997). This finding is not surprising given the grant 

program focus on low-income housing and the focus of the Evaluation on populations most in 

need of lead hazard reduction, i.e., those generally living in older, depressed inner city areas. 

This suggests that the program was effective in targeting resources to units where the risk was 

the greatest. 

4.4.1 Characteristics of Adults 

The amount of formal education completed by adults may be associated with dust lead loadings 

and blood lead levels (Lanphear 1996a). Education levels for principal3 females and males were 

very similar. Overall, approximately one-third each of principal males and females completed 

less than 12 years of schooling, one-third had graduated from high school, and one-third had 

more than 12 years of schooling (Table 4-5). This differs from the 1995 national education 

distribution, where a higher percentage of individuals (47%) stayed in school past high school, 

and only 20 percent of people have less than 12 years of education. 

Poverty has been associated with high blood lead levels in children (Pirkle 1998). Overall, the 

median income of households enrolled in the Evaluation at pre-intervention was $13,000 per 

year, far less than the 1995 national household median of $31,416 (Table 4-6) (HUD 1997). 

Median income for households in Baltimore, California, and Cleveland tended to be lower, in the 

vicinity of $9,000 per year. Median income for households in Boston and Wisconsin tended to be 

higher, at approximately $21,000 per year. 

4.4.2 Characteristics of Children 

Separate information was collected about each enrolled child between the ages of six months and 

six years in a household. Data were collected to document the characteristics of children in the 

Evaluation and help identify conditions that might affect the childrenís blood lead levels. 

4.4.2.1 Gender, Age and Racial/Ethnic Group Distribution. At pre-intervention, enrolled children 

were evenly distributed across gender groups (52% male, 48% female), and evenly distributed 

across age groups, with a median age at the time of enrollment being between 36 and 48 months 

(Table 4-6). Not surprisingly, given that the target child population was supposed to be 6 months 

to 5 years of age, only 3 percent of the enrolled children were 6 years or older, and only 7 

percent were less than 1 year old. Age distributions for individual grantees were generally 

similar, although some grantees such as Boston, California, and Rhode Island had a relatively 

higher proportion of children 48 months or older and fewer that were less than 24 months old. 

Several different racial/ethnic groups were represented in the enrolled children: Black (47%), 

White (23%), Hispanic (17%), Asian or Pacific (8%) (Table 4-5). Another four percent of the 

enrolled children were reported as ìOther.î Compared with 1995 US Census data, the 

Evaluation had higher percentages of racial/ethnic groups that were not White (Table 4-5) 

 

3 Interview information was obtained from a variety of adults, including parents, legal guardians, or primary adult 

caregivers for households with children, and other men and women for households without children. Information 

from these various adults was combined in order to summarize data and identify trends; therefore, for this report, 

these adults were grouped under the terms ìprincipal malesî and ìprincipal females.î 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 4-21 

(Census 1996). Certain grantees widely differed from this overall distribution, reflecting regional 

differences in racial/ethnic distributions and the targeting by grantees of areas having a particular 

racial/ethnic makeup. For instance, as shown in Table 4-6, more than 90 percent of children 

enrolled in Baltimore and Cleveland were Black, while more than 90 percent of those in 

Vermont were White. Sixty percent (60%) of enrolled children in California were Hispanic. 

4.4.2.2 Length of Residence for Children. Length of residence for children is an important issue 

because in many instances, previously unexposed children must live in a residence having lowlevel leaded dust for several months for the effects of exposure to lead hazards in that residence 

to be fully reflected in the blood. A wide distribution in length of residence was observed for 

enrolled children at pre-intervention, with approximately one-third residing at the address of the 

enrolled dwelling less than 12 months, one third 12 to less than 24 months, and one-third 24 

months or more (Table 4-6). Overall, 15 percent of enrolled children had lived in their homes for 

6 months or less. Boston, New York City and Wisconsin had slightly higher percentages of longterm child residents, with 50 percent or more of their enrolled children living in the residence for 

24 to more than 48 months. Half of Minnesotaís enrolled children had lived in their residence for 

less than 12 months (Table 4-6). 

4.4.2.3 Previous Blood Lead Testing History. Although universal screening for blood lead was 

recommended by the CDC in 1991, such testing was typically focused in areas that were 

expected to pose high risks to young children. Pre-intervention Evaluation data corroborate this 

tendency: as discussed in Section 2.2, most grantees tended to enroll children from 

neighborhoods expected to have lead hazard concerns, and 77 percent of the enrolled children 

had had a blood lead test prior to any testing done as part of the Evaluation. Only in California 

were fewer than 50 percent of enrolled children previously tested, while 95 percent of those in 

Boston had been tested previously. 

Although 40 percent of previously tested children reportedly had been previously lead-poisoned, 

grantee-specific reports of lead poisoning were highly variable (Figure 4-7), possibly depending 

on whether grantees used lead-poisoned children as a major criterion for enrolling households 

and dwelling units in the Evaluation. For example, over 50 percent of previously tested children 

enrolled by Baltimore, Chicago, Cleveland and Minnesota (which specifically enrolled units with 

lead-poisoned children) were reported to be previously lead poisoned, while less than 15 percent 

of previously tested children enrolled by Boston, California and New York City had such reports. 

4.5 PRE-INTERVENTION BLOOD LEAD LEVELS

The information provided in this section is useful in determining the differences in the impact of 

lead hazard control interventions on the blood lead levels of children who were lead poisoned 

prior to the intervention compared with those who were not previously lead poisoned. The 

influence of factors such as season, childís age, race, and sex on pre-intervention blood lead 

levels are discussed in order to help ensure that interventions are not unjustifiably credited or 

penalized for blood lead changes that would have been expected due to such influences. 
TABLE 4-5: Comparison of Pre-Intervention Family Characteristics with General US Populationó 

All Grantees Combined 

Category 

Total Number (Percent) of Individuals 

within Category, National Evaluation 

Percentage of Individuals within 

Category, US Population 

(Gender/Race: Children <6years old) 

Gender of Children: Female 854 (48%) 49% 1Male 912 (52%) 51% 1Total Number of Children: 1,766 (100%) -- Racial/Ethnic Group of Children:Black 833 (47%) 15% 1 White 405 (23%) 65% 1Hispanic 304 (17%) 16% 1 Asian or Pacific 142 (8%) 4% 1Other 75 (4%) 1% 1 Total Number of Childrena: 1,759 (100%) -- Years of Schooling: Principal Males Principal Females Males & Females Combined Less than 12 years 270 (35%) 527 (36%) 19% 212 years 266 (34%) 507 (35%) 34% 2More than 12 years 234 (31%) 433 (29%) 47% 2Total Number of Householdsb 770 (100%) 1,467 (100%) -- aNumber of children excluded due to missing data for specified variable: age, 3; racial/ethnic group, 6; length of residence, 1. bNumber of households excluded due to non-responses: years of schooling for females, 81; for males, 778. 

Data as of June 1, 2000-restricted to units that passed clearance Data from: Forms 04, 05 Source of Data: UC Tables 073, 151, 153, 070, 071, 072, 11995 Population Estimates (Census 1996), 2 1995 American Housing 

Survey (HUD 1997) 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

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TABLE 4-6: Summary Of Selected Household Characteristicsa―By Grantee 

Grantee Name Length of Residence 

of Children 

Age of Children Racial/Ethnic 

Group of Childrenb

Household Median 

Annual Income 

All Grantees 0-<12 months: 33% 

12-<24 months: 28% 

24 ->48 months: 39% 

0-<24 months: 25% 

24-<48 months: 37% 

48 months or more: 38% 

Black: 47% 

White: 23% 

Hispanic: 17% 

$13,000 

Alameda County 0-<12 months: 26% 

12-<24 months: 29% 

24 ->48 months: 45% 

0-<24 months: 27% 

24-<48 months: 33% 

48 months or more: 40% 

Hispanic: 36% 

Black: 26% 

White: 26% 

$12,600 

Baltimore 0-<12 months: 35% 

12-<24 months: 22% 

24 ->48 months: 43% 

0-<24 months: 24% 

24-<48 months: 40% 

48 months or more: 36% 

Black: 96% $9,400 

Boston 0-<12 months: 15% 

12-<24 months: 32% 

24 ->48 months: 53% 

0-<24 months: 20% 

24-<48 months: 31% 

48 months or more: 49% 

Black: 56% 

Other: 22% 

$22,000 

California 0-<12 months: 35% 

12-<24 months: 24% 

24 ->48 months: 41% 

0-<24 months: 21% 

24-<48 months: 32% 

48 months or more: 48% 

Hispanic: 60% 

Asian/Pacific: 21% 

$9,900 

Chicago 0-<12 months: 33% 

12-<24 months: 26% 

24 ->48 months: 41% 

0-<24 months: 23% 

24-<48 months: 44% 

48 months or more: 33% 

Black: 69% 

Hispanic: 28% 

$10,500 

Cleveland 0-<12 months: 38% 

12-<24 months: 32% 

24 ->48 months: 30% 

0-<24 months: 29% 

24-<48 months: 31% 

48 months or more: 40% 

Black: 90% $9,600 

Massachusetts 0-<12 months: 37% 

12-<24 months: 30% 

24 ->48 months: 33% 

0-<24 months: 24% 

24-<48 months: 44% 

48 months or more: 32% 

Hispanic: 42% 

White: 25% 

Black: 18% 

$14,000 

Milwaukee 0-<12 months: 44% 

12-<24 months: 25% 

24 ->48 months: 31% 

0-<24 months: 24% 

24-<48 months: 39% 

48 months or more: 37% 

Black: 71% $12,000 

Minnesota 0-<12 months: 50% 

12-<24 months: 27% 

24 ->48 months: 23% 

0-<24 months: 26% 

24-<48 months: 37% 

48 months or more: 37% 

Black: 44% 

White: 27% 

Asian/Pacific: 16% 

$14,000 

New Jersey 0-<12 months: 0% 

12-<24 months: 0% 

24 ->48 months: 100% 

0-<24 months: 0% 

24-<48 months: 50% 

48 months or more: 50% 

Hispanic: 100% $16,100 

New York City 0-<12 months: 15% 

12-<24 months: 28% 

24 ->48 months: 57% 

0-<24 months: 22% 

24-<48 months: 43% 

48 months or more: 35% 

Black: 62% 

Hispanic: 38% 

$16,000 

Rhode Island 0-<12 months: 27% 

12-<24 months: 37% 

24 ->48 months: 36% 

0-<24 months: 24% 

24-<48 months: 29% 

48 months or more: 47% 

White: 55% 

Hispanic: 16% 

$12,900 

Vermont 0-<12 months: 28% 

12-<24 months: 31% 

24 ->48 months: 41% 

0-<24 months: 30% 

24-<48 months: 30% 

48 months or more: 40% 

White: 90% $13,100 

Wisconsin 0-<12 months: 15% 

12-<24 months: 35% 

24 ->48 months: 50% 

0-<24 months: 21% 

24-<48 months: 38% 

48 months or more: 41% 

White: 65% 

Asian/Pacific: 27% 

$20,600 

a

Children living in units that passed clearance and had interview data available. 

b

Categories included in column if they were in at least the top 70% of the granteeís children. For all grantees, 8% of children 

were Asian/Pacific and 4% were reported in ìotherî racial/ethnic groups. 

Data as of: June 1, 2000; Data from: Forms 04, 05; Data source: UC Tables 10A, 070, 071, 072, 073 
Figure 4-7: Blood Lead Poisoning History of Children Tested Prior to Enrollment in Evaluation

40%

35%

50%

13%

9%

69%

54%

34%

36%

52%

5%

29%

42%

25%

0%

90%80%70%60%50%40%30%20%10%

100%

ALL AC BA BO CA CH CL MA MILW MN NYC RI VT WI

Grantee

Percentage of Previously Tested Children who were Lead-Poisoned

NJ Excluded due to too few children with data for this variableData as of: June 1, 2000-restricted to units that passed clearanceData from: Form 05 Data source: UC Tables 124, 125 

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4-25 

Because grantees used different methods to recruit households and dwelling units into the 

Evaluation, grantee-specific differences in blood lead levels of enrolled children may be 

expected and are highlighted as appropriate. 

This section focuses on the 1,274 children who had blood lead test results available at preintervention, from testing conducted just prior to or after enrollment in the Evaluation. Blood 

lead levels are generally discussed in terms of the following ìbreakpointsî (CDC 1991): 

• <10 μg/dL: Level at which CDC recommended reassessment or re-screening in one year, but 

no additional action unless exposure sources change. 

• At or exceeding 20 μg/dL: At levels between 20 and 44 μg/dL, CDC recommended 

environmental investigation, clinical management, and lead hazard control intervention.4 

At pre-intervention, over half of the tested children (54%) had blood lead levels less than 10 

μg/dL, with a median blood lead level of 9 μg/dL for all tested children at pre-intervention 

(Figure 4-8). Pre-intervention blood lead levels varied considerably among grantees, with four 

grantees enrolling a higher-than-average percentage of children who had blood lead levels below 

10 μg/dL: Alameda County (85% of its tested children, median=5 μg/dL); California (89%, 

median=4 μg/dL); New York City (96%, median=5 μg/dL); and Wisconsin (82%, median=6 

μg/dL). 

Overall, 15 percent of the tested children had blood lead levels between 20 and 44 μg/dL. 

Cleveland (27%, median=13 μg/dL) and Milwaukee (25%, median=13 μg/dL) had an even 

higher percentage of tested children with blood lead levels in this range (Figure 4-8). 

4.5.1 Comparison of Evaluation Blood Lead Levels with NHANES III 

The third National Health and Nutrition Examination Survey (NHANES III) Phase 2 is a 

nationally representative survey of the civilian, non-institutionalized U.S. population from 1991 

through 1994.. Blood lead level results for NHANES III are not directly comparable to those 

from the Evaluation since NHANES III Phase 2 provided data collected somewhat earlier (1991 

through 1994) than the pre-intervention dates for the Evaluation, which were collected from 

approximately 1994 to 1997. In addition, in the reporting of blood lead levels from NHANES III, 

children aged 1 to 5 years were considered as a group, while the Evaluation generally grouped 

children between 6 months to 6 years of age. With these caveats in mind, NHANES III reported 

a mean blood lead level of 2.7 μg/dL for children 1 to 5 years of age, much lower than the 

geometric mean blood lead level of 9 μg/dL reported for children enrolled in the Evaluation. In 

addition, while 46 percent of Evaluation children had pre-intervention blood lead levels of 10 

μg/dL or greater, less than five percent of the US child population had blood lead levels in this 

range. This is an expected result since grantees generally targeted neighborhoods or communities 

where lead hazards were of concern, whereas the NHANES III was representative of the entire 

United States population. 

 

4

 If confirmed levels were between 15 and 19 μg/dL, CDC (1991) also recommended these actions be taken if 

sufficient resources were available. 
4-26 

Data as of: June 1, 2000-restricted to units that passed clearance Data from: Form (09 or 05) (04 or 01 for age) Data Source: UC Table 024 NOTE: NJ excluded because only 1 child had data. 

Figure 4-8: Percentage of Enrolled Children Within Each Specified Range of Pre-Intervention 

Blood Lead Levels

54%

85%

62%

50%

89%

24%

36%

60%

34%

52%

96%

49%

64%

82%

31%

9%

24%

44%

11%

57%

37%

34%

41%

30%

4%

37%

32%

15%

15%

6%

14%

6%

0%

19%

27%

6%

25%

18%

0%

14%

4%

3%

0%

90%80%70%60%50%40%30%20%10%

100%

ALL AC BA BO CA CH CL MA MILW MN NYC RI VT WI

median

9ug/dL

median

5ug/dL

median

8ug/dL

median

10ug/dL

median

4ug/dL

median

14ug/dL

median

13ug/dL

median

9ug/dL

median

13ug/dL

median

9ug/dL

median

5ug/dL

median

10ug/dL

median

7ug/dL

median

6ug/dL

Grantee

Percentage of Enrolled Children

<10 ug/dL 10-<20 ug/dL 20 ug/dL or more

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4.5.2 Influence of Various Factors on Pre-Intervention Blood Lead Levels 

As expected, blood lead levels tended to vary with the childís age. Pre-intervention blood lead 

levels appeared to increase as children approached 24 to 36 months of age and then began to 

decline in older children. Children 6 to 12 months of age had the lowest geometric mean blood 

lead level (5.3 μg/dL). The 24- to 36-month age group had the highest geometric mean blood 

lead level (10.0 μg/dL) (Figure 4-9). As expected, pre-intervention blood lead levels appeared to 

increase as children approached 24 to 36 months of age and then began to decline in older 

children. This overall trend is generally comparable with NHANES III, which reported that the 

geometric mean blood lead level in 1 to 2 year olds (3.1 μg/dL) was higher than that of 3 to 5 

year olds (2.5 μg/dL) (Pirkle 1998). 

Children that were reported to be in the Black and ìOtherî racial/ethnic groups had higher 

geometric mean blood lead levels (10.9 and 10.1 μg/dL, respectively) than those in the Hispanic, 

Asian, or White racial/ethnic groups (7.3, 7.3 and 7.0 μg/dL, respectively) (Figure 4-10). Again, 

although NHANES III generally reported much lower blood lead levels, the overall racial trend 

held, with Black non-Hispanic individuals having a larger geometric mean blood lead level (2.8 

μg/dL) than that of White non-Hispanic individuals (2.2 μg/dL) (Pirkle 1998). 

The geometric mean blood lead level for males was the same as that for females (8.9 μg/dL). 

This trend is different from NHANES III data, which reported a higher geometric mean blood 

lead level for males (2.8 μg/dL) than for females (1.9 μg/dL) (Pirkle 1998). 

Pre-intervention blood lead levels tended to vary by season, with higher blood lead levels 

generally present during the summer and fall months and lower levels in the winter (Figure 4-

11). This is the same trend observed previous EPA study of children in Milwaukee, which 

observed that blood lead levels in the summer were about 40 percent higher than those in the 

winter (EPA 1996a). For the Evaluation, the magnitude of the difference appeared to be 

approximately 2 μg/dL from peak to trough. During the months of April, June and July, the 

blood lead levels were lower than expected. These differences may be due in part to variations in 

when grantees tested children. For example, in July, over one-fifth of the blood lead results were 

reported from Wisconsin, a grantee that had lower blood lead levels across all seasons. 

Children who lived in older dwelling units had higher geometric mean blood lead levels, with 

concentrations tending to decrease as building age decreased. Blood lead levels in children living 

in dwelling units constructed in the decades before 1920 (geometric means ranging from 8.1 to 

8.5 μg/dL) were higher than those for children living in units constructed in the decades after 

1940 (geometric means ranging from 4.8 to 5.1 μg/dL). This trend is similar to that observed in 

NHANES III, which found that people living in homes built before 1946 had a slightly higher 

geometric mean blood lead level (2.6 μg/dL) than those living in homes built between 1946 and 

1973 (2.3 μg/dL) (Pirkle 1998). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

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Figure 4-9: Pre-Intervention Blood Lead Levels (ug/dL) by Age of Child

6.1

9.8

10.9

10.6

9.6

8.7

5.3

9.0

10.0 9.8

8.8

8.0

4.6

8.3

9.2 9.1

8.1

7.4

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

6-<12 12-<24 24-<36 36-<48 48-<60 60 or more

Age of Child (months)

Blood Lead Level (ug/dL)

Upper 95% CI bound

GM

Lower 95% CI bound

Figure 4-10: Pre-Intervention Blood Lead Levels by Racial/Ethnic Group and 

Gender

11.9

8.0

9.2

7.8

12.8

9.4 9.4

10.9

7.3 7.3 7.0

10.1

8.9 8.9

10.0

6.6

5.7

6.2

8.0 8.4 8.5

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Black Hispanic Asian White Other Male Female

All Racial/Ethnic Groups

Racial/Ethnic Group and Gender

Blood Lead Level (ug/dL)

Upper 95% CI bound

GM

Lower 95% CI bound
Figure 4-11: Pre-Intervention Blood Lead Levels (ug/dL) by Month of Sample Collection

9.6 9.6 9.6

8.9

10.7

10.4

10.0

10.9

10.3 10.4 10.4

9.5

8.5 8.4 8.5

7.8

9.5

9.2

8.8

9.7

9.2 9.2 9.2

8.1

7.5

7.3

7.5

6.8

8.4

8.1

7.7

8.6

8.2 8.2 8.2

6.9

9.08.07.06.0

12.011.010.0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month of Sample Collection

Blood Lead Level (ug/dL) Upper 95% CI bound GMLower 95% CI bound

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4.5.3 Discussion 

Grantee-specific reports of lead poisoning occurring prior to enrollment in the Evaluation were 

highly variable, possibly due to variation in the use of this factor as an enrollment criterion. Over 

half of enrolled children had blood lead levels less than 10 μg/dL at pre-intervention, 31 percent 

had levels between 10 and 19 μg/dL, and 15 percent had blood lead levels of 20 μg/dL or 

greater. These levels were generally much higher than those observed for a similar age group of 

children in the NHANES III survey. 

Blood lead levels varied with age, peaking in the 24 to <36-month age group. Blacks and 

ìOtherî racial/ethnic groups had higher blood lead levels than Hispanics, Asians, or Whites. No 

gender-related differences in blood lead levels were noted. Seasonal influences were apparent, 

with higher levels in the summer and lower levels in the winter. Higher blood lead levels were 

observed in older dwelling units. The findings of multivariate statistical modeling of the effects 

of pre-intervention variables on blood lead levels are presented in Chapter 9. 
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5-1 

5.0 DESCRIPTION OF INTERVENTIONS 

5.1 DESCRIPTION OF THE INTERVENTION DATA COLLECTION PLAN/DEFINITION OF TERMS

A main attribute of the HUD LHC Grant Program has been the flexibility that grantees are given 

to select the lead treatments for any particular dwelling. The grantees have had the freedom to 

treat all areas of the property or to treat only some locations (interior, exterior, and/or soil). The 

grantees can also decide on the intensity of the treatments. Possible treatment intensities have 

ranged from specialized cleaning to full abatement of all lead-based paint. Especially in the 

initial rounds of the grants, HUD encouraged grantees to experiment with different levels of lead 

hazard control activities. 

Grantees were allowed to experiment because there is no apparent single state-of-the-art 

intervention to control lead-based paint hazards. For example, some programs believed that 

windows containing lead-based paint must be replaced to protect the health of residents. Other 

programs contended that by using lower level/lower cost treatments, more residents could be 

served, while still protecting their health. In some cases, grantees even decided to leave some 

limited or negligible lead-based paint hazards untreated, believing that these limited hazards did 

not endanger the residentís health. 

The Evaluation collected information about the lead interventions on two levels: a general 

characterization of the intensity of the intervention for each dwelling unit and a detailed list of all 

lead hazard control treatments. Because readers may be interested in different levels of detail, the 

report examines the costs and effectiveness of interventions at both levels. At the dwelling unit 

level, comparisons can be made between low-intensity interventions (e.g., cleaning and spot 

painting) and more intensive interventions (e.g., partial or full abatement). At the individual 

treatment level, comparisons can be made between low-level treatments to a component (e.g., 

paint stabilization of a window) and more intensive treatments to that component (e.g., window 

replacement). 

5.1.1 Dwelling Unit Interventions 

The system to characterize the intensity of the lead interventions at the dwelling unit level was 

originally developed in the early 1990s by URC, Inc. a consultant for a Baltimore nonprofit 

housing developer. The developer used this system to develop a strategic plan to address the 

lead-based paint hazards in its varying stock of housing. The Evaluation designers used the same 

consultant to create a system to categorize the lead interventions of the grantees. Although the 

categorization system was, in essence, unique to the Evaluation, it can be related to the classes of 

lead hazard control activities, such as interim controls and abatement, discussed in the HUD 

Guidelines. 

The different levels of lead interventions are called strategies, from their roots as elements of a 

strategic plan. Grantees reported the strategies that were applied to each dwelling unit using a 

three-part ìstrategy codeî: one strategy for each region of the dwelling (i.e., dwelling interior, 

building exterior, and site/soil). Higher strategy levels reflect more intensive interventions. A list 

of the strategy codes used in the Evaluation is found in Table 5-1. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-2 

Table 5-1: Strategy Code Definitions 

Strategy Definition 

Interior 01 No Action 

 02 Cleaning, Spot Paint Stabilization Only 

 03 Level 02 plus 

Complete Paint Stabilization, Floor Treatments 

 04 Level 03 plus 

Window Treatments 

 05 Level 04 plus 

Window Replacement, Wall Enclosure/Encapsulation 

 06 All Lead-Based Paint Enclosed, Encapsulated, or Removed 

(Meets Public Housing Abatement Standards) 

 07 All Lead-Based Paint Removed 

Exterior 00 No Action 

 01 Spot or Partial Paint Stabilization 

 02 Complete Paint Stabilization, Porch Treatments 

 03 Level 02 plus 

Porch/Trim Enclosure, Stabilization or Encapsulation 

 04 All Lead-Based Paint Enclosed, Encapsulated, or Removed 

 05 All Lead-Based Paint Removed 

Site 0 No Action 

 1 Cover Soil with Temporary Cover (Mulch, Stone) 

 2 Level 01 plus 

Seed, Install Barriers (Bushes, Fencing) 

 3 Level 02 plus 

Partial Soil Removal, Plant Sod 

 4 Complete Soil Removal or Enclosure with Asphalt, Concrete 

Glossary of Treatments

Encapsulation - The application of a covering or coating that acts as a barrier between lead-based paint and the 

environment, the durability of which relies on adhesion and which has an expected life of at least 20 years. 

Enclosure - The application of rigid, durable construction materials that are mechanically fastened to the substrate to 

act as a barrier between lead-based paint and the environment. 

Paint Stabilization - The process of repainting surfaces coated with lead-based paint, which includes the proper 

removal of deteriorated paint and priming. 

Paint Removal - The complete removal of lead-based paint by wet scraping, chemical stripping, or contained 

abrasives. 

Removal/Replacement - The removal/replacement of a building component that was coated with lead-based paint. 

Window Treatments - The process of eliminating lead-containing surfaces on windows that are subject to friction or 

impact through the removal of paint or enclosure of certain window components.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-3 

Strategies in the Evaluation are defined by the treatments applied to the dwelling rather than by 

the condition of the dwelling after treatment is completed. For example, when the primary 

treatment to two different dwelling units was complete paint stabilization, both dwellings would 

be classified with the same strategy. It did not matter in the strategy assignment that one 

dwelling might have had its windows replaced prior to enrollment, while the second dwelling 

retained its lead-painted windows. 

By defining the lead intervention by what was done, the objectives of the study could be met 

without placing an additional data collection burden on the grantees. The effect of intervention 

strategies on environmental and biological lead levels was examined by comparing pre- and 

post-intervention conditions of the dwellings. Pre-existing conditions, such as the previously 

replaced windows, should already be accounted for by the pre-intervention data. Had the 

strategies been defined by outcomes, grantees would have needed to conduct a complete 

inventory of the lead-based paint and lead-based paint hazards after the intervention to verify the 

reported outcomes. Such an inventory was not considered feasible. 

In addition to characterizing lead hazard control work using intervention strategies, the 

Evaluation team collected detailed information about individual lead hazard control treatments. 

Grantees were asked to provide a list of construction specifications that described every lead 

hazard control treatment that was conducted at a dwelling unit. 

5.1.1.1 Reporting Lead Hazard Control Strategies. It must be emphasized that neither HUD nor 

the Evaluation team dictated the lead hazard control treatments to be used by the grantees. The 

grantees selected treatments and then fit the work to the Evaluation strategy definitions. Thus, 

the strategy definitions presented on Table 5-1 are examples of the predominant treatments 

within each strategy category. The strategy definitions do not specify exactly what was done to 

each dwelling. While the Evaluation team tried to standardize the definitions of strategies, in a 

small percentage of the cases, similarly treated dwellings may have been assigned different 

interior strategies. In some homes, mixtures of treatments were done that did not neatly fit into 

one strategy. For example, New York City conducted work in some dwellings where walls and 

ceilings were enclosed, trim was replaced, and windows were only minimally treated because 

most had already been replaced. Without window replacement, these units did not fall into 

Interior Strategy 05, but these treatments were much more intensive than paint stabilization so 

Interior Strategy 03 was too low. These units were thus classified as Interior Strategy 04 even 

though they did not receive traditional window treatments such as jamb liners.

Grantees were responsible for identifying the strategies performed at each dwelling. A potential 

drawback of having grantees designate the intervention strategies was that each grantee might 

have had a slightly different interpretation of the strategy definitions. In an attempt to avoid this 

problem (poor inter-rater reliability), the consultant who developed the strategy system was 

retained to compare each set of strategy codes with the scope of the specifications for each 

dwelling. Strategy codes that deviated significantly from the scope of the specifications were 

returned to the grantee for revision. This review not only corrected inappropriately coded 

strategies but also helped to standardize the reporting of future strategy codes.1

 

1

 At the end of the study, the Evaluation team developed a computer program to compare reported interior strategies 

with the specifications for the interior treatments. Based on this review, it was determined that 15 percent of the 

interior strategies should be reclassified to better reflect the level of lead hazard control. The reclassified interior 

strategies are used in this report. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-4 

5.1.1.2 Concurrent Work. The flexibility that was given to grantees when determining what 

would be done to each dwelling went beyond decisions about how to treat lead hazards and 

included decisions about the complete scope of the construction project. The HUD Office of 

Lead Hazard Control (presently known as the Office of Healthy Homes and Lead Hazard 

Control) encouraged the integration of lead hazard control activities with general housing 

rehabilitation activities when the combination of such activities made economic and 

programmatic sense. While HUD LHC Grant Program funds could not be used to carry out 

major rehabilitation activities, grantees could combine the grant funds with other federal, state or 

local funds to complete a comprehensive project. Residents would benefit from a comprehensive 

project when a dwelling unit had other housing code and safety hazards that could not be 

addressed with HUD LHC Grant Program funds. Taxpayers also benefit from the potential cost 

efficiencies of rehabilitating low-income housing and controlling lead hazards simultaneously. 

Comprehensive projects may have offered benefits to residents and the general public, but they 

added a complication for the Evaluation team. The distinction between a lead hazard control 

activity and a basic construction activity was not always clear. Consider a building exterior that 

was coated with intact lead-based paint. A grantee may not have considered treating intact leadbased paint as a priority for lead hazard control, but the grantee could have decided to apply 

exterior siding using another funding source. While the siding would be applied primarily for 

reasons such as reduced maintenance costs or improved energy efficiency, it could also be 

expected to have long-term lead hazard control benefits. 

The Evaluation team found it impossible to define rigid rules to distinguish between lead work 

and non-lead work. Instead, grantees were given guidance to generally classify work on leadbased paint hazards as a lead hazard control activity and to use their own judgment in other 

situations, such as the example above. Non-lead work activities that occurred between the 

collection of the initial pre-intervention environmental samples and the immediate postintervention samples (clearance) were to be reported. Non-lead work was given the term 

concurrent work. Grantees determined what work was concurrent work, calculated the cost of 

these activities and then classified the extent of the concurrent work based on these costs. 

Concurrent work costs were classified as $5,000 or less; $5,001 to $15,000; $15,001 to $25,000; 

and more than $25,000. 

5.1.2 Individual Lead Hazard Control Treatments 

For a lead program that is considering (or reconsidering) its strategic plan, the effectiveness of 

different strategies on housing in different conditions is likely to be of critical importance. This 

level of analysis, however, does not provide the level of detail needed for a specification writer, 

contractor or property owner to decide how to treat a particular building component. In order for 

the Evaluation team to examine the effectiveness of different treatments at the building 

component level, grantees were told to report all lead hazard control treatments that they 

performed in each enrolled dwelling unit. 

To help facilitate the reporting of this information, grantees were given a copy of SpecmasterÆ, a 

specification-writing and cost-estimating software program developed by The Enterprise 

Foundation to assist nonprofit developers of lower-income housing design and estimate the costs 

of their projects and then solicit bids (Enterprise 1994). Some grantees used SpecmasterÆ in this 

manner to streamline the specification writing and contractor selection process. In addition, 

SpecmasterÆ offered the grantees the ability to report treatments in a uniform manner so that 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-5 

they could be compared across all grantees. Grantees were expected to confirm that all 

treatments were completed as written prior to submitting the specifications for a particular 

dwelling unit. 

SpecmasterÆ contains a master database of detailed write-ups for more than 2,000 housing 

rehabilitation specifications. Periodically during the Evaluation, the master database was revised 

when grantees requested changes based on special local conditions. Over 400 specifications 

related to lead hazard control were included in the final database. An example of a SpecmasterÆ 

specification is titled: Trim ñ Replace 1î x 3î. The specification included a detailed (39-word) 

description of the method of properly removing the old trim, disposing of it and installing the 

new trim. The specification also included a recommended unit of measure for determining the 

amount of work performed, in this case, linear feet. 

The use of SpecmasterÆ served an important function in standardizing the descriptions of 

component treatments and limiting the number of unique potential treatments. However, with 

over 400 lead specifications, the final number of different specifications used proved unworkable 

for evaluation purposes. Before analyses began, the Evaluation team reviewed the specifications 

and collapsed them into a more manageable number of categories. These categories are called 

equivalent treatment categories. 

Equivalent treatment categories were developed separately for cost analyses and effectiveness 

analyses. For example, for cost analyses, Trim ñ Replace 1î x 3î was combined with seven other 

trim replacement specifications to be examined as Trim - Modern Molding. For effectiveness 

analyses, Trim ñ Replace 1î x 3î was combined with 46 other trim replacement specifications to 

be examined as Trim ñ Remove/Replace Component. The criteria for combining treatments for 

cost analyses were more restrictive because the Evaluation team believed that certain attributes 

would matter for cost (i.e., historic trim v. modern trim), but they would not impact leaded dust 

generation that could modify effectiveness outcomes. 

5.2 DESCRIPTION OF THE LEAD HAZARD INTERVENTIONS AT THE DWELLING UNIT LEVEL

A total of 2,920 dwelling units were treated as part of the Evaluation. Grantees submitted 

complete and accurate construction data (i.e., a strategy report form and a SpecmasterÆ 

report for the dwelling interior and exterior) and evidence of clearance for 2,615 (90%) of these 

dwellings. The 2,615 dwellings were contained in 1,440 buildings. 

5.2.1 Lead Hazard Control Strategies 

Grantees used a variety of lead hazard control strategies: 2,583 dwellings (99%) had interior 

work, 1,827 dwellings (70%) had treatments done to the exterior of the building, and 343 (13%) 

had soil work (Table 5-2). The most common combination of strategies was Interior Strategy 05 

along with treatments to the exterior and no soil treatment (1,062 dwellings (41%)). Interior 

Strategy 05 is defined as the abatement of lead-based paint from windows in the dwelling, 

primarily by window replacement, and the treatment of other lead-based paint hazards in the 

dwelling. Although the intensity of the treatments to the other building components is not part of 

the strategy definition, grantees tended to stabilize the paint on identified hazards. However, 

interior strategy 05 did not preclude other components from being treated with more intensive 

treatments. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

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Table 5-2: Frequency of Dwelling Units Treated by Interior Strategy 

and Whether Exterior and/or Soil Work was Conducted 

Treatment to 

Building Exterior 

No Treatment 

to Building Exterior 

Interior Strategy 

Soil 

Treatment 

No Soil 

Treatment 

Soil 

Treatment 

No Soil 

Treatment 

01 ñ None 16 13 2 1 

02 - Spot Painting/Cleaning 39 49 3 125 

03 ñ Complete Painting 25 130 2 179 

04 ñ Complete Painting plus 

Additional Window Treatments 

30 241 13 137 

05 ñ Partial Abatement of Lead 

including Window Abatement 

171 1,062 39 160 

06/07 ñ Full Abatement of Lead 3 48 0 127 

Total Dwellings 2,615 284 1,543 59 729 

Data from: Form 23, Question 2 

Data as of: June 1, 2000 

Source of Data: UC Table 517

Another 241 (9%) of the dwellings had treatments to the exterior and no soil treatments, but were 

treated with Interior Strategy 04. Interior Strategy 04 is defined as an intervention of the dwelling 

that includes window treatments that are more intensive than paint stabilization, but less 

intensive than the removal or replacement of the lead-based paint, along with the treatment of 

other lead-based paint hazards in the dwelling. 

While these two combinations of strategies made up half of the dwellings, a diversity of 

strategies existed that allowed the effectiveness of a number of different treatments to be 

compared. At least 20 dwellings were treated within the strategy combinations that included 

Interior Strategies 02-05 and either exterior and site treatments, exterior treatments without site 

treatments, or no exterior/site treatments (Table 5-2). However, some combinations were rarely 

used, so the ability to measure effects was limited for treatment combinations such as interior 

strategies with just soil treatments; full interior lead abatement with exterior/soil treatments; and 

all combinations with no interior work. 

5.2.1.1 Interior Strategies. The most common interior strategy was Interior Strategy 05, the 

partial abatement of lead, including window replacement (1,432 dwellings (55%)) (Table 5-3). 

Other frequently used interior strategies included Interior Strategies 02 through 04. These 

strategy levels represent interventions ranging from minimal spot painting and cleaning of leadcontaminated dust (Interior Strategy 02) to painting with window friction controls (Interior 

Strategy 04). Only 178 dwellings (7%) underwent full abatement of the interior (Interior 

Strategies 06 & 07). Even fewer dwellings (32 dwellings (1%)) had no interior work conducted 

(Interior Strategy 01). 

While a variety of interior strategies were used in the Evaluation, grantees tended to select one or 

two dominant strategies (Table 5-3). Grantees often developed one or two intervention designs 

that they repeated throughout the project. Ten grantees used a single interior strategy in 60 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-7 

percent or more of their dwellings. The remaining four grantees had over half of their dwelling 

units treated by one of two strategies. Ten grantees (Baltimore, Boston, California, Chicago, 

Cleveland, Massachusetts, Minnesota, Rhode Island, Vermont, and Wisconsin) used Interior 

Strategy 04 and 05 in their dwellings. 

Milwaukee, Alameda County, and New York conducted a more diverse selection of interior 

interventions. These grantees had less than three quarters of their dwellings treated by their two 

most frequently used strategies. These three grantees plus Vermont and Minnesota were the only 

grantees to have at least 20 dwellings in at least three of the six interior strategy categories. 

In some cases, strategies were concentrated at a few grantee sites or a single site. For example, 

Alameda County contributed 25 (78%) of the 32 dwellings to which no interior work was 

conducted (Interior Strategy 01). Similarly, New York contributed 127 (71%) of the 178 

dwellings where full abatement (Interior Strategy 06-07)2

 was conducted. Concentrations of units 

from a few grantees were also apparent for Interior Strategies 02 through 04 (Table 5-4). 

As explained in Section 5.1.1, interior strategies were assigned by the grantees based on how 

well they fell into the strategy definitions presented in Table 5-1. Within a strategy, there was 

some variability of the treatments selected. For the grantees that conducted at least five percent 

of their interventions within Interior Strategies 02 through 05, Tables 5-4 and 5-5 present the 

principal interior treatments that each grantee conducted. 

 

2 During the process of writing this report, New York City provided further information about their Interior Strategy 

06 treatments. In most if not all dwellings where this strategy was conducted, the lead-based paint had been 

completely removed. This information suggests that these dwellings might better have been coded as being treated 

with Interior Strategy 07. For most analyses in this report, the full abatement strategies (06-07) are merged so this 

new information has little impact on the findings in later chapters. 
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5-8 

Table 5-3: Number and Percentage of Dwelling Units in which 

a Specific Interior Intervention Strategy was Undertaken 

 Interior Intervention Strategy 

Grantee Total 

 Dwellings with 

 01 02 03 04 05 06 07 Strategy Reported 

Alameda County 25 55 26 14 35 3 5 163 

 15.3% 33.7% 16.0% 8.6% 21.5% 1.8% 3.1% 100% 

Baltimore 0 1 12 5 362 0 4 384 

 0.0% 0.3% 3.1% 1.3% 94.3% 0.0% 1.0% 100% 

Boston 0 1 1 7 49 10 0 68 

 0.0% 1.5% 1.5% 10.3% 72.1% 14.7% 0.0% 100% 

California 0 3 17 3 80 0 0 103 

 0.0% 2.9% 16.5% 2.9% 77.7% 0.0% 0.0% 100% 

Chicago 0 1 6 12 101 0 0 120 

 0.0% 0.8% 5.0% 10.0% 84.2% 0.0% 0.0% 100% 

Cleveland 0 9 5 31 75 0 0 120 

 0.0% 7.5% 4.2% 25.8% 62.5% 0.0% 0.0% 100% 

Massachusetts 0 5 7 17 104 0 0 133 

 0.0% 3.8% 5.3% 12.8% 78.2% 0.0% 0.0% 100% 

Milwaukee 0 56 54 94 18 0 0 222 

 0.0% 25.2% 24.3% 42.3% 8.1% 0.0% 0.0% 100% 

Minnesota 3 21 9 72 38 0 0 143 

 2.1% 14.7% 6.3% 50.3% 26.6% 0.0% 0.0% 100% 

New Jersey 0 0 0 0 1 0 24 25 

 0.0% 0.0% 0.0% 0.0% 4.0% 0.0% 96.0% 100% 

New York City 0 0 168 79 46 127 0 420 

 0.0% 0.0% 40.0% 18.8% 11.0% 30.2% 0.0% 100% 

Rhode Island 0 1 11 8 137 2 0 159 

 0.0% 0.6% 6.9% 5.0% 86.2% 1.3% 0.0% 100% 

Vermont 1 58 12 74 246 0 0 391 

 0.3% 14.8% 3.1% 18.9% 62.9% 0.0% 0.0% 100% 

Wisconsin 3 5 8 5 140 0 3 164 

 1.8% 3.0% 4.9% 3.0% 85.4% 0.0% 1.8% 100% 

All Grantees: 32 216 336 421 1432 142 36 2615 

 1.2% 8.3% 12.8% 16.1% 54.8% 5.4% 1.4% 100% 

Note 1: Table includes dwelling units in single and multifamily buildings. It does not include work conducted 

 on common areas (e.g., hallways) of multifamily buildings. 

Note 2: Interior Strategy Codes: 01=No Action, 02=Cleaning/Spot Painting, 03=02 + Full Painting, 04=03 + Window 

 Treatment, 05=04 + Windows, 06=05 + Public Housing Standard, 07=Lead Free. 

 See Table 4.1 for detailed strategy definitions. 

Data from: Form 23, Question 02 

Data as of: June 1, 2000 

Source of Data: UC Table 176
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5-9 

For Interior Strategy 02, the treatments ranged from cleaning only in Minnesota to a mixture of 

treatments including spot stabilization and replacement of a few small leaded components in 

Alameda County. For Interior Strategy 03, the treatments were generally limited to paint 

stabilization, but the intensities ranged from New York City where over 60 percent of the rooms 

treated had walls, doors, trim and windows repainted (and some trim replaced) to Alameda 

County where less than 40 percent of rooms had windows stabilized and less than 20 percent of 

rooms had doors, trim and walls stabilized. 

Table 5-4: Description of Lead Hazard Control Treatments 

for Dwellings Undergoing Interior Strategy 02 through 04 by Grantee 

Interior 

Strategy 

Grantee Number of 

Dwellings 

% of 

Dwellings 

by Strategy 

Treatment Description 

Vermont 58 27% Spot paint stabilization, window 

trough caps, and cleaning 

Milwaukee 56 26% Cleaning only or cleaning with 

aluminum window wraps/caps 

on window sill and troughs 

Alameda 

Co. 

 55 25% Treatments ranged from cleanonly to spot stabilization with 

replacement of a few small 

leaded components 

Minnesota 21 10% Clean-Only 

02 

Others1 26 12% 

New York 

City 

168 50% Paint stabilization of most 

components except floors; 

replacement of trim. 

Milwaukee 54 16% Paint stabilization of most 

windows and some walls, doors 

and trim; and window sill caps. 

Alameda 

Co. 

26 8% Paint stabilization of some 

components and minor window 

repair. 

California 17 5% Paint stabilization of most 

windows and some walls, doors 

and trim. 

03 

Others2 71 21% 1 Other Grantees conducting Interior Strategy 02: Baltimore (1 Dwelling), Boston (1), California (3), Chicago (1), 

Cleveland (9), Massachusetts (5), Rhode Island (1), Wisconsin (5) 

2 Other Grantees conducting Interior Strategy 03: Baltimore (12), Boston (1), Chicago (6), Cleveland (5), 

Massachusetts (7), Minnesota (9), Rhode Island (11), Vermont (12), Wisconsin (8)

Data from: Form 23, Question 2 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table
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Table 5-4 (continued): Description of Lead Hazard Control Treatments 

for Dwellings Undergoing Interior Strategy 02 through 04 by Grantee 

Interior 

Strategy 

Grantee Number of 

Dwellings 

% of 

Dwellings 

by Strategy 

Treatment Definition 

Milwaukee 94 22% Jamb liners installed in most 

windows; some window sill 

caps; paint stabilization of 

walls, doors, trim and other 

window components 

New York 

City 

79 19% Enclosure of most walls/ceiling; 

replacement of most trim; 

refinishing of most floors; paint 

stabilization of doors; minimal 

window work 

Vermont 74 18% Paint removal and reinstallation 

of sashes or sash replacement 

on most windows; window 

trough caps; paint stabilization 

of doors and trim and some 

walls; paint removal on some 

door sills, jambs and window 

sills. 

Minnesota 72 17% Sash replacement on most 

windows with some trough 

caps; paint stabilization of trim 

and some other components 

Cleveland 31 7% Paint removal from window 

sills/troughs and some sashes; 

paint stabilization of other 

window components, walls, 

doors and trim; enclosure of 

some floors 

04 

Others3

 71 17% 3 Other Grantees conducting Interior Strategy 04: Alameda County (14), Baltimore (5), Boston (7), California (3), 

Chicago (12), Massachusetts (17), Rhode Island (8), Wisconsin (5) 

Data from: Form 23, Question 2 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

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Table 5-5: Description of Lead Hazard Control Treatments 

for Dwellings Undergoing Interior Strategy 05 by Grantee 

Interior 

Strategy 

Grantee Number of 

Dwellings 

% of 

Dwellings 

by Strategy 

Treatment Description 

Baltimore 362 25% Replacement of most windows; paint 

stabilization of most trim and doors 

and some walls; replacement of some 

doors and enclosure of some floors 

Vermont 246 17% Replacement or off-site stripping of 

most windows and/or installation of 

trough caps; replacement of some 

doors and trim; paint removal from 

some trim; enclosure of some floors 

and walls; paint stabilization of doors 

and trim and some walls. 

Wisconsin 140 10% Replacement of most windows and 

some doors; paint stabilization of 

some trim, doors and other 

components. 

Rhode Island 137 10% Replacement of most windows and 

doors and some trim; paint removal 

from some trim; paint stabilization of 

most walls, trim and doors and some 

floors; enclosure of some walls. 

Massachusetts 104 7% Replacement of most windows and 

some trim; paint removal from trim, 

windows and doors; paint stabilization 

of some walls, doors, and trim; 

installation of trough caps 

Chicago 101 7% Replacement of most windows and 

some trim and doors; enclosure of 

walls; paint stabilization of some walls 

and trim 

California 80 6% Replacement of most windows and 

some trim and doors; encapsulation or 

paint stabilization of walls and other 

trim; enclosure of some floors 

Cleveland 75 5% Replacement of most windows and/or 

installation of trough caps; very 

limited replacement or stabilization of 

other components 

05 

Others* 187 13%

*Others include: Alameda County (35), Boston (49), Milwaukee (18), Minnesota (38), New Jersey (1), and New 

York City (46) 

Data from: Form 23, Question 2 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table 
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Interior Strategy 04 had the greatest variety of treatments among the five grantees that most 

frequently conducted this strategy. Window treatments included jamb liners (Milwaukee); sash 

replacement (Minnesota/Vermont); paint removal from sashes (Vermont/Cleveland) and 

stripping or capping of window sills and/or troughs for all four grantees. For these four grantees, 

additional treatments generally included paint stabilization of doors, trim and walls with some 

floor enclosure in Cleveland and some paint removal on door components in Vermont. In New 

York City, windows were generally not treated as part of their Interior Strategy 04, but the other 

treatments were so intensive that the interventions were placed in this strategy. Work in New 

York included enclosure of most walls/ceilings, replacement of most trim, refinishing of most 

floors and paint stabilization of doors. 

Grantees that conducted Interior Strategy 05 generally replaced all or most windows in the 

dwellings. In Vermont, some of the windows were abated with off-site paint removal. A variety 

of additional treatments were conducted in these dwellings, ranging from limited replacement of 

doors (<10% of rooms) and some paint stabilization in Cleveland and Wisconsin to mixtures of 

door and trim replacement, wall or floor enclosure, and paint removal, encapsulation or 

stabilization at the other grantee sites. 

5.2.1.2 Exterior Strategies 

Exterior Strategies by Dwelling 

Seventy percent of the dwellings (1,843) in the Evaluation were in buildings where the exterior 

was treated (Table 5-6). Almost two-thirds of these 1,843 dwellings had lower level exterior 

strategies, such as partial or full paint stabilization, while the remaining dwellings had partial or 

full exterior lead abatement. The most common exterior strategy consisted of full paint 

stabilization (Exterior Strategy 02) and was conducted at 36 percent of all dwellings (51% of 

treated dwellings). Other levels of exterior work included partial abatement (Exterior Strategy 03 

-13% of all), partial painting (Exterior Strategy 01-10%) and full abatement (Exterior Strategy 

04-05 -1%). 

Eleven of the 14 grantees used a single exterior strategy (including Exterior Strategy 00 ñ No 

Treatment) in at least 48% of their dwellings (Table 5-6). However, for most grantees, the 

preference of an exterior strategy was not as strong as for an interior strategy. Only three 

grantees selected one exterior strategy for over three-quarters of their dwellings: New York City 

(Exterior Strategy 00), New Jersey (05), and Baltimore (02). Eight grantees had at least five 

percent of their dwellings classified in each of four categories of exterior strategies. As with 

interior strategy selections, Alameda County, Milwaukee, Minnesota and Vermont tended to 

select a variety of exterior strategies. Eighty-three percent of the dwellings without exterior work 

were contributed by four grantees (New York, Vermont, Minnesota, and Cleveland), with 53 

percent contributed by New York City alone. 
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Table 5-6: Number and Percentage of Dwelling Units on which 

a Specific Exterior Intervention was Undertaken

 Exterior Intervention Strategy 

Grantee Total 

 Dwellings 

 with Strategy

 00 01 02 03 04 05 Reported 

Alameda County 7 28 96 23 9 0 163 

 4.3% 17.2% 58.9% 14.1% 5.5% 0.0% 100.0% 

Baltimore 6 72 304 0 0 2 384 

 1.6% 18.8% 79.2% 0.0% 0.0% 0.5% 100.0% 

Boston 1 9 17 38 3 0 68 

 1.5% 13.2% 25.0% 55.9% 4.4% 0.0% 100.0% 

California 0 2 19 23 59 0 103 

 0.0% 1.9% 18.4% 22.3% 57.3% 0.0% 100.0% 

Chicago 50 32 13 13 12 0 120 

 41.7% 26.7% 10.8% 10.8% 10.0% 0.0% 100.0% 

Cleveland 58 0 11 4 47 0 120 

 48.3% 0.0% 9.2% 3.3% 39.2% 0.0% 100.0% 

Massachusetts 0 12 66 48 7 0 133 

 0.0% 9.0% 49.6% 36.1% 5.3% 0.0% 100.0% 

Milwaukee 54 41 74 21 30 1 221 

 24.4% 18.6% 33.5% 9.5% 13.6% 0.5% 100.0% 

Minnesota 85 16 15 17 10 0 143 

 59.4% 11.2% 10.5% 11.9% 7.0% 0.0% 100.0% 

New Jersey 0 0 0 1 0 24 25 

 0.0% 0.0% 0.0% 4.0% 0.0% 96.0% 100.0% 

New York City 420 0 0 0 0 0 420 

 100.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Rhode Island 0 9 85 37 28 0 159 

 0.0% 5.7% 53.5% 23.3% 17.6% 0.0% 100.0% 

Vermont 98 12 208 42 31 0 391 

 25.1% 3.1% 53.2% 10.7% 7.9% 0.0% 100.0% 

Wisconsin 8 16 19 82 34 5 164 

 14.3% 9.5% 28.6% 33.3% 14.3% 0.0% 100.0% 

All Grantees: 787 249 927 349 270 32 2614 

 30.1% 9.5% 35.5% 13.4% 10.3% 1.2% 100.0% 

Note 1: One dwelling unit was excluded from this table due to miscoding. 

Note 2: Exterior Strategy Codes: 00=No Action, 01=Partial Paint Stabilization, 02=Complete Paint 

 Stabilization, Porch Treatments, 03=02 + Porch/Trim Enclosure and Stabilization, 04=All Lead Paint Enclosed or Removed, 05=All Lead Paint Removed. 

 See Table 5-1 for more complete strategy definitions. 

Data from: Form 23, Question 02 

Data as of: June 1, 2000 

Source of Data: UC Table 177-A
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Exterior Strategies by Building 

In 82 percent of the buildings in the analysis, the exterior was treated (Table 5-7). Grantees 

selected exterior strategies based on the general guidance provided by Table 5-1, yet as with 

interior strategy selection, certain treatments were conducted that went beyond the strategy 

definitions. While Exterior Strategy 01 was principally limited to paint stabilization, between 10 

and 20 percent of the buildings had some paint removed, components enclosed or components 

replaced. Exterior Strategy 02 had rates of component enclosure and replacement similar to those 

of Exterior Strategy 01, but the percentage of buildings with paint removal more than doubled 

(from 15 to 32 percent). 

Table 5-7: Use of Exterior Treatments by Exterior Strategy 

Exterior 

Strategy 

Number of 

Buildings 

% of 

Treated 

Buildings 

Treatment Description 

(by building) 

01 201 17% 84% had stabilization 

17% had replacement 

15% had paint removal 

12% had enclosure 

02 613 52% 96% had stabilization 

32% had paint removal 

19% had replacement 

12% had enclosure 

03 216 18% 72% had stabilization 

66% had enclosure 

35% had replacement 

29% had paint removal 

 6% had encapsulation 

04 140 12% 71% had enclosure 

59% had stabilization 

54% had replacement 

15% had encapsulation 

 7% had paint removal 

Total Treated 

Buildings 

1,177* 

*Includes 7 Buildings treated with Exterior Strategy 05 (Full Abatement) 

Data from: Form 23, Question 2 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table 
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For the buildings treated with Exterior Strategy 03, paint stabilization remained the leading 

treatment, as it was used at 72 percent of the buildings. However, the application of enclosure 

and replacement increased substantially from the lower level exterior strategies. For Exterior 

Strategy 04, the full abatement strategy, the leading exterior treatment was enclosure (71% of 

buildings) and a majority of the buildings (54%) had some component replacement. Another 15 

percent of these buildings included encapsulation and seven percent included paint removal. 

While Exterior Strategy 04 was intended to include only full abatement strategies, 59 percent of 

the buildings were treated with some paint stabilization. This may represent repainting after 

replacement, enclosure or paint removal; the repainting of surfaces with a paint lead level below 

1 mg/cm2

; or the misclassification of some dwelling units. 

5.2.1.3 Site Strategies

Site Strategies by Dwelling 

Only 13 percent of the dwellings in the Evaluation had site lead hazard control work conducted 

(Table 5-8). Site lead hazard control work included treatments to reduce a childís exposure to 

lead in soil, such as the installation of barriers/fencing or grass/ground cover and treatments that 

permanently abated the hazard, such as soil removal or capping of the ground with 

concrete/asphalt. Of the dwellings that had site treatments, 264 dwellings (77%) had limited, 

temporary treatments such as mulching (Site Strategy 01 and 02), while the remaining 79 

dwellings (23%) had partial or full abatement of the soil (Site Strategy 03 and 04). 

The distribution of site strategies across grantees was far from balanced (Table 5-8). Six of the 

14 grantees never treated the site: Baltimore, Boston, Massachusetts, Milwaukee, New Jersey 

and New York City. Four other grantees (California, Chicago, Vermont, and Wisconsin) treated 

the site at less than 8 percent of their dwellings. Of the remaining four grantees, only Alameda 

County, Cleveland and Rhode Island treated the soil at more than half of their dwellings. Five 

grantees, the three above plus Vermont, and Minnesota, treated 97 percent of the 348 dwellings 

with site treatments. Alameda County and Rhode Island alone contributed 61 percent of the 

dwellings with site treatments in the Evaluation. Of the 79 dwellings with full or partial 

abatement of soil (Site Strategy 03 and 04), 64 (81%) were treated by Alameda County or Rhode 

Island. Cleveland, along with Rhode Island and Alameda County, dominated the lower level site 

strategies; 77 percent of these strategies were completed by the three grantees. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

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Table 5-8: Number and Percentage of Dwelling Units at which a 

Specific Site Intervention Strategy was Undertaken

 Site Strategy 

Grantee Total Dwellings

 with Strategy 

 00 01 02 03 04 Reported 

Alameda County 68 32 13 23 27 163 

 41.7% 19.6% 8.0% 14.1% 16.6% 100.0% 

Baltimore 384 0 0 0 0 384 

 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Boston 68 0 0 0 0 68 

 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

California 97 6 0 0 0 103 

 94.2% 5.8% 0.0% 0.0% 0.0% 100.0% 

Chicago 119 1 0 0 0 120 

 99.2% 0.8% 0.0% 0.0% 0.0% 100.0% 

Cleveland 55 1 60 4 0 120 

 45.8% 0.8% 50.0% 3.3% 0.0% 100.0% 

Massachusetts 133 0 0 0 0 133 

 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Milwaukee 221 0 0 0 0 221 

 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Minnesota 111 21 8 1 2 143 

 83.5% 11.3% 2.6% 0.9% 1.7% 100.0% 

New Jersey 25 0 0 0 0 25 

 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

New York City 420 0 0 0 0 420 

 100.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Rhode Island 46 44 55 12 2 159 

 28.9% 27.7% 34.6% 7.5% 1.3% 100.0% 

Vermont 362 15 6 8 0 391 

 92.6% 3.8% 1.5% 2.0% 0.0% 100.0% 

Wisconsin 162 0 2 0 0 164 

 98.8% 0.0% 1.2% 0.0% 0.0% 100.0% 

All Grantees: 2271 120 144 48 31 2614 

 86.9% 4.6% 5.5% 1.8% 1.2% 100.0% 

Note 1: One dwelling unit was excluded from this table due to miscoding 

Note 2: Site Strategy Codes: 00=No Action, 01=Cover Soil, 02=01+ Seed and Install Barriers, 

03=02 + Partial Soil Removal and Plant Sod, 04=Complete Soil Removal or Enclosure with 

Concrete. 

See Table 5-1 for more complete strategy definitions. 

Data from: Form 23, Question 02 

Data as of: June 1, 2000 

Source of Data: UC Table 178-A
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5-17 

Site Strategies by Building 

A total of 154 of the 1,440 buildings (11%) in this analysis had site treatments conducted (Table 

5-9). Site Strategies 1 and 2 were similar; both were dominated by temporary ground cover 

(mulch, grass, or other plantings). Of the buildings treated with Site Strategies 1 or 2, 93 percent 

had temporary ground covers applied and less than nine percent had soil removed or permanently 

enclosed. The distinction between two lower level site strategies was largely determined by the 

amount of surface area treated, although a clear distinction between the two strategies did not 

exist. 

Site Strategies 3 and 4 were also similar strategies, with permanent enclosure of soil conducted at 

a majority of the buildings. Soil removal was conducted at 17 percent of the buildings classified 

as Site Strategy 3 or 4. While Site Strategy 4 had a higher percentage of buildings with 

permanent enclosure than Site Strategy 3, it was not apparent that Site Strategy 4 truly 

represented full abatement of soil, since ground cover was installed on at least a portion of the 

soil at 81 percent of the buildings. These higher level site strategies may better be defined as 

partial to substantial abatement of the soil. 

Table 5-9: Use of Site Treatments by Site Strategy by Building 

Site Strategy Number of 

Buildings 

% of 

Treated 

Buildings 

Treatment Description 

(by building) 

1 63 41% 89% had mulch/seed/sod/plant 

 8% had soil removal 

 6% had enclosure 

 3% had structure removal 

2 56 36% 98% had mulch/seed/sod/plant 

10% had enclosure 

 7% had soil removal 

 4% had structure removal 

3 21 14% 81% had mulch/seed/sod/plant 

52% had enclosure 

19% had soil removal 

10% had structure removal 

4 14 9% 93% had enclosure 

81% had mulch/seed/sod/plant 

14% had soil removal 

Total Treated 

Buildings 

154 

Data from: Form 23, Question 2 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table 
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5.2.2 Concurrent Work 

In addition to the observations about the lead hazard control strategies, the Evaluation made 

observations about the presence or absence of additional construction work at each of the 

dwellings and the extent of that work. As defined previously, this related construction work, 

conducted immediately before, during, or immediately after the lead hazard control work, is 

referred to as concurrent work. While considered ìnon-lead workî, the concurrent work may 

have influenced the effectiveness of the lead hazard control work in some dwelling units either 

directly (e.g., siding covering stabilized lead-based paint) or indirectly (e.g., storm windows that 

reduce the effect of climate on painted window components). 

Forty-five percent of the dwelling units had concurrent work conducted (Table 5-10). Every 

grantee had concurrent work done in at least some of their dwelling units. The frequency of 

concurrent work ranged from one percent in Chicago to 100 percent in New Jersey, with a 

median of 22 percent. Six grantees completed concurrent work in at least half of their dwelling 

units: Baltimore, California, New Jersey, New York City, Vermont, and Wisconsin. 

In the dwelling units where concurrent work was conducted, the value of concurrent work varied 

considerably: 46 percent of dwellings had concurrent work costs less than $5,000, 27 percent had 

concurrent work costs between $5,000 and $25,000, and 27 percent had concurrent work costs 

over $25,000. Baltimore and California contributed almost 70 percent of the dwelling units with 

concurrent work valued at less than or equal to $5,000, while Vermont and New York City 

contributed over 60 percent of the dwelling units with concurrent work valued between $5,000 

and $25,000. New York City and Vermont also were the largest contributors (90%) of the 

dwelling units with concurrent work valued over $25,000. These findings reflect the different 

types of concurrent work conducted. In general, Baltimore property owners conducted preintervention housing code work and/or post-intervention painting, while Californiaís program 

conducted weatherization activities in conjunction with the lead hazard control work. In Vermont 

and New York City, lead hazard control work was often performed in conjunction with moderate 

or substantial housing rehabilitation work completed by the local housing program. 

Concurrent work was associated with increasing levels of interior work (Table 5-11). Grantees 

that selected lower level interior strategies (Interior Strategies 02-03) rarely conducted 

concurrent work (8% of dwellings), while grantees that selected abatement strategies (Interior 

Strategies 06-07) almost always conducted concurrent work (94% of dwellings). Dwellings 

treated with Interior Strategies 04-05 were fairly evenly split between having concurrent work 

conducted (49% of dwellings) or not. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

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Table 5-10: Number and Percentage of Dwelling Units 

Having Undergone Concurrent Non-Lead Work 

by the Cost of the Concurrent Work

 Cost of Concurrent Work 

 Total 

Grantee Dwellings with 

 $1 to $1,000 to $5,000 to $15,000 to $25,000 Intervention 

 None < $1,000 < $5,000 < $15,000 < $25,000 or more Reported 

Alameda County 132 5 13 2 2 5 159 

 83.0% 3.1% 8.2% 1.3% 1.3% 3.1% 100.0% 

Baltimore 61 148 164 1 5 5 384 

 15.9% 38.5% 42.7% 0.3% 1.3% 1.3% 100.0% 

Boston 55 10 2 1 0 0 68 

 80.9% 14.7% 2.9% 1.5% 0.0% 0.0% 100.0% 

California 32 4 62 4 0 0 102 

 31.4% 3.9% 60.8% 3.9% 0.0% 0.0% 100.0% 

Chicago 118 0 1 0 0 0 119 

 99.2% 0.0% 0.8% 0.0% 0.0% 0.0% 100.0% 

Cleveland 100 10 7 0 0 3 120 

 83.3% 8.3% 5.8% 0.0% 0.0% 2.5% 100.0% 

Massachusetts 108 7 10 7 0 0 132 

 81.8% 5.3% 7.6% 5.3% 0.0% 0.0% 100.0% 

Milwaukee 165 10 16 13 11 5 220 

 75.0% 4.5% 7.3% 5.9% 5.0% 2.3% 100.0% 

Minnesota 133 0 3 3 0 3 142 

 93.7% 0.0% 2.1% 2.1% 0.0% 2.1% 100.0% 

New Jersey 0 0 0 0 25 0 25 

 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 100.0% 

New York City 169 0 0 42 40 169 420 

 40.2% 0.0% 0.0% 10.0% 9.5% 40.2% 100.0% 

Rhode Island 135 11 9 4 0 0 159 

 84.9% 6.9% 5.7% 2.5% 0.0% 0.0% 100.0% 

Vermont 150 0 2 33 86 120 391 

 38.4% 0.0% 0.5% 8.4% 22.0% 30.7% 100.0% 

Wisconsin 55 27 26 38 7 10 163 

 33.7% 16.6% 16.0% 23.3% 4.3% 6.1% 100.0% 

All Grantees: 1413 232 315 148 176 320 2604 

 54.3% 8.9% 12.1% 5.7% 6.8% 12.3% 100.0% 

Note: 11 Dwellings were excluded from this table because concurrent work was reported without an 

associated cost 

(7 dwellings) or no concurrent work was reported, but a concurrent work cost was reported 

(4 dwellings) 

Data from: Form 23, Question 6 & 7 

Data as of: June 1, 2000 

Source of Data: NCLSH Table
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5-20 

 

Table 5-11: Number and Percentage of Dwelling Units 

with Concurrent Work by Interior Strategy 

Interior 

Strategy 

Concurrent Work 

Completed 

Total 

Dwellings 

02 12 

5.6% 

216 

03 32 

9.6% 

332 

04 191 

45.6% 

419 

05 720 

50.4% 

1,428 

06 132 

93.0% 

142 

07 36 

100% 

36 

Total 1,123 

43.6% 

2,573 

Note 1: 11 Dwellings were excluded from this table because concurrent work was reported without an 

associated cost (7 dwellings), or no concurrent work was reported but a concurrent work cost was 

reported (4 dwellings). 

Note 2: 31 Dwellings were excluded from this table because no interior work was conducted. 

Note 3: Interior Strategy Codes: 01=No Action 

 02=Cleaning/Spot Painting 

 03=Full Painting 

 04=Window Treatments 

 05=Window Abatement 

 06=Full Abatement 

 07=Lead Free 

 See Table 5-1 for detailed strategy definitions 

Data from: Form 23, Question 9 

Data as of: June 1, 2000 

Source of Data: NCLSH Table 

5.2.3 Summary of Strategy Selection and Interventions 

The descriptions of interventions presented in this chapter offer a picture of the treatments 

undertaken. Grantees tended to select interior strategies that were below full abatement but 

included significant window treatments, ranging from jamb liner installation or sash replacement 

to off-site stripping of window components or full window replacement. While some grantees 

such as Boston and Massachusetts had their strategies largely dictated by state law, most 

grantees had the freedom to choose from the full range of lead hazard control options. Most 

grantees decided that treatments beyond paint stabilization but less than full abatement met their 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-21 

needs, after taking into account factors such as local housing conditions, presence of a leadpoisoned child, and financial constraints. 

Grantees generally chose to treat building exteriors using a range of strategies. When exterior 

treatments were not selected, a principal reason was the lack of exterior lead-based paint hazards. 

Over half of the dwellings that had no exterior treatments were in New York City, where the 

buildings were masonry with little or no exterior paint. Because of cost, some grantees 

deliberately selected buildings without exterior lead hazards. At most properties, grantees chose 

not to treat the site. Decisions were often based on programmatic decisions not to include soil as 

part of the granteeís lead hazard control plans and were not made based on the existence or 

absence of lead-contaminated soil, since most grantees chose not to test the soil. Just three 

grantees, Alameda County, Cleveland, and Rhode Island chose to treat soil at a majority of their 

properties. 

Lead hazard control activities were often accompanied by concurrent work. The types of work 

varied by grantee, with some grantees such as Baltimore requiring additional work from property 

owners, while other programs incorporated the lead hazard control work with other activities 

such as weatherization or substantial housing rehabilitation. The use of concurrent work tended 

to correspond with higher intensities of interior treatments. 

The descriptions in this chapter also offer an understanding of the analytic opportunities and 

limitations produced by the selection of treatments in this Evaluation. Never before have studies 

of lead hazard control had the opportunity to analyze the effectiveness of such a diversity of 

treatments. In addition, the diversity of pre-intervention building conditions, the variety of 

housing types and locales, and differences in grantee programs (see Section 2.2) offer 

opportunities for considering the effects of treatments under many different conditions. 

Yet at the same time, this Evaluationís central feature, the freedom provided to grantees when 

they selected their lead hazard control strategies, created some limitations for the analyses of 

treatment effectiveness. The Evaluation team did not have the authority to direct grantees to use 

certain strategies, so in some cases the quantity of dwellings treated with certain strategies was 

limited. For example, an examination of the post-intervention effects of creating dwellings free 

of lead-based paint was not possible because of the small number of dwellings treated with this 

strategy that had complete post-intervention data available. 

The flexibility afforded the grantees meant that strategies were not randomly or evenly 

distributed across the enrolled dwellings. As will be explained in more detail in Sections 8.0 and 

9.0, the clustering of intervention strategies among a few grantees and a limited variety of 

housing types and housing conditions posed challenges in data analysis and in the interpretation 

of findings. One challenge posed by the clustering of strategies was that while the Evaluation 

was national in scope, some findings are based on the work of just a few grantee sites and may 

be less generalizable. For example, the results from Alameda County and Rhode Island will have 

a large influence on the conclusions that can be drawn about the effectiveness of site work 

because they contributed 60 percent of the site treatment data. The non-random application of 

strategies also created a situation where strategies were often correlated with other factors such 

as baseline building condition (i.e., buildings in worse condition received higher level strategies). 

This intercorrelation of strategy with other factors presented a challenge to the Evaluation teamís 

ability to determine which factors were influencing treatment effectiveness and the magnitude of 

the effects. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

5-22 

While the Evaluation team did their best to organize the lead hazard control activities into a 

limited number of strategies and treatment categories, the findings demonstrate quite clearly that 

the specific interventions within a strategy do vary from grantee-to-grantee. A limitation of this 

study is that the ìshort-handî definitions of strategy that are used throughout this report may not 

fully reflect the diversity of treatments within each strategy. Furthermore, the outcomes 

associated with any particular strategy offer important information about the strategy in general, 

but cannot provide conclusive data about any specific treatment approach taken by just one or 

two grantees. For example, the outcomes related to Interior Strategy 04 should not be used to 

draw conclusions about the utility of jamb liners since they were used in just a portion of the 

dwellings treated with this strategy. 

5.3 DESCRIPTION OF INDIVIDUAL LEAD HAZARD CONTROL TREATMENTS

Of the 2,920 dwelling units treated in the study, 2,615 dwellings in 1,440 buildings had 

acceptable specifications submitted and had evidence of passing clearance. A total of 23,580 

rooms were identified within these dwellings. 

5.3.1 Interior Treatments 

The most common treatments that were reported (other than cleaning3) were window 

replacement and paint stabilization of trim, doors and walls/ceilings (Table 5-12). Each of these 

treatments was reported in at least 22 percent of the rooms. Window replacement was the most 

popular treatment having been conducted in 40 percent of the rooms. In 15 percent of the rooms, 

some form of friction/impact/moisture control was applied to the windows; nine percent of the 

rooms had both replacement and friction controls. Enclosure was the preferred treatment on 

floors and stairways (10% of rooms). 

When developing the equivalent treatment categories, the term stabilization of paint was used to 

identify all reported uses of a paint or sealant. As presented on Table 5-1, paint stabilization is 

generally defined as ìthe process of repainting surfaces coated with lead-based paint, which 

includes the proper removal of deteriorated paint and priming.î However, the evaluation team 

found that grantees used specifications for pure paint stabilization and other repainting 

interchangeably. In some cases, paint was applied to intact painted surfaces and sealant was 

applied to non-leaded surfaces. Because it was observed that the specifications were more 

commonly used for the purpose of treating deteriorated paint, the decision was made to consider 

all painting and sealing as ìpaint stabilization.î 

 

3

 Cleaning was assumed to be completed in all treated rooms 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

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Table 5-12: Interior Component System Treatments (By Room) 

 Number and Percentage of Rooms with a Specific Class of Treatment 

Component 

Systems 

Total 

Rooms 

Misc. 

Treatments 

Paint 

Stabilization 

Encapsulation Paint 

Removal 

Window 

Rework 

Enclosure Component 

Replacement/ 

Removal 

Wall/Ceiling 23,580 13 

<1% 

5,065 

22% 

246 

1% 

46 

<1% 

2,252 

10% 

105 

<1% 

Floor/Stairs 23,580 53 

<1% 

954 

4% 

3 

<1% 

607 

3% 

2,301 

10% 

92 

<1% 

Doors 23,580 63 

<1% 

5,600 

24% 

34 

<1% 

400 

2% 

2,389 

10% 

Trim 23,580 25 

<1% 

7,826 

33% 

301 

1% 

2,629 

11% 

190 

1% 

3,479 

15% 

Windows 23,580 33 

<1% 

2,137 

9% 

16 

<1% 

724 

3% 

3,444 

15% 

9,511 

40% 

Data from: Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C6 

Beyond the commonly used treatments, grantees selected a broad variety of treatments to meet 

their needs. Even when treatments were selected less frequently on a percentage basis, there are 

still enough instances to allow further investigation of effectiveness. For example, paint was 

stabilized on windows in 9 percent of the rooms, encompassing 2,137 rooms, sufficient to 

analyze the effect of this treatment. 

Encapsulation was infrequently used in the Evaluation. Encapsulation was used on 301 of the 

trim systems (1%), 246 of the wall/ceiling systems (1%), and less than 20 of the floor/stair and 

window systems. Grantees were more than 20 times more likely to use paint than encapsulants 

on wall/ceilings and more than 25 times more likely to use paint on trim. 

Table 5-13 presents the 25 most commonly used interior equivalent treatment categories used for 

effectiveness analyses. The table includes eight individual window treatments 

and four individual treatments in each of following treatment categories: wall/ceilings, 

floor/stairs, doors and trim. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 

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Table 5-13: Top 25 Most Frequently Used 

Individual Interior Lead Hazard Control Treatments 

Rank Treatment Number 

of Times 

Used* 

1 Trim ñ Stabilize Paint 10,025 

2 Window ñ Replace 9,002 

3 Wall/Ceiling ñ Stabilize Paint 7,949 

4 Door ñ Stabilize Paint 6,198 

5 Trim ñ Replace/Remove 4,619 

6 Trim ñ Remove Paint 3,798 

7 Wall/Ceiling ñ Enclose 3,149 

8 Window ñ Wrap Sill/Trough 2,721 

9 Door ñ Replace 2,543 

10 Floor/Stair ñ Enclose (wood/vinyl) 2,382 

11 Window ñ Stabilize Paint 2,323 

12 Floor/Stair ñ Stabilize Paint 1,245 

13 Window ñ Remove Component 1,171 

14 Window ñ Replace Sash Only 883 

15 Window ñ Install Jamb Liner 814 

16 Window ñ Remove Paint 788 

17 Window ñ Repair 673 

18 Floor/Stair ñ Refinish 612 

19 Door ñ Remove Paint 496 

20 Door ñ Remove Component 475 

21 Trim ñ Encapsulate 358 

22 Wall/Ceiling ñ Patch 307 

23 Wall/Ceiling ñ Encapsulate 262 

24 Floor/Stair ñ Dispose of Carpet 219 

25 Floor/Stair ñ Enclose (carpet) 213 

 *Number of Times Used is based on the number of instances when a specification was reported. 

Specifications were generally reported once per room but an individual treatment could be used more than 

once in a room. For example, if two separate window specifications were used to report sash paint 

stabilization and sill paint stabilization in a room, two Window-Stabilize treatments would be counted for 

that room. However, if a single specification were used to report the replacement of 3 windows in a room, 

then a single Window-Replace treatment would be counted for that room. A total of 23,580 rooms were 

considered for this analysis. 

Data from: Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C2 
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5-25 

5.3.2 Exterior/Site Treatments 

Paint stabilization was by far the most common treatment on building exteriors, used on the 

cladding and trim of 69 percent of the 1,440 buildings (Table 5-14a). Other frequently used 

treatments on building exteriors were: component enclosure (24%), paint removal (21 %), and 

component replacement/disposal (20 %). 

On exterior stairways and porch decking, the most common treatment was replacement/disposal, 

which was conducted at 137 buildings (10%). Enclosure and paint stabilization were used on 

stairs and decks at five percent of the buildings. 

The most common soil treatment was the installation of a soil covering, including mulch, seed or 

sod (Table 5-14b). Soil covering was installed at 147 buildings (10%). A small subset of 

buildings had more intensive soil remediation conducted: two buildings with both permanent 

enclosure and soil removal, 32 buildings with partial or full permanent enclosure only, and 13 

buildings with partial or full soil removal only. The relatively small number of buildings with 

higher intensity soil treatments precludes comparison of soil treatments. At 18 buildings (1%), an 

outbuilding was removed. 

Table 5-15 presents the 11 most commonly used exterior/site equivalent treatment categories 

used for effectiveness analyses. The table includes six individual treatments to exterior cladding 

or trim, three individual treatments to exterior stairs or decking, and two individual treatments to 

soil. 

Table 5-14a: Exterior Component System Treatments (By Building) 

 Number and Percentage of Buildings with a Specific Class of Treatment 

Component 

Systems 

Total 

Buildings 

Misc. 

Treatments 

Paint 

Stabilization 

Encapsulation Paint 

Removal 

Rework 

/Replacement 

Enclosure 

Exterior 

Cladding/Trim 

1,440 36

3%

997

69%

40

3%

298

21%

305 

21% 

341

24%

Stairs/Decking 1,440 6

<1%

71

5%

0

0%

8

1%

137 

10% 

77

5%

Table 5-14b: Site Treatments (By Building) 

 Number and Percentage of Buildings with a Specific Class of Treatment 

Component 

Systems 

Total 

Buildings 

Misc. 

Treatments 

Remove 

Structure 

Mulch/Seed 

/Sod/Plant 

Remove 

Soil 

Permanent 

Enclosure 

Site 1,440 13 

1%

18

1%

147

10%

15 

1% 

34 

2%

Data from: Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C6 
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Table 5-15: Top Most Frequently Used Individual Exterior 

Lead Hazard Control Treatments 

Rank Treatment Number of Times Used* 

1 Exterior - Stabilize Paint 2,082 

2 Exterior - Remove Paint 707 

3 Exterior - Enclose 654 

4 Exterior - Replace 497 

5 Exterior Stair/Decking - Replace 133 

6 Exterior Stair/Decking - Stabilize 102 

7 Soil - Seed 86 

8 (tie) Exterior - Encapsulate 85 

8 (tie) Exterior Stair/Decking - Enclose 85 

10 (tie) Exterior - Dispose Component 59 

10 (tie) Soil - Mulch 59 

*Number of Times Used is based on the number of instances when a specification was reported. 

Specifications were generally reported once per location (building) but an individual treatment 

could be used more than once at a building. For example, if two separate exterior specifications 

were used to report siding paint stabilization and fascia paint stabilization at a building, two 

Exterior-Stabilize treatments would be counted for that building. However, if a single 

specification were used to report the stabilization of 2 porches at a building, then a single 

Exterior-Stabilize treatment would be counted for that building. A total of 1,440 buildings were 

considered for this analysis. 

Data from: Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C3 

5.3.3 Summary of Individual Treatments 

As with intervention strategies, grantees selected a wide variety of individual lead hazard control 

treatments. The variety of treatments provided the Evaluation team with an opportunity to 

explore the effects of the different treatments. Many types of building components were treated 

with a sufficient variety of treatment categories (e.g., stabilization, paint removal, replacement) 

so that comparisons of effectiveness could be undertaken. Among the analyses presented later in 

this report are comparisons of the cost of individual treatments (Section 6.0), the longevity of the 

treatments (Section 8.6) and the effectiveness of window treatments and paint removal 

treatments as measured by longitudinal dust lead levels (Section 8.7). Additional comparisons 

between floor, trim and door treatments were originally part of the analysis plan, but as 

explained in Section 8.7, the Evaluation team was unable to confidently separate the effects on 

dust lead levels of the treatments to these components. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-1

6.0 COSTS OF LEAD HAZARD CONTROL ACTIVITIES 

6.1 BACKGROUND

When the Evaluation was being designed, there were very few sources of empirically based 

estimates of lead hazard control costs. For example, lead abatement cost estimates developed 

during the HUD Lead-Based Paint Abatement Demonstration in 1991 (HUD 1991) were based 

on applying costs of labor, materials and overhead/profit provided by contractors to the studyís 

findings of time and material requirements for certain treatments. Other reports of lead hazard 

control costs were often anecdotal, based on unscientific surveys of contractors and property 

owners in limited geographic areas. In 1999, HUD relied on cost estimates based on interviews 

with contractors and state officials, as well as data from this Evaluation, to identify lead hazard 

reduction costs for its Economic Analysis of the Final Rule on Lead-Based Paint (HUD 1999). 

Given the number of requests for information about costs that the Evaluation team has received, 

the limited availability of lead hazard control cost data cannot be for a lack of demand. The 

paucity of empirical cost data is more likely due to the many issues involved in reporting costs. 

The costs of lead hazard control may vary greatly depending on factors such as the size of the 

dwelling, the extent of the hazards, the number of dwellings in the project, the scope of the 

treatments and regional cost differences. A more basic question which must be addressed is what 

lead hazard control activities (e.g., lead hazard evaluation, hazard reduction, relocation, 

clearance, general oversight) should be included when reporting costs. When reporting 

construction costs, the costs that will be attributable to lead hazard control must be defined. For 

example, for some constituents, such as property owners, the most informative value is likely to 

be the amount that a lead abatement contractor will charge. For other constituents, such as state 

legislatures, a more useful value may be the incremental costs of treating lead hazards, 

subtracting the costs of routine maintenance and painting and standard rehabilitation activities. 

6.1.1 Evaluation Costs 

One of the principal objectives of the Evaluation was to describe the costs of applying the 

various intervention strategies to dwelling units that received interventions under a HUD LHC 

Grant. The Evaluation offered an opportunity to report empirically based lead hazard control 

costs because of the detailed information about housing conditions, treatments, and costs that 

were collected. However, the researchers faced challenges in determining how best to report the 

costs. Decisions about what to report were sometimes based on data collection limitations and in 

other cases based on analytical decisions. This section discusses the process used to collect cost 

data in the Evaluation while the methodology portions of Sections 6.2 and 6.4 describe analytical 

decisions made when considering the costs. An understanding of how costs were determined is 

critical to interpreting the results, especially when comparing costs to those reported by other 

programs. 

6.1.2 Methodology 

A central concern of HUD when designing the Evaluation was ìto evaluate the cost and efficacy 

of lead-based paint hazard control efforts conducted under the HUD programî (NCLSH 1994). 

Given this focus, data collection forms were designed to report information about the costs of 

lead hazard reduction. The costs of other lead hazard control activities including the costs of 

environmental testing, medical surveillance of children, family relocation or program oversight 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-2

were not collected as part of the Evaluation. This study was not designed to measure the per-unit 

costs of managing a Lead-Based Paint Hazard Control Grant or any similar governmental 

program. The costs presented are strictly related to the costs that an organization or individual 

could expect to pay for lead hazard control, including worksite preparation, lead treatments, 

clean-up, and hazard disposal, as well as profit and overhead (if applicable). 

For each dwelling unit, grantees reported the cost of lead hazard control work, the total cost of 

the intervention (lead hazard control work plus concurrent work) and the cost for each treatment 

specification for the dwelling. Grantees usually obtained these costs from the contractor invoices. 

For single-unit homes, the costs included the cost of interior, exterior and site work. For multiunit buildings, costs were reported on a form for each separate dwelling unit that was treated and 

a separate form was prepared for the common areas. The dwelling unit forms for multi-unit 

buildings included only the costs for treating the interior of the dwellings, while the common 

area forms included costs for interior common areas, exteriors and site work. (It should be noted 

that the costs of interior treatments to common areas in multi-unit buildings have not been 

examined. In general, common hallway treatments, costs and their effects are not part of this 

report.) 

During the first months of the data collection process, questions arose about when costs should 

be allocated to lead hazard control work versus concurrent work. Among the allocation systems 

that the Evaluation team considered: 

1) Allocate costs by source of funding (e.g., work paid for by the HUD LHC Grant Program 

= lead work); 

2) Allocate costs by surface treated (e.g., work conducted on a leaded surface = lead work); 

3) Allocate costs by intent (e.g., treatments conducted to control lead hazards = lead work); 

4) Allocate costs by incremental lead costs (e.g., special worksite preparation, worker 

protection, and clean-up = lead work, while regular painting activities = non-lead work). 

After discussing the issue with Grantees at a meeting in February 1995, oral guidance was 

provided to all grantees that cost allocation should be conducted based on intent. All work that 

could have been legitimately paid for by the HUD LHC Grant was eligible to be considered lead 

work. All work conducted on lead-based paint hazards as well as to lead-based paint was eligible 

to be lead work. Work conducted in order for other lead treatments to be effective (roof repair, 

plumbing leak repair, minor structural repairs) was also considered lead work. In general, 

grantees were encouraged to report treatments as lead work when those treatments were eligible 

costs under the grant program. 

The purpose of this allocation system was to identify the full cost per unit for lead-based paint 

hazard reduction activities that a property owner might expect to pay while discounting any extra 

work that may have been conducted. This extra work included major structural work conducted 

as part of substantial rehabilitation projects, HVAC or electrical work that would not be eligible 

for lead grant funding. The extra work also included treatments that could arguably have 

improved the effectiveness of the lead work, but in the opinion of the spec writer, were 

conducted for other reasons such as energy efficiency. These treatments included storm window 

and siding installation and cosmetic painting. While the use of intent to allocate costs resulted in 

some variation in cost reporting from grantee to grantee and from spec writer to spec writer, the 

system appeared to reasonably reflect the full cost per unit of lead-based paint hazard control. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-3

One obvious limitation of this approach was that it was not possible to empirically estimate the 

incremental costs of lead hazard control. Grantees were not required to report the cost of 

treatments they would have incurred had lead abatement contractors and lead-safe work practices 

not been used. Any estimate of the incremental costs based solely on these data would be 

speculative. 

The dollar amounts reported by the grantee were expected to be the actual dollar amounts paid 

by the program for the treatments. As such, the costs included the labor and materials for the 

project as well as any overhead and profits that were charged. Eighty-eight percent of the 

dwelling units were treated by for-profit contractors and generally all of these factors were 

included in their reported costs. (In a few cases, grantees paid for some contractor expenses such 

as worker training and liability insurance.) In a limited number of dwellings, grantees hired nonprofit contractors (5%), property owners (5%), or used their own staff (2%) to complete the 

treatments. In these cases, the reported costs did not include a profit factor and in the case of the 

public employees may not fully account for the overhead expenses. The possible impact of this 

variation will be discussed with the results. 

To report the costs of individual lead hazard control treatments, grantees estimated those costs 

using their personal knowledge of construction pricing and in some cases values reported by the 

contractor. Grantees were required to develop estimates for specifications that when totaled 

would be within 20 percent (or $200, if that was larger) of the total lead hazard control costs for 

the dwelling as reported on Form 23. Dwellings where this level of precision of estimation could 

not be achieved were excluded from the analysis of individual lead hazard control treatment 

costs. Fifteen percent of treated dwellings and 26 percent of treated common areas from all 

grantees except New York City were excluded because reported costs did not meet these criteria. 

6.2 DWELLING UNIT LEVEL COST ESTIMATES

The cost of lead hazard control varied substantially from dwelling to dwelling. The variation was 

influenced by many factors including the scope of the treatments and the size of the dwelling. 

Although sufficient study data are available to generate a single ìnationalî average cost for lead 

hazard control in the Evaluation, such a result would have little practical value to anyone 

planning to fund or conduct lead hazard control work. Agencies would most likely find it more 

useful to have average costs presented for the type and size of dwelling that they plan to treat and 

for the intensity of the treatments they plan to implement. 

6.2.1 Methodology 

A central data analysis issue was how to organize and subdivide the cost data to have practical 

benefit. After consideration of a number of different organizational methods, it was determined 

that costs would be subdivided by the ìgeographyî (interior, exterior, site) of the property treated 

as well as by strategy. This report presents the dwelling unit costs of interior treatments, exterior 

treatments and site/soil treatments by the intensity of the interventions. 

A cost separation procedure to categorize the specifications into the three ìgeographiesî of the 

property was applied to eligible dwellings. In order to be considered for the cost separation 

procedure, the dwelling had to have: 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-4

1. construction forms available with data representing both interior and exterior/site 

treatments. For multi-unit buildings, these include data for the dwelling unit and the 

common areas; 

2. all data on strategies accepted by the Evaluation team (based on a visual comparison 

of the strategies and the specifications conducted); and 

3. total costs for the specifications meet the criteria of being within 20% or $200 

(whichever is larger) of the total lead hazard control costs reported on Form 23 

(Appendix A). 

In brief1

, the cost separation procedure used the sketch and paint inspection report information to 

identify interior and exterior locations at each dwelling. Specifications in interior locations were 

considered interior treatments. Specifications in exterior locations were separated into site 

treatments and exterior building treatments, using the specification descriptions. 

Specifications that did not apply to an individual treatment, but defined general requirements for 

the whole intervention were classified as general requirements. Because some grantees reported 

separate costs for the general requirements and others had already included these costs for each 

specification, a determination was made that general requirement costs needed to be incorporated 

into the cost of treatments at all dwellings to make the costs comparable. General requirement 

costs, when assigned an individual cost value, were proportionately distributed across the three 

ìgeographiesî. 

For example, in a building where $5,000 was spent on interior treatments, $2,000 was spent on 

exterior treatments, $1,000 was spent on site treatments, and $2,000 was spent on general 

requirement costs, the general requirement costs would be allocated across the three 

ìgeographiesî of the property. With $8,000 in treatment costs, 62.5% (5000/8000) of the $2000 

general requirements costs would be allocated to interior treatments, 25% (2000/8000) to 

exterior treatments, and 12.5% (1000/8000) to soil/site treatments. For this building, the 

allocated costs would be calculated as $6,250 for interiors, $2,500 for exteriors, and $1,250 for 

site. 

While specification costs from SpecMasterÆ were used to allocate costs to the three 

ìgeographiesî at each property, the Evaluation team determined from field observations and 

discussions with spec writers that the total specification costs were not the most accurate value 

for total lead hazard control costs. The lead hazard control costs reported on Form 23 were 

judged to be a more accurate accounting of the lead hazard reduction costs because they were 

generally based on contractor invoices. Therefore, when the total of the specification costs was 

not the same as the total lead hazard control cost reported on Form 23, the total allocated costs 

were adjusted to equal the Form 23 lead hazard control costs. In the example above where the 

total specification costs for the building were $10,000, if the Form 23 lead hazard control costs 

were reported as $11,000, then each of the allocated costs would be adjusted upward by 10 

percent. The adjusted values were the final costs used in this report. 

The lead hazard control costs for each ìgeographyî of the property are presented by the strategy 

level (intensity of treatment) applied to that ìgeographyî. For example, for interior treatment 

costs, the costs are presented for each interior strategy ranging from Interior Strategy 02

 

1

 A full description of the procedure is available with the data documentation for this study. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-5

(cleaning and spot painting) to Interior Strategy 07 (full removal of all lead-based paint). The 

strategies are described in more detail in Section 5.2.1. 

A variety of descriptive statistics are presented here. Both the arithmetic mean and the median 

cost of lead hazard interventions are reported by ìgeographyî. Because the lead hazard control 

cost data had a skewed distribution, the median cost is a better measure of the cost to treat an 

individual ìaverageî dwelling. On the other hand, the arithmetic mean value provides a better 

measure of the average costs a program might encounter if it were treating numerous dwellings. 

To illustrate the wide variation in costs reported, the 5th and 95th percentiles of costs by 

ìgeographyî are described in the text. When comparisons between strategies are made, the more 

commonly used measure of statistical variability is presented, the interquartile range (i.e., 25th

and 75th percentiles). The costs were not adjusted for any factors including regional cost 

differences or inflation. 

6.2.2 Interior Treatment Costs 

A total of 2,332 dwelling units that met the three cost separation criteria had interior 

interventions conducted. The mean cost of interior work was $6,140 while the median cost was 

$5,960 (Table 6-1). The 5th and the 95th percentile costs were $410 and $11,690, respectively. 

The broad range of interior lead hazard control costs can be largely explained by the wide variety 

of the treatment intensities represented by these costs. As expected, treatment costs tended to 

increase with the increase in treatment intensity. The median cost for interior work when 

cleaning and possibly some spot painting were conducted (Interior Strategy 02) was $430. As the 

level of intensity of the interior strategies increased, from full paint stabilization (Interior 

Strategy 03) through partial (04) and full window abatement (05) to full abatement (06), the 

median costs were $4,930, $6,120, $6,800, and $9,570, respectively. 

Only Interior Strategy 07, full removal of lead-based paint, deviated from the trend of increasing 

cost with increasing treatment intensity. The median cost for the full removal of lead-based paint 

was $4,110. While this finding is counterintuitive, the results make sense when considered in the 

context of a lead hazard control program where grantees had control over the intensity of 

treatments that they applied. Grantees rarely set out to fully remove all lead-based paint from a 

dwelling, but when opportunities arose to achieve full removal that were not cost prohibitive, this 

strategy was selected. Often, there was only a limited amount of lead-based paint present in the 

dwelling so full removal was more moderately priced. 

Although subdividing the interior costs by strategies reduced the variation, a fairly wide 

distribution of costs still exists within each strategy. The interquartile ranges overlapped for most 

of the most of the strategies (Figure 6-1). The coefficient of variation2

 was 44 percent or higher 

for all interior strategies except Strategy 06 (Table 6-1). For interior costs, the cost factors that 

might explain this variation were examined through statistical analysis. The methods of this 

analysis and discussion of the findings are presented in Section 6.3. 

 

2

 The coefficient of variation (CV) is a measure of dispersion, which is calculated by dividing the standard deviation 

of a sample by its arithmetic mean. A higher CV indicates the results are more variable. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-6

Table 6-1: Intervention Costs by ìGeographyî and Strategy 

Strategy Lead Hazard Control Costs by ìGeographyî 1 Number of 

Dwelling Units 

Or Buildings 

Mean Coeff. 

Of 

Variation

5th

%tile 

Median 95th %tile

Interior 02 238 Dwellings $730 108% $60 $430 $2,200

03 328 Dwellings $4,730 44% $1,170 $4,930 $7,960

 04 368 Dwellings $6,370 52% $1,880 $6,120 $11,740

 05 1,219 Dwellings $7,150 46% $2,740 $6,800 $12,680

 06 145 Dwellings $9,510 16% $8,290 $9,570 $9,950

 07 34 Dwellings $4,410 83% $880 $4,110 $10,570

 02-07 2,332 Dwellings $6,140 59% $410 $5,960 $11,690

Exterior 01 167 Buildings $1,280 156% $70 $600 $4,090

02 554 Buildings $3,040 123% $330 $1,390 $11,010

 03 168 Buildings $5,560 88% $690 $4,260 $15,210

 04 121 Buildings $9,400 50% $3,020 $9,130 $17,320

 05 6 Buildings $3,100 114% $70 $1,860 $9,190

 01-05 1,016 Buildings $3,930 115% $250 $1,870 $13,080

Site 1 65 Buildings $910 108% $110 $560 $2,940

2 56 Buildings $1,810 209% $120 $970 $3,860

3 21 Buildings $4,250 75% $1,100 $2,700 $10,820

 4 15 Buildings $6,620 83% $1,200 $5,300 $19,020

 1-4 157 Buildings $2,220 160% $140 $1,080 $8,700

1

See Table 5-1 for Strategy Definitions 

Data from: Form 23 & SpecMaster 

Data as of: June 1, 2000 

Source of Data: UC Tables 401-I, 401-E, 401-S 
Figure 6-1: Median and Interquartile Interior Lead Hazard Control Costs by Interior Strategy

170

3410

3980

4850

8860

910

4930

6120

6800

9570

4110

1070

6040

8570

9170

9880

5890

430

$0

$8,000$6,000$4,000$2,000

$12,000$10,000

02 03 04 05 06 07

Interior Strategy

Costs

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

6-7
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-8

The lack of variability within Interior Strategy 06 is largely due to the unique cost reporting 

system that was used for many of the dwellings that underwent this strategy. New York City 

conducted about 90 percent of the Interior Strategy 06 interventions. When New York City 

conducted these treatments, they were always done in conjunction with complete rehabilitation 

of the building that was paid for with other funding sources. The treatments were fairly 

homogeneous since the size and the scope of the work at each dwelling was quite similar. New 

York City set a cap of $10,000 to be spent on the removal and disposal of leaded components in 

the dwelling. The cost of replacing those leaded components as well as the cost of all other 

rehabilitation work was classified as concurrent work. Not surprisingly, contractors quickly 

learned of the $10,000 cap and prices for the lead removal were generally close to the cap. Lead 

hazard control costs for dwellings treated with full abatement in New York City were never 

above $10,000 and were rarely far below that value. 

Costs for Interior Strategy 02 (cleaning/spot paint) were at the other extreme for variability; the 

coefficient of variation was 108 percent. The variation can be explained in part because the 

treatments and intervention designs were not homogeneous and were markedly different across 

grantees. Four grantees, Milwaukee, Vermont, Alameda County and Minnesota, conducted 

almost 90 percent of the Interior Strategy 02 interventions, with differing scopes of work, work 

requirements, and delivery mechanisms: 

• Milwaukee. Milwaukee conducted approximately one-quarter of the lowest intensity 

interior strategies. Milwaukeeís scope of treatments included cleaning only or cleaning 

supplemented by aluminum window wraps/caps on sills and troughs. City employees 

conducted these low level treatments. No special labor, insurance or warranty 

requirements were placed on these jobs, and Milwaukee did not consider the waste water 

generated from cleaning hazardous. Since the work was conducted by city employees, no 

profits or overhead were included in the costs reported. Costs were generally less than 

$100 per unit. 

• Vermont. Vermont conducted approximately one-quarter of the Interior Strategy 02s. 

Vermontís scope of work was generally dictated by the stateís Essential Maintenance 

Practices (EMP), which required spot paint stabilization, window trough caps, and 

cleaning (Vermont Act 165, 1996). Property owners conducted the work in their 

properties. Owners were required to carry their own insurance but were exempt from any 

hazardous waste requirements under the household exemption. Property owners were 

paid for their expenses but not a profit. Costs generally ranged from $400-500 per unit. 

• Alameda County. Alameda County conducted approximately one-quarter of the Interior 

Strategy 02s. Alameda Countyís scope of work was the least standardized and at times 

the most intensive of the four major contributors. The treatments ranged from clean-only 

to spot paint stabilization with replacement of a few small leaded components. Work was 

conducted by private for-profit lead abatement contractors. The contractors were required 

to hold lead-specific insurance, warrant their work, and follow hazardous waste disposal 

regulations. Reported costs included the overhead and profit that the contractor charged 

the grantee. Costs generally ranged from $700-800 per unit. 

• Minnesota. Minnesota conducted about 10 percent of the Interior Strategy 02s. The scope 

of work was solely clean-only. The work was completed by a private for-profit lead 

abatement contractor and was conducted at the Minneapolis subsite. The contractor, who 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-9

did other lead hazard control work under this grant, was required to hold lead-specific 

insurance, post a performance bond, and pay Davis-Bacon wages. In addition, the State 

of Minnesota strictly interpreted hazardous waste regulations and expected that waste 

water and other materials generated would be treated accordingly. The prices for specific 

treatments were pre-negotiated as part of the bidding process, with cleaning costs 

established at $200 per room. Reported costs included the overhead and profit that the 

contractor charged the grantee. Costs generally ranged from $1,500-1,700 per unit. 

The examples of these four grantees demonstrate that even when treatments are collapsed into a 

seemingly similar treatment group, there can be great variability in the design of a intervention 

that will influence the costs. The many unique features of the grantee programs posed challenges 

for generalizing the costs. Some of the factors that influence costs will be addressed in Section 

6.3, but it was often difficult to separate factors that produced higher or lower costs. However, 

between the average costs presented above and these examples, one can get a sense of the 

programmatic costs for conducting lead hazard control to dwelling interiors. 

6.2.3 Exterior Costs 

Exterior interventions were performed on 1,016 buildings that met the three cost separation 

criteria. Another 262 buildings had no exterior treatments. The mean cost for exterior work on 

treated buildings was $3,930 while the median cost was $1,870 (Table 6-1). The 5th and the 95th

percentile costs were $250 and $13,080, respectively. 

Like interior costs, the exterior costs encompassed a broad range of treatments from minor paint 

stabilization to complete lead-based paint removal. As the levels of the Exterior Strategies 

increased, from partial paint stabilization (Exterior Strategy 01) through full paint stabilization 

(02) to partial abatement (03) and then full abatement (04), the median costs increased: $600, 

$1,390, $4,260, and $9,130, respectively. 

The increasing trend of costs with increasing treatment intensity was broken when full removal 

of lead-based paint (Exterior Strategy 05) was conducted. The median costs were just $1,860 for 

this treatment. As with interior costs, this result is logical, since grantees chose this highest level 

of treatment only when the quantity of leaded surfaces to be removed was considered 

manageable and not cost prohibitive. In fact, only six buildings from three grantees underwent 

this level of treatment and met the cost analysis criteria. 

Similar to interior strategies, the costs of exterior lead hazard control displayed a degree of 

variability within strategies. The coefficient of variation was 50 percent or above for all 

strategies. While exterior costs within a strategy were highly variable, the costs across strategies 

were more likely to differ from each other than interior strategies. Except for Exterior Strategy 

02, the median costs of exterior strategies did not fall within the interquartile range of any 

adjacent strategy (Figure 6-2). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

 6-10

6.2.4 Site Costs 

A limited number of properties had site or soil treatments. Of the 1,279 properties that were 

eligible for the cost analysis, 157 (12%) had site treatments. The mean cost for conducting site 

treatments at the treated properties was $2,220 while the median cost was $1,080 (Table 6-1). 

The 5th and the 95th percentile costs were $140 and $8,700, respectively. 

Site Strategies 1 and 2 represent interim control treatments. The distinctions between these two 

strategies were not large, with both strategies generally including the installation of mulch and/or 

a ground cover such as seed or sod. Grantees tended to assign a higher-level strategy to 

properties where the area of treatment was larger, so it is appropriate that median costs for Site 

Strategy 2 were somewhat higher than Site Strategy 1 ($970 v. $560) although there was 

substantial overlap in the costs for each strategy. 

Site Strategies 3 and 4 represent partial abatement treatments. Over 70 percent of these higherlevel soil treatments were conducted in Alameda County so the observed costs may be less 

generalizable. The treatments included the full or partial removal of soil or the partial enclosure 

of soil with concrete, asphalt or brick, along with the installation of mulch and other ground 

covers. Like the lower level soil treatments, properties treated with a higher level strategy tended 

have to a larger surface area treated. Site Strategy 4 had a higher median cost than Site Strategy 3 

($5,300 v. $2,700), but the interquartile ranges for the two strategies were similar (Figure 6-3) 

and were indicative of the similarities between the two strategies. 

6.2.5 Discussion 

The results offer a picture of the costs that local programs and property owners might expect to 

pay contractors for the treatment of lead hazards and related housing rehabilitation and repair. 

The costs were reported by the ìgeographyî of the property that was treated and by the intensity 

of treatments to those ìgeographiesî. The presentation of costs does not provide the total costs 

that would be incurred when conducting different levels of treatments to different ìgeographiesî 

of a property. Combining the costs of the different treatment levels reported here would provide 

a fairly good estimate of the costs. For example, treating the interior with window replacement 

(05), the exterior with full paint stabilization (02) and conducting no site treatments would have a 

combined median cost of $8,190 and a combined mean cost of $10,190. 

With a few exceptions, the categorization of lead hazard control work into ìgeographiesî of the 

property and treatment intensities still left highly variable costs. The coefficient of variation was 

generally over 50% for each of the strategies examined. Some of this variation can be attributed 

to differences in the treatments applied within a strategy. An analysis of covariance of interior 

lead hazard control costs was conducted to examine other factors that might explain the 

variation. The description and results of this analysis is presented in the following section.
Figure 6-2: Median and Interquartile Exterior 

Lead Hazard Control Costs by Exterior Strategy

310

850

2460

6350

430 600

1390

4260

9130

1860

1490

3670

7490

11030

5150

$0

$8,000$6,000$4,000$2,000

$12,000$10,000

01 02 03 04 05

Exterior Strategy

Costs

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

6-11
Figure 6-3: Median and Interquartile Site

Lead Hazard Control Costs by Site Strategy

270 360

1640

2470

560

970

2700

5300

1080

2010

7330

8700

$0

$9,000$8,000$7,000$6,000$5,000$4,000$3,000$2,000$1,000

$10,000

1234

Site Strategy

Cost

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

6-12
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

6- 13

6.3 FACTORS CONTRIBUTING TO THE OBSERVED VARIATION IN INTERIOR COSTS

6.3.1 Methodology 

An examination of factors that could explain the variation in interior lead hazard control costs at 

the dwelling unit level was conducted using multiple regression modeling. The analysis 

considered 19 variables believed to be possible influences on costs. The variables were 

categorized into six areas of interest: the intervention strategy, the pre-intervention building 

characteristics and condition, the occupancy status of the dwelling pre-intervention, the 

contractorís economies of scale, the general requirements placed on the contractor, and regional 

cost factors for general construction activities. The specific variables considered are listed in 

Table 6-2. The dependent variable of interior lead hazard control costs was log-transformed, as 

were the independent variable representing the square feet of living space and the three paint 

lead variables. Variables were considered significant at a p-value of 0.05. 

A variable that was originally considered for the analysis to explain the variation in interior lead 

hazard control costs was the cost of concurrent work. However, it was determined that the cost of 

concurrent work was not independent of interior strategy, so it was dropped from the model. The 

cost of concurrent work is presented by strategy for each of the interior strategy levels in Table 

6-3. 

To be eligible for the analysis, a dwelling unit had to meet the requirements for cost separation 

described in Section 6.2.1. Based on analyses by the Evaluation team and ICF Consulting3, a 

decision was also made to exclude the dwellings in New York City from the cost analysis. For 

many of the factors considered in the analysis, New York City displayed some of the most 

extreme values. New York City had the smallest dwellings, the most multi-unit buildings, the 

most dwellings with more than three stories, and the most dwellings treated by full abatement. 

Such extreme values created problems with confounding between variables. Furthermore, the use 

of alternative sources of funding in New York City resulted in a certain level of cost shifting 

between lead and non-lead cost categories. This made their reported lead hazard control costs 

somewhat less reliable. Excluding New York City, 1,223 dwellings were eligible for the 

analysis. 

 

3

 ICF Consulting conducted an independent assessment of the Evaluation costs for HUD and reported that ìThe cost 

data for all grantees other than New York are much more consistent across strategy codes.î ICF also excluded New 

York from its analysis. (Memo to HUD, August 8, 2000) 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Table 6-2:Variables Examined in the Analysis of 

Interior Lead Hazard Control Cost

Intervention

 Interior Strategy 

Pre-Intervention Building Characteristics

 Building Type (single-unit v. small multi-unit (2-4 units) v. large multi-unit) 

Entry Height in Stories 

Living Space (sq. ft.)* 

 Number of Elements with Interior Building Deterioration* 

 Presence of Roof Leak 

 Presence of Plumbing Leak 

 Percent Deteriorated Interior Lead-Based Paint (≥ 1 mg/cm2

 and poor condition)* 

 Paint Lead on Interior Doors/Trim*Interior Strategy 

 Paint Lead on Windows*Interior Strategy 

 Paint Lead on Other Interior Surfaces*Interior Strategy 

Occupancy Status

Contractor Effects

 Number of Units Treated by Each Contractor 

 Number of Units in Building Treated by Contractor 

General Requirements

 Insurance Requirements 

 Waste Disposal Requirements* 

 Performance Guarantee Required 

 Wage Rate Required 

Regional Cost Factors

 Regional Construction Labor Rates 

 Regional Construction Materials Rates 

*Interaction with Interior Strategy also tested 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

6- 15

 Table 6-3: Geometric Mean Interior Costs 

and Associated Concurrent Costs by Strategy 

Strategy Number of 

Units 

Geometric Mean Interior 

Cost 

Geometric Mean 

Concurrent Cost 

Interior 02 194 $407 $1

 03 282 $4,056 $2

 04 341 $5,464 $104

 05 1,159 $6,400 $73

 06 122 $9,419 $29,357

 07 30 $3,097 $17,448

Data from: Form 23 & SpecMaster 

Data as of: June 1, 2000 

Source of Data: Descriptive Statistics from UC Cost Model (5/12/01) 

6.3.2 Results 

The median cost of interior lead hazard control and related housing rehabilitation for dwellings 

in this analysis was $5,635; or about $300 less than the median of the full data set. The 5th and 

the 95th percentile costs were $360 and $12,060, so the results remained highly variable. The 

model accounted for 77 percent of the variation in interior lead hazard control cost. 

Six variables were identified as significant influences on the cost: 

• the treatment intensity (interior strategy level), 

• the size of the dwelling (in square feet), 

• the type of building (single-unit v. multi-unit), 

• the percentage of leaded interior paint in poor condition, 

• the number of dwellings in the grant program treated by a contractor, and 

• whether hazardous waste requirements were placed on the contractor. 

6.3.3 Discussion of Findings 

As discussed in Section 6.3.1, the variables in the models were categorized into five areas of 

interest: the intervention strategy, the pre-intervention building characteristics and condition, the 

pre-intervention occupancy status of the dwelling, the contractorís economies of scale, the 

general requirements placed on the contractor, and regional cost factors for general construction 

activities. For each of the six areas of interest, this section explores the influence of those sets of 

variables on intervention costs. 

6.3.3.1 Intervention Strategy. The treatment intensity as defined by the interior strategy 

explained 65 percent of the variation in interior lead hazard control costs. When controlling for 

other factors, the trends of higher costs for higher intensity work described in Section 6.2 were 

supported by the analysis, with the exception that Strategy 06 and 07 were not significantly 

different in cost. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

6- 16

6.3.3.2 Pre-intervention Building Characteristics and Condition. The pre-intervention building 

characteristics, such as the size and configuration of the buildings, and the pre-intervention 

building condition such as the physical condition of the interior and exterior building 

components were examined. It was hypothesized that smaller dwellings would cost less to treat. 

It was also hypothesized that dwellings in better physical condition at pre-intervention would 

cost less to treat. The analysis provides evidence supporting both hypotheses. 

Dwellings with more living space (measured in square footage) had significantly higher interior 

lead hazard control costs. The median dwelling in this analysis was reported to have a living area 

of 1,000 square feet. A dwelling with 800 square feet of living space (25th percentile) was 

predicted to cost 10 percent less than the average unit, while a dwelling with 1,275 square feet of 

living space (75th percentile) was predicted to cost 11 percent more than the average unit. 

Forty-one percent of the dwellings were in single-unit buildings, while another 41 percent were 

in two- to four-unit buildings (small multi-unit) and the remaining units were in buildings with 

more than four units (large multi-unit). Homes in single-unit buildings were independently 

significantly higher in cost than those in multi-unit buildings. There was no significant difference 

in costs between small and large multi-unit buildings. Homes in single-unit buildings were 

predicted to cost 23 percent more than those in multi-unit buildings after controlling for dwelling 

unit square footage. These results appear reasonable because units in single-unit buildings had 

more windows and exterior doors than dwellings in multi-unit buildings. 

While the number of building components with deterioration at pre-intervention was not found to 

significantly affect costs, dwellings with a higher percentage of painted surfaces with 

deteriorated lead-based paint (i.e., paint rated as in poor condition) had significantly higher 

interior lead hazard control costs. As might be expected, the higher the percentage of painted 

surfaces that needed to be treated, the more the lead hazard control activities cost, even after 

controlling for the interior strategy. In the median dwelling, seven percent of the painted surfaces 

tested had lead-based paint in poor condition. A dwelling at the 75th percentile of paint condition, 

which had twice as much lead-based paint in poor condition (14%), was predicted to cost six 

percent more to treat. 

6.3.3.3 Pre-intervention Occupancy Status of the Dwelling. It was hypothesized that dwelling 

units that were vacant prior to intervention could result in treatment cost savings. Contractors 

would not have to worry about possibly working around occupant belongings or dealing with the 

uncertainty of occupant relocation schedules. The occupancy status was not identified as a 

significant factor influencing interior lead hazard control costs. Contractors may not differentiate 

costs based on the occupancy status of the dwelling. It is also possible that because grantees 

often paid for the relocation of belongings (as well as families) from dwellings, the difference 

between treating occupied and vacant dwellings was not very great. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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6.3.3.4 Contractor Economies of Scale. One of the hypotheses about costs was that when 

contractors were given the opportunity to treat more dwellings, either within a building or across 

a grantee, they would have economies of scale that could reduce prices. Conversely, the use of a 

single contractor by a grantee might indicate the lack of competition in a community that could 

drive up prices. The number of units within a building that a contractor treated was not a 

significant predictor of interior lead hazard control costs. However, the number of dwellings that 

a contractor treated for a grantee was found to be a significant predictor of cost; costs were lower 

when more units were treated. 

For the median dwelling unit in this analysis, the dwelling was treated by a contractor who had 

treated a total of 41 other dwellings for that grantee. A dwelling at the 75th percentile of number 

of dwellings treated by the contractor (85 other dwellings treated) was predicted to cost three 

percent less to treat, while a dwelling at the 25th percentile (24 other dwellings treated) was 

predicted to cost one percent more to treat. 

6.3.3.5 General Requirements Placed on the Contractor. The Evaluation tracked four of the 

general requirements that were placed on contractors. Those general requirements included: 

Insurance Requirements, Waste Disposal Requirements, Performance Bonding Requirements, 

and Wage Rate Requirements. It was hypothesized that as more or a higher level of requirements 

were placed on the contractor, the more the costs of treatments would rise. 

Preliminary analyses of costs suggested that both insurance requirements and hazardous waste 

requirements added to the cost of interior lead hazard control costs. Further investigation of 

insurance requirements found that they were highly correlated with the treatments applied. The 

only grantees that imposed no insurance requirements on their contractors were Milwaukee when 

public employees conducted very low-level treatments and Wisconsin for a subset of their 

projects. When the effect of insurance requirements was examined separately for Wisconsin, it 

was not a significant factor in determining costs. In Milwaukee, the dwellings treated by very 

low-level treatments had no insurance requirements, but they also were treated by public 

employees with no profit and limited overhead, no hazardous waste requirements and no 

performance warranties. Insurance was dropped from the analysis because it was impossible 

from the data available to determine whether the lack of insurance requirements or some other 

element of this public sector program influenced its lower than expected costs. 

A similar examination of effects of a hazardous waste requirement on costs was conducted. 

Overall, 75% of the dwellings in this analysis had hazardous waste requirements and eight of the 

grantees placed hazardous waste requirements on all of their interventions. The other five 

grantees in the analysis placed no hazardous waste requirements on at least a portion of the 

dwellings treated. The five grantees included Milwaukee and Wisconsin, which placed no 

hazardous waste requirements on any of their units. Every interior strategy except Interior 

Strategy 06 had some units where no hazardous waste requirements were placed on them. 

Enough contrasting data were available to suggest that a determination of the effect of hazardous 

waste requirements was feasible. 

Interior lead hazard control costs were significantly higher when hazardous waste requirements 

were imposed. The magnitude of the effect varied significantly by the interior strategy. The cost 

difference of placing a hazardous waste requirement on Interior Strategy 03, 04 and 05 

interventions was estimated to be 23%, 48%, and 31% greater, respectively, than when the 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

6- 18

requirement was not placed on the work. The magnitude of the effect was larger than expected 

and may be partially influenced by other factors related to the grantees. For example, if costs 

were lower in Milwaukee and Wisconsin because of other factors not controlled for in the 

models, these lower costs may be partially attributed to these granteesí choice of no waste 

requirements. 

Comparisons between dwellings with and without hazardous waste requirements that were 

treated with Interior Strategy 02 were not conducted given the differing scopes of work, work 

requirements, and delivery mechanisms used by each grantee that performed this strategy (as 

described in Section 6.2.2). Because only 5 of the 30 dwellings treated with Interior Strategy 07 

had hazardous waste requirements, comparisons for this strategy were also not made. 

6.3.3.6 Regional Cost Factors for General Construction Activities. It was hypothesized that 

some of the cost variation identified could be attributed to the local economic conditions. 

Geographic regions of the country such as northern New Jersey where prices are above the 

national average were expected to have higher lead hazard control costs. To measure regional 

costs, estimates for the cost of construction labor and the cost of construction materials for each 

of the grantee sites were obtained. The source of the data was R.S. Means Building Construction 

Cost Data 1997(R.S. Means 1997), which reported a metropolitan 1996 Means Construction 

Cost Index for both labor and materials costs. The Means Labor Index sets a value of 100 for a 

community where construction labor costs were approximately the national average. A 

community where labor costs were 20 percent higher would receive a score of 120, while a 

community where labor costs were 20 percent lower would receive a score of 80. R.S. Means

used a similar scale for the cost of construction materials. Both variables were considered in the 

analytical model. 

Neither variable was a significant predictor of interior lead hazard control costs. While it is 

surprising that the local construction costs did not help explain costs, it may be that the index 

chosen was not appropriate. It is quite likely that lead hazard control costs did vary from 

community to community (see Section 6.4.3), but the variation did not correspond to differences 

in the local construction costs. For example, a lead-specific materials cost index might be more 

heavily weighted with window and paint costs and less weighted with lumber costs than a 

general construction cost index. Similarly, the construction labor market may be very different 

from the lead abatement worker market, because the former has few barriers to entry while the 

latter field requires special training and certification. A community with a fairly competitive 

construction market could still experience higher lead hazard control costs if there was a limited 

supply of lead abatement contractors/workers. 

6.4 COSTS OF INDIVIDUAL LEAD HAZARD CONTROL TREATMENTS

As with lead hazard control activities, lead hazard control costs were collected at two different 

levels: overall costs for the dwelling unit and specific lead treatment costs. The presentation of 

the average costs for conducting interior, exterior and soil work found in Section 6.2 should 

prove helpful in understanding the general costs that can be expected when conducting different 

intensities of lead hazard control. However, as discussed above, these costs can vary widely 

based on the size and the condition of the dwelling. In order to estimate the cost of a specific 

intervention, spec writers needed to understand the costs of the specific lead treatments on a 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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quantity treated basis (e.g., per square foot or per window). Furthermore, information about the 

costs of specific lead treatments allows for price comparisons between different treatments. 

6.4.1 Methodology 

At the specific lead treatment level, the SpecMasterÆ data reporting system was used to collect 

costs per treatment. For each room/location at a dwelling, the grantees reported the specifications 

conducted, the quantity of the treatment (e.g., 25 square feet), and the total cost of the treatments. 

To identify the cost per quantity, the total cost for each specification in a room was then divided 

by the total quantity of that treatment. 

The specifications were organized into equivalent (cost) treatment categories4

 when the 

treatments and the costs of materials were determined to be similar. For example, grantees had 

four choices of materials for painting doors (acrylic, alkyd, urethane or other paint) and each 

material had its own unique specification. These four specifications were combined into one 

equivalent treatment because the costs of these materials were expected to be similar. When a 

specification was considered unique, the cost of the treatment was examined separately. For 

example, no other specification was similar to the specification for stripping paint from door 

sills. 

The categorization of painting and sealant treatment costs posed a challenge to the evaluation 

team. As explained in Section 5.3.1, grantees used specifications for pure paint stabilization (ìthe 

process of wet scraping, priming and repainting surfaces coated with deteriorated lead-based 

paintî) interchangeably with specifications for painting or sealing any surface. A decision was 

made to classify all painting and sealing as the stabilization of paint even if the evaluators did not 

have a specific report that the treatment included wet scraping or that the surface was coated with 

lead-based paint. Thus, the costs of paint stabilization refer to the costs for any painting activities 

conducted for lead purposes. 

Sometimes grantees used a different measure of quantity treated for the same specification. For 

example, the stabilization of paint on trim was measured in linear feet and in square feet. When 

measures of quantity for a given specification differed, the costs per unit were treated as separate 

outcomes. The Evaluation team did not have enough information to convert differing measures 

of quantity to one standard measure so that the results could be combined. 

The general procedure for recording the specification costs was to develop estimates for the costs 

for individual specifications and then adjust the estimates at each dwelling so that they 

approximated the contractorís total costs. The spec writers were to use their professional 

experience, and in some cases, guidance from the contractor, to estimate the costs for individual 

specifications. The total of the estimated specification costs was required to be within 20 percent 

or $200 (whichever was larger) of the total lead hazard control cost reported separately on Form 

23. Dwellings where the costs did not meet this criterion were excluded from analysis. While this 

procedure was intended to improve the precision of the estimated costs, it must be recognized 

that the costs reported remain estimates of what the treatments cost. 

 

4

 These equivalent (cost) treatment categories treatments differ from the equivalent (effectiveness) treatment 

categories described in Section 5.3 because the latter categories include specifications that were not only expected 

have a similar cost but were expected to be of similar effectiveness (e.g., similar lead dust generation). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Some grantees reported the costs of general requirements separately while other grantees rolled 

the costs of these factors (e.g., insurance, waste, worksite preparation) into the treatment costs. 

To standardize the treatment costs across grantees, if general requirement costs were reported 

separately, these costs were first totaled for a building and then proportionally distributed by cost 

across all of the treatments. 

Following preliminary analyses of the treatment costs per quantity treated, it became apparent 

that treatment costs varied from grantee to grantee. Some grantees had consistently higher costs; 

others had consistently lower costs, while other grantees had costs that were high for some 

treatment categories and low for others. Median costs for the grantee with the highest treatment 

costs were often three to four times higher than the median costs of the grantee with the lowest 

treatment costs. Consideration was given to adjusting costs by grantee, but the level of variation 

within some grantees made this adjustment difficult. Furthermore, even after collapsing the 

specifications into equivalent treatment categories, similar treatments were often conducted by 

only three or four grantees. The Evaluation team was concerned that with limited comparative 

data, any adjustments would introduce enough error that the final costs would not be reliable. 

In order to address the concerns, the median treatment costs are presented by grantee. In 

addition, the maximum and minimum grantee median costs for each treatment are presented to 

offer an indication of the variation across grantees. To ensure that the costs are based on a 

reasonable sample of occurrences, a treatment had to be used in at least 25 room/locations by a 

grantee and had to be used by at least three grantees. Twenty-seven treatments met these criteria. 

In addition, when six or more grantees used a treatment at least 25 times, the median of the 

grantee costs is presented. 

6.4.2 Results 

The median treatment costs by grantee are presented in Table 6-4. The table includes three 

wall/ceiling treatments, three floor/stair treatments, four door treatments, seven window 

treatments and nine door treatments as well as an exterior treatment. No site treatments met the 

criteria for presentation. 

6.4.2.1 Walls/Ceilings. The stabilization of paint on walls and ceilings was a treatment 

conducted by 13 of the 14 grantees. The enclosure of walls or ceilings with a drywall or laminate 

was also a commonly selected treatment with nine grantees conducting the treatment in at least 

25 rooms. For both treatments, the most commonly used unit of treatment was square footage. 

For the nine grantees that conducted both enclosure and paint stabilization, the median cost of 

paint stabilization ranged from $0.75 to $1.83 per square foot, with a grantee median of $1.45. 

The median cost of enclosure ranged from $0.86 to $3.50 per square foot, with a grantee median 

of $2.01. In most cases, the cost of enclosure did not include the cost of finish painting, 

suggesting that additional costs would have to be incurred to bring the dwelling to a condition 

likely to satisfy residents. In Vermont, the paint stabilization treatment included only prepping 

and priming the surface. Non-lead contractors were used to repaint the whole room. Baltimore 

often had property owners complete the finish painting. These practices help explain the lower 

costs of paint stabilization for these two grantees. 

A point of debate has been whether it is more cost effective to paint a limited area of a wall or 

ceiling, instead of a whole wall or a whole room. Anecdotally, some grantees reported that 

requiring spot paint stabilization was not a substantial cost savings because contractors charged 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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more for a limited treatment. Six grantees reported costs for both full paint stabilization and 

limited paint stabilization. For two of these six grantees, the median cost per square foot of 

limited paint stabilization was less than full paint stabilization. When median costs of limited 

paint stabilization were higher than full paint stabilization, the costs for limited paint stabilization 

ranged from 2% to 200% more than full paint stabilization. The observed results do not 

definitively answer the question of the relative costs of full versus partial paint stabilization. 

6.4.2.2 Floors/Stairs. Sufficient cost data were reported by six grantees that enclosed floors with 

underlayment and a vinyl covering. The median cost for this work ranged from $2.80 to $5.09 

per square foot, with a grantee median cost of $3.23. Floor paint stabilization cost data were 

available from three grantees, with a range in median costs from $0.84 to $3.75 per square foot. 

Two grantees used both enclosure and paint stabilization of floors as separate treatments. For 

these grantees, floor enclosure cost was three to four times the cost of paint stabilization. 

The stabilization of paint on stairs was conducted by four grantees in at least 25 of their 

stairways. Costs were reported per riser (or per step). The median cost ranged from $7.82 to 

$23.50 per riser. 

6.4.2.3 Doors. Costs for the treatment of doors were reported on a per door basis. Replacement 

cost data were available from seven grantees that installed metal pre-hung exterior doors and 

from six grantees that installed wooden hollow-core interior doors. The median cost for exterior 

door replacement ranged from $200 to $705, with a grantee median of $581. The median cost for 

interior door replacement ranged from $86 to $212, with a grantee median of $174. 

Vermont had a lower reported cost for exterior door replacement, partially the result of their twophase method of lead hazard control. Lead abatement contractors were hired to remove doors, 

while non-lead contractors installed the new replacement doors. The price of $200 per door only 

included installation and did not include removal. Removal costs were reported to be 

approximately $25 per door. 

Eight grantees applied a treatment in which interior doors were planed, adjusted (properly 

rehung), and stabilized in at least 25 rooms. The median cost for this treatment ranged from $64 

to $140 per door, with a grantee median of $88. Eight grantees treated interior doors with just 

paint stabilization. The median cost for door paint stabilization ranged from only $29 to $180 per 

door, with a grantee median of $48. Five grantees reported costs for both paint 

stabilization/adjustment and paint stabilization only. For four of these grantees, the cost of paint 

stabilization and adjustment was more than paint stabilization only. The paint stabilization and 

adjustment treatments cost $15 to $48 more (12% to 125% more) per door. In Wisconsin, there 

was essentially no cost difference between the two treatments. 

Five grantees reported costs for both paint stabilization and adjustment of interior doors and 

replacement of interior doors. The median cost of replacement was two to three times more than 

paint stabilization and adjustment at four of the grantee sites. In Rhode Island, the cost of 

replacement was lower, but by only 10%, which is not substantial given the method of 

estimation. 
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Table 6-4: Median Treatment Costs by Grantee: 

Treatments used at least 25 times by a grantee, by at least 3 grantees 

(Adjusted for General Requirement Costs) 

Component 

System Wall/Ceiling Floor/Stair Doors Treatment Enclose Walls/Ceilings ñ Drywall Stabilize Walls/Ceilings Stabilize Walls/Ceilings ñLimited Surface Enclose Floors ñ Underlayment and Vinyl Stabilize Floors Stabilize Stairs Replace Doors (Ext.) ñ Metal Pre-Hung Replace Doors (Int.) ñ Wood Hollow-core 

Stabilize Doors ñ Plane and Adjust Stabilize Doors 

UNIT $/SF $/SF $/SF $/SF $/SF $/RI $/EA $/EA $/EA $/EA 

AC 3.50 1.04 140.00 125.00

BA 2.49 1.00 2.85 125.00 65.00 

BO 2.35 1.51 2.67 

G CA 1.65 3.25 162.00 85.10 37.70

R CH 1.91 1.40 581.00 212.00 

A CL 2.01 1.60 5.09 1.34 28.50

N MA 2.45 2.09 48.20

T ML 1.87 1.15 7.82 84.30 47.20

E MN 7.10 3.75 700.00 180.00

E NJ 705.00 

NY 1.65 1.59 1.90 3.21 23.50 590.00 211.00 63.50 31.60

RI 1.22 0.56 2.80 0.84 501.00 85.70 94.80 

VT 0.86 0.75 0.77 3.35 17.00 200.00 90.00 

WI 3.06 1.83 5.47 19.30 525.00 185.00 95.20 96.80

Grantee Min 0.86 0.75 0.56 2.80 0.84 7.82 200.00 85.70 63.50 28.50

Grantee Med.* 2.01 1.51 2.00 3.23 - - 581.00 174.00 87.60 47.70

Grantee Max 3.50 7.10 5.47 5.09 3.75 23.5 705.00 212.00 140.00 180.00

Total # Uses 1786 4001 1630 1417 459 262 607 649 4206 1139

EA= Each, LF= Linear Feet, RI= Per Riser, SF=Square Feet 

*Grantee Median only presented when six or more grantees qualified for table. 

Data from: SpecMaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C8
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Table 6-4 (continued): Median Treatment Costs by Grantee: 

Treatments used at least 25 times by a grantee, by at least 3 grantees 

(Adjusted for General Requirement Costs) 

Component 

System Trim Treatment Replace Trim ñ Historic Molding Replace Trim ñ Modern Molding Replace Door Sill Strip Trim ñ Scrapers Strip Door Sill 

Stabilize Trim Stabilize Trim ñ Limited Surface Stabilize Radiator Stabilize Cabinet 

UNIT $/LF $/LF $/EA $/LF $/EA $/LF $/LF $/EA $/LF 

AC 5.60 6.01 8.48 

 BA 3.00 15.00 16.00 1.00 50.00 

 BO 5.07 2.24 1.32 1.77 

G CA 2.38 2.05 

R CH 2.29 2.66 

A CL 1.64 

N MA 4.14 2.54 1.29 1.26 

T ML 2.15 28.60 

E MN 6.00 

E NJ 37.30 

 NY 2.68 0.95 42.90 31.50 

 RI 2.80 33.40 1.39 0.85 44.50 16.80 

 VT 6.09 3.00 70.00 3.53 40.00 1.50 

 WI 3.36 142.00 

Grantee Min 4.14 2.24 15.00 1.29 16.00 0.95 0.85 42.90 16.80 

Grantee Med.* - 2.68 - - - 1.91 - - - 

Grantee Max 6.09 5.60 70.00 3.53 40.00 6.01 8.48 142.00 31.50 

Total # Uses 303 2046 92 191 654 6044 193 1153 211 

EA= Each, LF= Linear Feet, RI= Per Riser, SF=Square Feet 

*Grantee Median only presented when six or more grantees qualified for table. 

Data from: SpecMaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C8
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Table 6-4 (continued): Median Treatment Costs by Grantee: 

Treatments used at least 25 times by a grantee, by at least 3 grantees 

(Adjusted for General Requirement Costs) 

Component 

System Windows 

Exterior 

Clad/Trim 

Treatment 

Replace Window - Wood Replace Window ñ Vinyl Replace Window ñ Aluminum Replace Window ñ Sash Only Install Window Jamb Liner Stabilize Window & Enclose Trough Stabilize Window Stabilize Exterior Cladding/Trim 

UNIT $/EA $/EA $/EA $/EA $/EA $/EA $/EA $/SF 

AC 563.00 500.00 246.00 238.00 115.00 2.68

BA 285.00 30.00 1.36

 BO 241.00 3.80

G CA 300.00 30.60 2.22

R CH 507.00 104.00 

A CL 220.00 162.00 38.10 

N MA 261.00 1.25

T ML 427.00 120.00 50.00 2.17

E MN 372.00 320.00 149.00 145.00 

E NJ 567.00 

NY 316.00 84.30 24.70 

RI 335.00 226.00 112.00 27.40 0.83

VT 225.00 205.00 165.00 75.00 0.77

WI 425.00 400.00 119.00 85.00 2.66

Grantee Min 225.00 205.00 246.00 162.00 84.30 112.00 24.70 0.77

Grantee Med.* - 303.00 - - - - 44.10 2.17

Grantee Max 563.00 567.00 316.00 238.00 120.00 149.00 145.00 3.80

Total # Uses 1139 5682 399 332 521 139 1911 729

EA= Each, LF= Linear Feet, RI= Per Riser, SF=Square Feet 

*Grantee Median only presented when six or more grantees qualified for table. 

Data from: SpecMaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Table C8 
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6.4.2.4 Trim5. Nine grantees replaced trim (e.g., baseboards, casings, other molding) with 

modern molding. Three of these grantees also replaced some of their molding with historic stock. 

For all nine grantees, the median cost of replacement ranged from $2.24 to $5.60 per linear foot, 

with a grantee median of $2.68. The median cost of using historic molding was one and one half 

to two times the cost of modern molding at each of the three grantees that reported such costs. 

The three grantees that used historic trim (Boston, Massachusetts and Vermont) also reported the 

use of scrapers to strip paint from trim in at least 25 rooms. The specifications for these 

treatments called for the trim to be primed and painted after replacement or stripping. While the 

median cost of replacing trim ranged from $4.14 to $6.09 for these three grantees, the median 

cost of removing the paint and leaving the trim in place ranged from $1.29 to $3.53 per linear 

foot. The median cost of replacement of trim with historic molding was about $2.50 to $3.50 per 

linear foot more than stripping. 

Twelve of the fourteen grantees stabilized their trim as a common treatment. The median cost of 

paint stabilization ranged from $0.95 to $6.01 per linear foot, with a grantee median of $1.91. 

Eight of the grantees conducted both paint stabilization and replacement of trim separately. For 

six of these grantees, the median cost of replacement was higher than the median cost of paint 

stabilization, with replacement ranging from 16% to 200% more. 

Three grantees used a specification for the stabilization of a limited amount of paint on the trim. 

Only two of these grantees, however, reported both full paint stabilization and limited paint 

stabilization of trim so a comparison of these costs is not very informative. Of the two grantees 

that conducted both treatments, limited paint stabilization cost more for one grantee and less for 

another. 

Grantees also used specifications to identify the treatment to specific trim components. Three 

grantees replaced door sills and three grantees stripped door sills as common treatments. 

Baltimore and Vermont conducted both treatments. In Baltimore, the median costs were 

generally the same ($15 v. $16 per sill), while in Vermont the median cost of replacement was 

higher ($70 v. $40 per sill). Grantees also reported the cost of stabilizing paint on radiators and 

on cabinets. The range of median cost for the four grantees stabilizing radiators was $42 to $142 

per radiator. The range of median cost for the three grantees stabilizing cabinets was $16.80 to 

$28.60 per linear foot of cabinetry. 

6.4.2.5 Windows. Grantees commonly selected four types of window replacement: wood, vinyl, 

aluminum and sash only. The most common type of window selected was vinyl replacement, 

which was installed in at least 25 rooms for all grantees except California and New York City. 

The median cost of vinyl window replacement ranged from $205 to $567 per window, with a 

grantee median cost of $303. Five of the grantees also selected wood replacement windows for 

some of their dwellings. The cost of wood windows was universally higher, with a median cost 

that was 6% to 48% more. 

As with door installation, Vermontís method of conducting lead hazard control made their cost 

values less comparable to the other grantees. Lead abatement contractors were hired to remove 

windows, while non-lead contractors installed the new replacement windows. The price of $205-

 

5

 Trim as defined here includes traditional trim work such as casings, baseboards and other moldings as well as other 

building components such as cabinetry, radiators and radiator covers that are often coated with trim paint. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

6- 26

225 per window did not include the price of removal. Removal costs were reported to be 

approximately $35 per window. 

Three grantees (Alameda County, California and New York City) commonly used aluminum 

replacement windows. Because these windows were often used to replace windows in units of 

more modern construction or in larger multi-unit buildings, the window systems were not very 

comparable to the wood and vinyl windows discussed above. The aluminum windows were 

generally single-hung or slider windows, while the wood and vinyl windows were commonly 

double-hung windows. The median cost of the aluminum windows ranged from $246 to $316 per 

window. 

Alameda County, Cleveland and Vermont selected the replacement of window sashes in at least 

25 of the rooms that each grantee treated. The median cost of window sashes ranged from $162 

to $238 per window. At all three sites, the cost of replacement of the sash only was 20% to 52% 

less than full replacement of vinyl windows. However, grantees that conducted sash only 

treatments may have incurred further costs to treat window components other than the sash. 

Three grantees (Chicago, Milwaukee and New York City) selected the installation of jamb liners 

as a common window treatment. The median cost ranged from $84 to $120 per window. The 

installation of jamb liners was often accompanied by additional window work including paint 

stabilization and the use of aluminum caps on window sills and/or troughs. In Chicago and 

Milwaukee, where vinyl windows were also a common treatment, the cost of replacement was 

three to four times higher than the jamb liners. A treatment of stabilizing the whole window and 

enclosing the troughs with caps had a median cost of $112 to $149 per window for the three 

grantees that used this specification. Ten grantees used a full window paint stabilization 

specification in at least 25 of their rooms. The median cost ranged from $25 to $145 per window, 

with a grantee median of $44. 

6.4.2.6 Exterior Treatments. Only one treatment to the exterior of the building or to the soil was 

reported by at least three grantees in at least 25 of the properties they treated. The paint 

stabilization of the exterior cladding and trim of the building was conducted by nine of the 

grantees. The median cost of this treatment ranged from $0.77 to $3.80 per square foot, with a 

grantee median cost of $2.17. The median cost of exterior paint stabilization was higher than 

interior wall and ceiling paint stabilization for six of the nine grantees, with one grantee having 

roughly equal costs and two grantees having lower exterior costs. As with interior paint 

stabilization costs, the exterior paint stabilization costs in Vermont were somewhat deflated 

because the treatment included only the cost of prepping and priming the surfaces. 

6.4.3 Discussion 

Table 6-4 provides an opportunity to examine costs by treatment and to make cross treatment 

comparisons. While the flexibility given to grantees in defining and revising their specifications 

places some limitations on the comparability of some data, particularly from Vermont, the 

specifications are similar enough that the values presented should prove useful. 

The Evaluation team examined reported data and used field observations to try to explain cost 

differences. In Vermont, the lower costs were clearly attributable to the two-phased contracting 

system. In other sites, including Baltimore, Rhode Island, and New York, costs for finish work 

were sometimes shifted to a property owner or non-lead contractor paid by non-lead funds. The 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

6- 27

Baltimore program made property owner contributions a requirement for participation in the 

program. Property owners in Rhode Island were often dissatisfied with the appearance of the 

limited paint stabilization conducted and paid the contractor extra for full repainting. Because of 

New York Cityís practice of coupling HUD LHC Grant funds with other funding sources, the 

full cost of the final painting is not always included in these estimates, because the cost of such 

work was paid for separately. 

In many cases, however, the wide variation in costs across grantees could not be explained by 

specification differences or reporting differences. Prices were almost always higher in Alameda 

County, Minnesota and Wisconsin, and the Evaluation team did not observe any unique 

reporting practices that might explain these costs. These costs may simply reflect the higher costs 

for lead abatement in these communities during the period of the Evaluation. 

6.5 FINAL COMMENTARY ON LEAD HAZARD CONTROL COSTS

The results presented here offer a large pool of empirical data on lead hazard control costs. 

Because of design issues, there were limits to what data was reported. The gathered information 

was limited to the costs of conducting construction-related activities and did not include costs for 

testing, relocation, construction oversight or other grantee-related costs. The costs represent the 

full costs of interior, exterior, and site lead hazard control. Incremental costs are not provided in 

this report. Because data were reported based on the intent of the grantee when applying the 

treatments, some variation in the costs from grantee to grantee was expected from the beginning 

because grantees interpreted cost allocation slightly differently. Finally, the data presented here 

are based on costs of interventions conducted between 1994 and 1997, so some adjustments in 

lead hazard control markets may have occurred since then. 

While these limitations create barriers to identifying a single set of national cost values, the 

information presented here offers important cost data that have not been available. A property 

owner or lead poisoning prevention program should be able to better estimate their costs after 

giving some consideration to the local conditions that they face. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-1

7.0 OBSERVED OUTCOMES IMMEDIATELY POST-INTERVENTION 

7.1 INTRODUCTION TO IMMEDIATE POST-INTERVENTION PERIOD

At the conclusion of every lead hazard control intervention supported by the HUD Lead Hazard 

Control Grant Program, grantees are required to have a clearance examiner verify that the work 

was satisfactorily completed. This review process is referred to as clearance. The principles of 

clearance as described in the HUD Guidelines1

 (HUD 1995) are to determine if: 

• The lead hazard control work was actually completed as specified. 

• The area is safe for unprotected workers to enter. 

• The area is a safe place for residents and young children to live. 

Clearance examiners determine that clearance has been achieved in two steps. First, a visual 

examination of the worksite is conducted to determine that all specified work was completed, 

that lead-based paint hazards were satisfactorily controlled and that no visible settled dust or 

debris remains. If the dwelling passes the visual examination, the clearance examiner collects 

dust wipe samples from the floor and window in at least four rooms of the dwelling. When all 

dust samples from each surface have dust lead loadings at or below the clearance standards for 

that surface (defined either by HUD/EPA or by a more stringent state standard), then the 

dwelling unit passes clearance and the lead hazard control work is considered complete. Should 

the clearance examiner determine that the dwelling unit did not pass the visual examination or 

that any dust sample had a dust lead loading above the applicable standards, then the dwelling 

fails clearance. For dwelling units that fail clearance, grantees are required to have the work 

completed and/or be recleaned, so that they may be reexamined and eventually pass clearance. 

This chapter provides details about the specific clearance procedures used by grantees in the 

HUD Lead Hazard Control Grant Program during the first two rounds of funding and the 

clearance data that were collected for the Evaluation. A key part of this discussion concerns the 

clearance dust lead standards that were in place at the time of the Evaluation, including the local 

standards under which some grantees were working. This chapter will examine the effects of 

lead hazard control interventions, as categorized by strategies, on initial clearance dust lead 

loadings and on the probability of failing initial clearance dust lead testing. An examination of 

the incidence of dwelling units failing to pass initial clearance tests was an original objective of 

the Evaluation. 

This chapter also includes sections that describe the occupant protection procedures for resident 

families during the intervention through clearance. Because many lead hazard control activities 

generate substantial amounts of leaded dust and debris, HUD directed grantees at the outset of 

the program to take ìappropriate action to protect occupants, especially young children and 

pregnant women, from lead hazards associated with lead hazard reduction activities.î (HUD 

1993) Occupant protection activities, including family relocation, are summarized based on 

information systematically collected from the families. 

This section on occupant protection also includes an analysis of the factors associated with a rise 

in a childís blood lead level of 5 micrograms/deciliter (μg/dL) or more from pre-intervention to 

 

1

 Clearance procedures described in the 1995 Guidelines differ somewhat from EPA and HUD regulations, but those 

regulations were not in effect when Evaluation clearance were being performed. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-2

immediate post-intervention. HUDís emphasis on children being protected during the lead 

hazard control work prompted the Evaluation team and HUD to make the analysis of 

ìsignificantî increases (≥ 5 μg/dL) of individual blood lead levels identified during immediate 

post-intervention, testing one of the nine original study objectives. Since inadequate occupant 

protection was just one factor that might have caused such blood lead elevations, HUD wanted to 

fully understand what factors were related to the increases and what, if anything, could be done 

to prevent them in the future. The analysis includes a discussion of the results of grantee 

feedback concerning each child whose blood lead level increased 5 μg/dL or more and an 

examination of factors that significantly differed between children who experienced such 

increases in blood lead levels and those who did not. 

7.2 OCCUPANT PROTECTION POLICIES

HUD stipulated that grantees design interventions in a manner that would protect the occupants 

and prevent their exposure to lead that was made more available during the process of 

intervention. Previous research has indicated that large increases in blood lead can occur as a 

result of lead abatement activities unless special precautions are taken to keep the child away 

from the work area during intervention (Amitai 1987; Farfel 1990). Furthermore, a thorough 

cleaning of the work area must occur after the intervention but prior to reoccupancy in order to 

protect the occupants. Based on these findings, HUD offered guidance on occupant 

protection/relocation in order to protect residents during interventions and required clearance 

testing in order to protect residents at reoccupancy. 

7.2.1 HUD Occupant Protection Policies under the HUD LHC Grant Program 

HUD issued guidance that prohibited access by occupants to work areas or designated adjacent 

areas while lead hazard control activities were taking place (HUD 1993). The memo explicitly 

stated ìoccupants may not reoccupy a work area or adjacent area until post-lead hazard reduction 

clearance standards have been met.î The guidance further stated that when work required more 

than eight hours to complete, families should, in general, be relocated from the dwelling. 

Grantees that did not relocate all families were required to prepare detailed descriptions of their 

occupant safety strategies. The only situations for which relocation was not required were when 

the lead hazard control activities: 

• Did not disturb lead-based paint, and the intervention involved cleaning only; 

• Were kept to a limited number of rooms so that occupants had access to bathroom, 

kitchen, sleeping facilities and adequate egress; dust and debris were properly 

contained within those rooms undergoing lead hazard control; and acceptable 

clearance results from work area samples were available prior to allowing 

reoccupancy; and/or 

• Were limited to exterior treatments; windows and doorways within the work area 

were sealed; and occupants had adequate egress from the building that did not pass 

through the work area. 

 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-3

7.2.2 HUD Clearance Policies under the HUD LHC Grant Program 

The original NOFA for the HUD Lead-Based Paint Hazard Control Grant Program (HUD 1992) 

stated that dwelling units ìshall not be reoccupied until acceptable clearance levels are 

achieved.î To achieve clearance, grantees were required to collect post-intervention dust wipe 

samples and have the levels of lead analyzed by an independent, accredited laboratory. At the 

start of the Grant Program, clearance thresholds were determined by the values listed in the HUD 

Interim Guidelines for Hazard Identification and Abatement in Public and Indian Housing (the 

HUD Interim Guidelines) (HUD 1990). At the time, a dwelling unit failed clearance if any one 

sample had lead levels above: 

200 micrograms per square foot (μg/ft2) on floors 

500 μg/ft2 on window sills, or 

800 μg/ft2 on window troughs (known then as window wells). 

Because there were no applicable Federal standards in 1992, HUD incorporated Maryland and 

Massachusettsís standards into the HUD Interim Guidelines. When Title X was passed in 

October 1992, the EPA was given authority to promulgate regulations identifying leadcontaminated dust hazards, as well as paint and soil hazards. While no health-based standards 

were established for leaded dust during the period of data collection for the Evaluation, HUD and 

EPA released guidance in 1994 identifying revised clearance guidance for dust lead hazards. The 

revised guidance retained the previously identified 500 μg/ft2 and 800 μg/ft2

 for window sills and 

window troughs, respectively, but lowered the threshold for floors to 100 μg/ft2. 

Because the Round One and Two NOFAs for the HUD LHC Grant Program had established 200 

μg/ft2 as the clearance threshold for floors, HUD left the decision whether to use the revised 

interim guidance of 100 μg/ft2 to the grantees. Three grantees, Cleveland, New Jersey and New 

York City, chose to clear floors at the lower guidance level. The Minnesota grantee used its state 

regulatory standard of 80 μg/ft2 for floors to clear dwelling units in Round One of the Grant 

Program. All other grantees retained 200 μg/ft2 as the standard for floors. 

In 2000, HUD promulgated regulations setting new interim clearance standards for all Federallyassisted housing. EPA published final clearance standards which took effect in January 2001 and 

which have been adopted by HUD (EPA 2001a). Those standards are: 

40 μg/ft2

 on floors, 

250 μg/ft2 on window sills, and 

400 μg/ft2

 on window troughs. 

Under these standards, a dwelling fails clearance when any single dust lead sample result is equal 

to or above the appropriate standard2

. While these levels are provided as a reference, it must be 

emphasized that these standards were not publicly available prior to the completion of all 

dwelling unit interventions in the Evaluation in October 1997, and were not used as clearance 

standards for any Evaluation units immediately post-intervention. 

The clearance requirements for the Grant Program called for dust wipe testing on interior floors, 

window sills and window troughs (if present). The Grant Program recommended that grantees 

 

2

 For risk assessment purposes, a floor or window sill is considered a hazard under these regulations when the 

arithmetic mean dust lead loading for a surface is above the appropriate standard. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-4

follow the guidance found in the 1990 HUD Interim Guidelines, which called for one singlesurface sample from each room treated if paint removal was not conducted and three singlesurface samples from each room if paint removal was conducted. In 1995, HUD released the 

Guidelines for the Evaluation and Control of Lead-Based Paint Hazards in Housing (HUD 

1995), which revised the clearance recommendations to two dust samples (a floor and window 

surface) in at least four treated rooms. Grantees were allowed to comply with either guidance or 

with state or local standards, if more protective. 

 

7.3 TREATMENT EFFECTIVENESS AT CLEARANCE

One of the principal objectives of the Evaluation (Objective 3) was an assessment of the 

clearance failure rates. The Evaluation designers were interested in the possible effects of the 

different treatment strategies on a contractorís ability to achieve clearance after construction 

work and final cleaning had been completed. The section describes analyses examining treatment 

effectiveness at clearance and the findings of these analyses. This section focuses on the initial 

clearance tests that were performed on the dwellings. All dwellings analyzed in this section 

passed clearance and had final clearance dust lead loadings that were at or below the standards 

observed by the grantees. 

The Evaluation team hypothesized that the different interior lead hazard control strategies would 

primarily affect dust lead loadings at clearance in three ways: 

• First, the work conducted under the different strategies was expected to generate different 

levels of lead dust. For example, a clean-only treatment should generate very little leaded 

dust, while an on-site paint removal project would likely generate much more leaded dust 

and debris. 

• Second, the containment and cleaning practices associated with a strategy were expected 

to have different effects on reducing any pre-existing dust lead and any dust lead that was 

generated. For example, under the HUD Guidelines lower level strategies required lower 

levels of containment. At the same time, the effectiveness of cleaning/containment was 

also expected to be largely influenced by the contractorsí experience and their 

compliance with the guidelines and each granteeís enforcement of the guidelines. 

• Third, the treatments conducted as part of the different strategies were expected to have 

different impacts on the ìcleanabilityì of surfaces. A clean-only treatment was not 

expected to improve the surface condition of components, while the replacement of a 

window or enclosure of a floor conducted as part of a higher-level strategy was expected 

to improve surface condition (and possibly change the type of surface). 

The long-term benefits of a higher-level strategy, such as the reduction of leaded sources in a 

dwelling, was not expected to be apparent at clearance. In fact, if substantial amounts of leaded 

dust were generated by a higher level strategy and the dust was not well contained, then a higherlevel strategy may not perform as well as lower level strategies at clearance given similar preintervention conditions. 

7.3.1 Methodology 

A fundamental part of the Evaluation was the use of a standard protocol for collecting dust lead 

samples at all data collection phases. The Evaluation protocols called for dust sampling to be 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-5

conducted in the interior entry to the dwelling, a living area (or childís play area), the kitchen, 

and the two youngest childrenís bedrooms3 during each phase of the study. The protocols called 

for the collection of floor samples in all of these areas and a window sill or window trough 

sample in rooms other than the entry (as described in Section 3.1). Regardless of the procedures 

used by grantees to select clearance sampling locations to meet programmatic requirements, the 

Evaluation protocols required that clearance dust sampling include single-surface samples from 

the alternate side of the doorways and windows that were tested pre-intervention. 

While grantees recorded and data-entered all clearance dust lead results for the dwelling units 

they tested, the Evaluation team determined that only the minimum Evaluation dust samples (as 

required to be reported on the first page of the dust collection form) would be used for analyses 

of clearance results. Because some grantees collected only the minimum number of samples at 

clearance and other grantees collected many additional samples, comparisons of failure rates 

would be biased if all samples were included in these analyses. The basic principles of 

probability would result in dwelling units having a higher chance of having one sample above 

the clearance standards (and fail clearance) if more clearance samples were collected. 

In order to compare clearance failure rates across treatment strategies (or any other factor), the 

Evaluation team adopted a single set of dust lead comparison values for all dwellings: 100 μg/ft2 

for floors, 500 μg/ft2 for window sills and 800 μg/ft2 for window troughs. Although a floor 

standard of 200 μg/ft2 was most commonly used by grantees in the Evaluation, 100 μg/ft2 was 

selected because it was the Federal guidance level at the time when most Evaluation 

interventions were conducted and at the point when the final analysis plan for this report was 

developed. Furthermore, an analysis of initial clearance ìfailure ratesî by grantee determined 

that the granteeís choice of a floor clearance standard of either 100 or 200 μg/ft2

 did not affect 

the probability of failure at 100 μg/ft2

. 

Clearance findings are presented at two levels: overall findings about the initial clearance failure 

rates and analyses of the effect of treatment strategies on clearance dust lead loadings. The 

overall findings are presented as tabled results of clearance failure rates by grantee. For a 

dwelling unit to be included in these tables, grantees had to provide evidence that the dwelling 

unit had achieved clearance. 

Two methods of statistical modeling were used to examine variables influencing immediate postintervention dust lead loadings. Nested and logistic regression models were fit to the clearance 

dust data to determine predictors of clearance dust lead loadings. For these analyses, entry floor, 

bare floor, all floor, window sills and window troughs were separately modeled. Nested models 

used the dust lead loading values of each individual dust lead sample in a dwelling as the 

outcome. Logistic regression was used to model the probability of failure of the appropriate 

HUD/EPA guidance: 100 μg/ft2

 for floors, 500 μg/ft2 for window sills and 800 μg/ft2 for window 

troughs. Each dwelling was classified as passing or failing clearance based on the maximum dust 

lead loading (for each surface type) in the dwelling. 

Exhibit 7-1 at the end of this chapter presents the possible predictors that were examined in the 

statistical models. Backward elimination of the possible predictors in each model was performed; 

the interior strategy was retained in all models regardless of statistical significance to allow for a 

 

3

 In dwelling units with only one childís bedroom, then just the one bedroom was sampled. If no child was present, 

then the smallest bedrooms were sampled. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-6

test of its potential effects in the final, reduced models. The SAS procedures, PROC MIXED and 

PROC GENMOD (with a logit link), were used to run the nested and logistic models, 

respectively. All lead variables (i.e., dust and paint) were transformed to their natural logarithm 

to normalize their statistical distributions. 

7.3.2 Initial Clearance Failures 

This report focuses on the 2,682 dwelling units that had data available to demonstrate that the 

dwelling unit passed clearance. Of these dwellings, 526 dwellings (20%)4 did not pass clearance 

on the first attempt based on the grantee-specified clearance standards described in Section 7.2.2. 

An additional 39 dwellings were retested by grantees at clearance indicating that the grantees 

may have identified additional hazards outside of those reported for Evaluation purposes. When 

these additional failures are included, 21 percent of units that eventually passed clearance failed 

the initial clearance dust tests. 

For the 565 dwelling units that were retested, an average of 1.13 recleanings and retests were 

required per dwelling to pass clearance. The vast majority of the dwellings that were retested 

passed clearance after just one additional cleaning. The number of retests needed was not related 

to the interior strategy that was applied. 

Using a universal floor comparison value of 100 μg/ft2

, 701 dwellings (26%) would have failed 

the initial clearance test. Even using a universal value, the initial clearance failure rates varied by 

grantee, with failure rates above 40 percent in Boston (56%), Milwaukee (47%) and 

Massachusetts (46%) and at or below 10 percent in New York City (10%), Rhode Island (9%) 

and New Jersey (0%) (Table 7-1). Initial clearance failure rates also varied by surface type 

sampled. Twenty percent of the dwelling units had at least one floor sample above 100 μg/ft2. 

Window sills and troughs failed at lower rates: 6% and 7%, respectively (Table 7-2). 

The number of surfaces tested for each surface type can explain, in part, the difference in failure 

rates. On average, five floor samples, two window sill samples, and one window trough sample 

were collected from each dwelling. The higher rate of failures on floors can be explained in part 

because the chance of finding one failure out of five samples is greater than the probability of 

finding a failure from one or two samples. 

The clearance failure rates for specific surfaces also varied by grantee (Table 7-2). Thirty percent 

or more of the dwellings had at least one initial floor dust lead clearance sample above 100 μg/ft2

in Boston (56%), Massachusetts (42%), and Milwaukee (30%). Less than 10 percent of the 

dwellings had at least one initial floor dust lead clearance sample above 100 μg/ft2

 in California 

(9%), Rhode Island (8%), New York City (4%) and New Jersey (0%). Two grantees had initial 

clearance failure rates above 10 percent on both window sills and window troughs: Milwaukee 

(13% and 18%, respectively) and Minnesota (11% and 12%, respectively). Rhode Island (1%) 

and New Jersey (0%) had initial clearance failure rates of one percent or less on both window 

sills and troughs. 

 

4

 When all dwellings with an Evaluation clearance dust test are considered, including those with no evidence of final 

clearance, 24 percent of the dwellings (686 of 2,842) failed the initial clearance. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-7

 Table 7-1: Number and Percentage of Dwellings with 

Initial Post-Intervention Dust Lead Loadings Above

1995 HUD/EPA Clearance Guidance Levelsa

 - by Grantee 

(Initial Clearance Failures) 

 Number of Number of Percentage of 

Grantee of Dwellings Dwellings with Dwellings with 

 Tested Failuresb Failuresb

Alameda County 167 52 31% 

Baltimore 393 124 32% 

Boston 68 38 56% 

California 103 17 17% 

Chicago 120 38 32% 

Cleveland 152 47 31% 

Massachusetts 134 61 46% 

Milwaukee 223 104 47% 

Minnesota 143 45 31% 

New Jersey 27 0 0% 

New York City 420 43 10% 

Rhode Island 160 15 9% 

Vermont 391 80 20% 

Wisconsin 181 37 20% 

All Grantees 2,682 701 26% 

aThe 1995 HUD/EPA Clearance Guidance Levels of 100 ug/ft2 -floors; 500 ug/ft2 -window sills; 

 and 800 ug/ft2 -window troughs were used as comparison values, regardless of clearance standards 

 used by a specific grantee. 

bA single failure of any component (floor, window sill, or window trough) constitutes a dwelling unit failure 

Data from: Form 19. 

Data as of: June 1, 2000 

Source of Data: UC Table 80-I
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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 Table 7-2: Number and Percentage of Dwellings with Initial 

 Post-Intervention Dust Lead Loadings Above 

 1995 HUD/EPA Clearance Guidance Levelsa - by Grantee and Sample Type 

(Initial Clearance Failures) 

Floor Window Sill Window Trough 

Grantee 

 Number of 

dwellings 

tested 

Dwellings 

with Initial 

failuresb

 (%)

Number of 

dwellings 

tested 

Dwellings 

with Initial 

failuresb (%)

Number of 

dwellings 

tested 

Dwellings 

with Initial 

failuresb (%)

Alameda County 167 25% 167 15% 110 5% 

Baltimore 392 27% 390 2% 387 5% 

Boston 68 56% 68 6% 67 7% 

California 103 9% 93 4% 47 6% 

Chicago 120 28% 117 8% 111 5% 

Cleveland 152 24% 152 9% 127 9% 

Massachusetts 134 42% 134 10% 133 7% 

Milwaukee 223 30% 223 13% 219 18% 

Minnesota 143 21% 141 11% 135 12% 

New Jersey 27 0% 25 0% 20 0% 

New York City 420 4% 415 1% 380 8% 

Rhode Island 160 8% 159 1% 158 1% 

Vermont 391 15% 384 4% 324 6% 

Wisconsin 179 16% 172 3% 168 5% 

All Grantees 2679 20% 2640 6% 2386 7% 

aThe 1995 HUD/EPA Clearance Guidance Levels of 100 ug/ft2 -floors; 500 ug/ft2 -window sills; and 

800 ug/ft2 -window troughs were used as comparison values, regardless of clearance standards used 

by a specific grantee 

bA single failure of a floor, window sill, or window trough wipe constitutes a dwelling unit failure for that 

component

Data from: Form 19. 

Data as of: June 1, 2000 

Source of Data: UC Table 081 & 082.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-9

The findings suggest that the likelihood of failing clearance on the initial attempt was partially 

influenced by factors related to the grantee. For example, across surfaces, Milwaukeeís 

dwellings were among those most likely to fail initial clearance dust tests, while Rhode Islandís 

dwellings were among those most likely to pass initial clearance dust tests. However, while 

failure rates for a grantee tended to be consistently high or consistently low across surfaces, there 

were some variations. Boston and Massachusetts had floor clearance failure rates that were more 

than twice the Evaluation average for floors, but their window sill and trough failure rates were 

close to the Evaluation averages. Conversely, Minnesotaís floor clearance failure rate was 

approximately equal to the Evaluation average for floors, but its window sill and trough rates 

were nearly double the Evaluation averages. Alameda Countyís window sill failure rates were 

almost three times the Evaluation average for sills, while its failure rates on other surfaces are 

close to the Evaluation average. New York Cityís floor and window sill clearance failure rates 

were one-fifth of their respective Evaluation averages, yet this granteeís window trough levels 

were close to the Evaluation average. 

Because the relative rates of failure were not always consistent across surfaces for a grantee, it 

does not necessarily follow that a broad grantee-related factor such as contractor experience or 

grantee oversight was a cause for the grantee-by-grantee variation. Other factors such as the 

choices of treatments conducted or the local housing conditions are likely candidates to explain 

the variation across grantees. The following sections explore the factors that were associated 

with initial clearance failures and initial clearance dust lead loadings. 

7.3.2.1 Results of Statistical Modeling: Clearance Failures. Five statistical analyses were 

developed exploring the factors that significantly affected the initial clearance dust lead failure 

rates. The analyses produced models that separately examined the factors influencing failure 

rates on 1) interior entry floors, 2) bare floors, 3) all floors, 4) window sills and 5) window 

troughs. The results presented here focus on the latter three models. The first two models offer 

additional insights into why dust lead loadings on floors failed. 

Failure rates for floors were calculated using 100 μg/ft2

 as a uniform threshold in order to avoid 

introducing grantee bias. 

7.3.2.1.1 Floors 

Factors that statistically significantly influenced floor clearance dust lead failures across the three 

floor analyses were: 

Pre-intervention dust lead loadings log-transformed (lower levels yielded fewer failures) 

 Pre-intervention paint lead loadings log-transformed (lower levels yielded fewer failures) 

 Occupancy status-pre-intervention (vacant dwellings yielded fewer failures) 

 Entry Height (dwellings on higher stories of building yielded fewer failures)

In addition to these factors, the interior lead hazard control strategy5

 had a significant effect on 

clearance failure rates for all floors and bare floors. These effects are described below. The 

treatment of exterior soil was significantly related to clearance failure rates on all floors and bare 

floors, with site treatments associated with lower clearance failure rates. However, neither 

 

5

 See Table 7-3 for strategy definitions. See Section 5.2 for a more detailed description of dwelling unit 

interventions. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-10

interior lead hazard control strategy nor site treatment was significantly related to failure rates on 

entry floors, after controlling for other factors. 

After controlling for factors listed above as well as the number of dwellings treated by the 

contractor, dwellings treated with lower level interior strategies were more likely to clear on the 

initial attempt than those treated with higher level interior strategies. At clearance, the failure rate 

on floors in dwelling units treated with Interior Strategy 02 or 03 was significantly different 

(lower) from those in dwellings units treated with Interior Strategies 04 and 05, when controlling 

for other factors (Table 7-4). Table 7-5 presents the actual failure rates for the dwellings in the all 

floors model. Initial clearance failure rates were more than twice as high when Interior Strategies 

04 or 05 were conducted than when Interior Strategies 02 or 03 were conducted. 

Table 7-3: Interior Strategy Code Definitions 

Strategy Definition 

Interior 01 No Action 

 02 Cleaning, Spot Paint Stabilization Only 

 03 Level 02 plus 

Complete Paint Stabilization, Floor Treatments 

 04 Level 03 plus 

Window Treatments 

 05 Level 04 plus 

Window Replacement, Wall Enclosure/Encapsulation 

 06 All Lead-Based Paint Enclosed, Encapsulated, or Removed 

(Meets Public Housing Abatement Standards) 

 07 All Lead-Based Paint Removed 

Glossary of Treatments

Encapsulation - The application of a covering or coating that acts as a barrier between lead-based paint and the 

environment, the durability of which relies on adhesion and which has an expected life of at least 20 years. 

Enclosure - The application of rigid, durable construction materials that are mechanically fastened to the substrate to 

act as a barrier between lead-based paint and the environment. 

Paint Stabilization - The process of repainting surfaces coated with lead-based paint, which includes the proper 

removal of deteriorated paint and priming. 

Paint Removal - The complete removal of lead-based paint by wet scraping, chemical stripping, or contained 

abrasives. 

Removal/Replacement - The removal/replacement of a building component that was coated with lead-based paint. 

Window Treatments - The process of eliminating lead-containing surfaces on windows that is subject to friction or 

impact through the removal of paint or enclosure of certain window components.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Table 7-4: Predicted Odds Ratios of a Clearance Failurea on All Floorsb 

by Interior Strategy 

Odds Ratio of Dwellings treated with Interior Strategies Listed Below 

Failing Clearance Compared to Interior Strategies at Left 

Interior 

Strategy 

02 03 04 05 06/07 

02 1.47 2.36** 2.20** 1.96* 

03 1.61** 1.50** 1.34 

04 0.93 0.83 

05 0.89 a

The 1995 HUD/EPA Clearance Guidance Level of 100 μg/ft2 ñfloors was used as a comparison value regardless of 

the clearance standard used by a specific grantee. 

b

All floors include entry and interior floor samples. 

**: Statistically Significant (p<0.05)

Data from: Form 19 

Data as of: June 1, 2000 

Source of Data: Model Results Associated with Clearance Models 

(Outcome: Clearance failure) 

Table 7-5: Number and Percent of Dwellings with 

Initial Post-Intervention Dust Lead Loadings Above 

1995 HUD/EPA Clearance Guidance Levelsa

 by Interior Strategy and Sample Type 

(Initial Clearance Failures) 

All Floorsb Interior Window Sills Window Troughs 

Strategy Number of 

Dwellings 

Tested 

Percent 

Failures 

(>100 μg/ft2

)

Number of 

Dwellings 

Tested 

Percent 

Failures 

(>500 μg/ft2)

Number of 

Dwellings 

Tested 

Percent 

Failures 

(>800 μg/ft2) 

02 218 11% 214 10% 190 12% 

03 336 13% 335 8% 305 8% 

04 422 24% 419 8% 402 10% 

05 1,436 23% 1,414 4% 1,252 5% 

06/07 185 11% 178 1% 169 10% 

All 2,597 20% 2,560 6% 2,318 7% 

a

The 1995 HUD/EPA Clearance Guidance Levels of 100 μg/ft2 ñfloors; 500 μg/ft2 ñwindow sills; and 800 μg/ft2 ñ

window troughs were used as comparison values regardless of the clearance standards used by a specific grantee. 

b

All floors include entry and interior floor samples.

Data from: Form 19 

Data as of: June 1, 2000 

Source of Data: Descriptive Statistics from Logistic Models
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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The effect of strategies on bare interior floor clearance failure rates was similar to all floors. 

Failure rates on entry floors were not significantly related to Interior Strategy. The findings of 

these analyses suggest that the effect of strategies on floor failure rates differ for entry and nonentry floors. 

7.3.2.1.2 Window Sills and Troughs 

Factors that influenced clearance dust lead failures on window sills and troughs were: 

Pre-intervention dust lead loadings log-transformed (lower levels yielded fewer failures)

Date of Sampling (March-April samples yielded most failures 

 /September-October samples yielded fewest failures) 

 Interior Strategy (effects described below)

Other factors associated with window sill clearance dust lead failures were (direction of 

relationship in parentheses): number of samples collected (+), window paint lead levels (+), 

occupancy (+), number of stories from entry (-). Other factors associated with window trough 

clearance failures were: door/trim paint lead levels (+) and number of dwellings treated by 

contractor (-). 

Table 7-5 presents the actual failure rates for the dwellings in the window sill and window trough 

models. The analysis of initial clearance failures on window sills and troughs identified a 

significant statistical effect of interior lead hazard control strategy on the probability of failure. 

Window sills in dwelling units treated with Interior Strategy 05 and 06/07 tended to have lower 

clearance failure rates than other Interior Strategies when controlling for other factors (Table 7-

6). The effect of interior interventions on window trough failure rates interacted with the preintervention trough dust lead loadings. Dwelling units treated with Interior Strategy 05 tended to 

have significantly different (lower) window trough failure rates than units treated with other 

interior interventions across the range of pre-intervention trough dust lead loadings. The failure 

rate on window troughs in dwelling units treated with Interior Strategy 02 tended to be 

significantly different (higher) from those in dwellings units treated with other interior strategies 

when pre-intervention dust lead loadings were high (e.g., at the 75th percentile). Table 7-6 

presents the odds ratios and results of the tests of significance contrasting Interior Strategies, for 

low, medium and high pre-intervention trough dust lead loadings (25th, Median and 75th

percentile, respectively). As pre-intervention trough dust lead loadings increase, dwellings 

treated with Interior Strategy 02 were predicted to have more clearance failures when compared 

to other Interior Strategies. All other odds ratios were relatively stable across the range of preintervention trough dust lead loadings. 

7.3.2.2 Results of Modeling: Clearance Dust Lead Loadings. Although the results of clearance 

testing generally focus on whether a household passes the clearance testing, an equally important 

element of the results is an assessment of the treatments/cleaning practicesí ability to reduce the 

dust lead loadings to levels as low as possible. A second set of five analytical models (i.e., all 

floors, entry floors, bare interior floors, window sills and window troughs) considered the factors 

influencing the initial clearance dust lead levels. The findings primarily focus on three of the 

models: all floors, window sills and window troughs. The dependent variable in the models was 

dust lead loading on a given sample type (e.g. all floors) as measured by individual dust samples. 

The factors influencing dust lead loadings were consistent with the factors identified in the 

models of clearance failures. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-13

Table 7-6: Predicted Odds Ratios of a Clearance Failurea on 

Window Sills and Troughs by Interior Strategy 

(with contrast results) 

Window Troughs 

By Pre-Intervention Dust Lead Loading 

Interior 

Strategies 

Contrasted 

Window Sills 

756 μg/ft2

Median: 

5,014 μg/ft2 28,567 μg/ft2

02 v.03 0.84 

p=0.606 

0.75 

p=0.536 

1.68 

p=0.161 

3.56 

p=0.003** 

02 v.04 1.28 

p=0.443 

0.79 

p=0.624 

1.49 

p=0.242 

2.69 

p=0.003** 

02 v. 05 2.24 

p=0.008** 

1.55 

p=0.344 

3.41 

p<0.001** 

7.08 

p<0.001** 

02 v. 06/07 5.95 

p=0.033** 

0.47 

p=0.185 

1.06 

p=0.897 

2.23 

p=0.099* 

03 v. 04 1.52 

p=0.181 

1.05 

p=0.903 

0.89 

p=0.707 

0.76 

p=0.479 

05 v. 02 0.45 

p=0.008** 

0.65 

p=0.344 

0.29 

p<0.001** 

0.14 

p=0.003** 

05 v. 03 0.37 

p<0.001** 

0.48 

p<0.032** 

0.49 

p<0.022** 

0.50 

p<0.095* 

05 v. 04 0.57 

p=0.023** 

0.51 

p=0.069* 

0.44 

p=0.002* 

0.38 

p<0.001** 

05 v. 06/07 2.66 

p=0.272 

0.30 

p=0.017** 

0.31 

p=0.003** 

0.31 

p=0.015** 

06/07 v. 02 0.17 

p=0.033** 

2.12 

p=0.185 

0.95 

p=0.897 

0.45 

p=0.099* 

06/07 v. 03 0.14 

p=0.015** 

1.59 

p=0.350 

1.59 

p=0.270 

1.60 

p=0.384 

06/07 v. 04 0.21 

p=0.067* 

1.67 

p=0.319 

1.41 

p=0.383 

1.21 

p=0.672 

06/07 v. 05 0.38 

p=0.272 

3.28 

p=0.017** 

3.23 

p=0.003** 

3.18 

p=0.015** a

The 1995 HUD/EPA Clearance Guidance Levels of 500 μg/ft2 ñwindow sills and 800 μg/ft2 ñwindow troughs were 

used as clearance standards by all grantees. 

**: Statistically Significant (p<0.05); *: Marginally Significant (p<0.10)

 

Data from: Form 19 

Data as of: June 1, 2000 

Source of Data: Model Results Associated with Clearance Models 

 (Outcome: Clearance Failure) 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-14

Factors associated with clearance dust lead loadings in the three main models were: 

Pre-intervention dust lead loadings log-trans. (lower levels yielded less dust lead at clr.) 

 Pre-intervention paint lead loadings log-trans. (lower levels yielded less dust lead at clr.) 

 Damage caused by a plumbing leak pre-intervention (yielded more dust lead at clr.) 

 Interior Strategy (effects described below)

The sampleís surface condition pre-intervention and the pre-intervention occupancy status of the 

dwelling were also significant factors in at least two of the three models. Surfaces in poorer 

condition were likely to have higher floor and window trough dust lead loadings at clearance, 

while occupied dwellings were likely to have higher floor and window sill dust lead loadings 

when controlling for other factors including pre-intervention dust lead loadings (Further 

interpretation of this latter finding is presented in Section 7.3.3.2). 

The completion of lead hazard control work on the site was associated with significantly 

different (lower) clearance window trough dust lead loadings. Exterior lead hazard control work 

was also associated with clearance dust lead loadings on entry floors, window sills and window 

troughs when exterior paint lead loadings were taken into consideration. As exterior paint lead 

levels increased in buildings where the exterior was treated, initial clearance dust lead loadings 

were significantly different (higher). Compared with dwellings without exterior treatments, 

exterior work was associated with larger declines in window dust lead loadings from preintervention to clearance only in buildings with lower exterior paint levels (i.e., < 1.9 mg/cm2

). 

On entry floors, exterior work was associated with smaller declines of dust lead loadings from 

pre-intervention to clearance in buildings with higher exterior paint levels (i.e., >3.0 mg/cm2). 

Although such findings may simply be artifacts of the close interrelationships between preintervention environmental lead levels, interior strategies and exterior work, the findings support 

future studies of exterior containment efficacy. 

7.3.2.2.1 Effect of Interior Strategy 

The descriptive statistics for dust lead loadings by Interior Strategy are presented on Table 7-7. 

Across the all floor, window sill and window trough models, interior lead hazard control strategy 

was a significant factor influencing the immediate post-intervention dust lead loadings. The 

effect of the interior strategies was influenced by (interacted with) the pre-intervention dust lead 

loadings for each of the surfaces (floors, sills and troughs). Figures 7-1 to 7-3 present the 

predicted values for immediate post-intervention dust lead loadings for specified Interior 

Strategies across the range of pre-intervention dust lead loadings, while holding all other 

significant factors constant at their mean values. Because the analyses examined individual 

samples (as opposed to dwelling unit averages used in other sections of this report), there were 

enough data to examine Interior Strategies 06 and 07 separately in the all floor and window sill 

models. Given the relatively small sample sizes of the Interior Strategy 07 data (1% or less of the 

samples), these findings are not discussed in further detail. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-15

Table 7-7: Geometric Mean Dust Lead Loadings 

at Pre-Intervention and Initial Clearance by Interior Strategy and Sample Type 

All Floorsa Interior Window Sills Window Troughs 

Strategy PreIntervention 

(μg/ft2

) 

Initial 

Clearance 

(μg/ft2) 

PreIntervention 

(μg/ft2) 

Initial 

Clearance 

(μg/ft2) 

PreIntervention 

(μg/ft2) 

Initial 

Clearance 

(μg/ft2) 

02 10 8 116 28 1,843 67 

03 16 14 120 40 990 75 

04 25 17 287 43 6,613 71 

05 47 11 385 16 5,032 29 

06 112 18 440 40 3,020 142 

07 4 3 18 6 - - 

All 29 12 271 23 3,722 44 

a

All floors include entry and interior floor samples. 

Data from: Form 19 

Data as of: June 1, 2000 

Source of Data: Descriptive Statistics Associated with Clearance Models 

 (Outcome: Continuous Variable) 

Within the interquartile range (i.e., between the 25th and 75th percentiles) of dust lead loadings 

for each surface type, certain patterns emerged across models. The dwellings treated with 

Interior Strategy 05 had significantly different (lower) dust lead loadings than dwellings treated 

with Interior Strategies 03, 04 and 06 across the interquartile range after adjusting for other 

factors. Clearance trough dust lead loadings in dwellings treated with Interior Strategy 05 were 

also significantly different (lower) than in dwellings treated with Interior Strategy 02 across all 

pre-intervention trough dust lead loadings. Dwellings treated with Interior Strategy 02 had 

clearance floor dust lead loadings that were lower than dwellings treated with Interior Strategies 

03, 04 and 06 when pre-intervention floor dust lead loadings were in the mid to low levels (e.g., 

at the median or 25th percentile) (Table 7-8). The results were similar on entries and bare floors.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Figure 7-2: Predicted Initial Clearance Window Sill Dust Lead Loading by PreIntervention Sill Dust Lead Loading and Interior Strategy

0

5

10

15

20

25

30

35

40

45

50

0 200 400 600 800 1000 1200

Pre-Intervention Sill Dust Lead Loading (μg/ft2

)

Predicted Initial Clearance Dust 

Lead Loading (mg/ft2

)

02

03

04

05

06

07

Figure 7-1: Predicted Initial Clearance All Floor Dust Lead 

Loading by Pre-Intervention Floor Dust Lead Loading and Interior 

Strategy

0

5

10

15

20

25

0 20 40 60 80 100

Pre-Intervention Floor Dust Lead Loading (μg/ft2

)

Predicted Initial Clearance Dust 

Lead Loading (mg/ft2

)

02

03

04

05

06

07
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Table 7-8: Statistical Significance of Results Comparing Predicted Clearance Dust Lead 

Loadings in Dwellings Treated with Interior Strategy 02 

with Other Interior Strategies by Pre-Intervention Dust Lead Loading 

(when Interior Strategy 02 associated with lower clearance loadings) 

All Floors 

Pre-Invention Dust Lead Loading 

Window Sills 

Pre-Invention Dust Lead Loading 

Interior 

Strategies 

Contrasted 25th

Percentile: 

7 μg/ft2

Median: 

22 μg/ft2

75th

Percentile: 

90 μg/ft2

25th

Percentile: 

60 μg/ft2

Median: 

221 μg/ft2

75th

Percentile: 

993 μg/ft2

02 v. 03 p<0.01** p<0.01** p=0.09* p<0.01** p<0.01** p=0.48 

02 v. 04 p<0.01** p<0.01** p=0.13 p<0.01** p=0.14 - 

02 v. 05 p=0.01** p=0.82 - - - - 

02 v. 06 p<0.01** p<0.01** p=0.07* p<0.01** p=0.15 - 

Note: ì-ì indicates that Interior Strategy 02 was associated with higher clearance loadings, although those 

associations were not necessarily significant. 

Data from: Form 19 

Data as of: June 1, 2000 

Source of Data: Model Results Associated with Clearance Models 

 (Outcome: Continuous Variable) 

Figure 7-3: Predicted Initial Clearance Window Trough Dust Lead Loading by PreIntervention Trough Dust Lead Loading and Interior Strategy

0

20

40

60

80

100

120

140

160

180

200

0 5000 10000 15000 20000 25000

Pre-Intervention Trough Dust Lead Loading (μg/ft2)

Predicted Initial Clearance Dust 

Lead Loading (mg/ft2

)

02

03

04

05

06
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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7.3.3 Discussion of Findings 

7.3.3.1 Treatment Effects. The findings of the Evaluation provide evidence that different interior 

lead hazard control strategies have significantly different effects on initial clearance failure rates 

and initial clearance dust lead loadings. Although a number of varying effects have been 

described in the previous sections, three observations stand out: 

1. Interior Strategy 05 out-performed other lower intensity strategies based on window dust lead 

loadings and failures at clearance. 

Dwellings treated with Interior Strategy 05, the strategy that included window abatement, are 

predicted to have lower initial clearance dust lead loadings and lower failure rates on both 

window sills and window troughs than those treated with any other interior strategy when all 

other conditions are equal. This finding may seem obvious, but it does demonstrate that windows 

painted with lead-based paint can be removed and replaced (or in some cases, stripped of paint) 

while keeping dust lead loadings low. Dwellings where Interior Strategy 05 was conducted had 

the lowest geometric mean window sill and window trough dust lead loadings at clearance: 16 

and 29 μg/ft2

, respectively. In addition, dwellings treated with Interior Strategy 05 generally had 

the lowest clearance failure rates of any strategy on window sills and window troughs: four and 

five percent, respectively. 

2. Low-intensity lead hazard control activities generally performed as well or better than other 

strategies based on floor dust lead loadings and failures at clearance. 

Dwellings treated with Interior Strategy 02, the strategy that generally included cleaning and 

possibly limited paint stabilization, had clearance floor dust lead loadings and failure rates at or 

below all other strategies. These results support the hypothesis that treatments that generate a 

limited amount of leaded dust can perform better at clearance than treatments that generate more 

leaded dust. Similarly, Interior Strategy 03, the strategy that generally included full paint 

stabilization and should have generated limited dust lead, had clearance failure rates at or below 

all other strategies on floors. 

However, clearance results do not necessarily predict future treatment success. Although pure 

cleaning treatments may perform well at clearance because little dust lead is generated during 

treatment and the focus of the contractor is on proper cleaning, such treatments are not expected 

to eliminate or reduce lead dust generation in the future. Chapter 8 provides information about 

the effectiveness of lead hazard control strategies on dust lead loadings one to three years after 

clearance. 

3. The relationship between average initial dust lead loadings at clearance and clearance failure 

rates varies by interior lead hazard control strategy. 

Although generally, the average initial dust lead loadings at clearance and clearance failure rates 

have a similar relationship for each Interior Strategy, there are exceptions and in at least two 

instances, the relationship substantially varied. Dwellings treated with Interior Strategy 05 had a 

geometric mean floor dust lead loading at clearance (11 μg/ft2

) that was lower than those for 

most other strategies, yet at least one floor sample was above 100 μg/ft2 in 23 percent of the 

dwellings, which was higher than most other strategies. Dwellings treated with Interior Strategy 

02 had a relatively low geometric mean window sill dust lead loading at clearance (28 μg/ft2

), yet 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-19

at least one sill sample was above 500 μg/ft2 in 10 percent of the dwellings, a relatively high 

percentage. 

This observation has major implications for interpreting these findings in light of the 2001 EPA 

clearance standards. Because the distribution of dust lead loadings appears to vary by Interior 

Strategy, it is difficult to reliably predict the percent of samples above a given level. In other 

words, knowing the average dust lead loading for a certain lead hazard control strategy does not 

mean that the failure rate at an alternative clearance standard can be reliably predicted. As a 

result, the relative effects of interior strategies on clearance failure rates may differ at the lower 

dust lead clearance standards (40, 250 and 400 μg/ft2

) issued by EPA in 2001 than those reported 

here. 

Finally, the Evaluation team recognizes an additional limitation for interpreting these results. 

There appear to be differences in clearance failure rates and clearance dust lead loadings by 

grantee. During preliminary analyses, ìGranteeî was included as a variable in the modeling and 

grantees were found to have significantly different effects on all clearance outcomes. After 

reviewing these findings, the Evaluation team determined that some effects attributed to 

ìGranteeî could have been influenced by other factors that are more generalizable on a national 

level. A principal concern was the strong correlation between certain grantees and the strategies 

they used (e.g., Milwaukee and low-level strategies, New York City and New Jersey and highlevel strategies). Out of concern that the ìGrantee effectî might dampen or hide the effects of 

variables such as lead hazard control strategies that could have more universal applicability, the 

ìGranteeî variable was excluded from these final models. 

Even so, the Evaluation team recognizes that the ìGrantee effectî may have been in part a valid 

effect. Potentially important factors that were captured by the Grantee variable in the analyses, 

such as the amount of grantee program oversight over contractor operations or the levels of 

exterior street dust lead in a community, are not accounted for by any other variable. Of concern 

is the possible unintended consequence of attributing to another variable, such as Interior 

Strategy, an effect that might have better been explained by the ìGrantee effect.î For example, 

as reported in Section 5.2.1, New York City contributed 89 percent of the Interior Strategy 06 

dwellings. In the preliminary analyses, dwellings treated with Interior Strategy 06 had the lowest 

predicted clearance dust lead loadings on floors, while dwellings treated in New York City had 

the highest predicted floor dust lead loadings among grantees. The final analyses, which did not 

consider the ìGrantee effectî indicated that dwellings treated with Interior Strategy 06 had the 

highest predicted floor dust lead loadings. When a grantee was closely related to a factor, such as 

New York City and Interior Strategy 06, it became difficult to determine whether the ìGrantee 

effectî was masking a poorly performing treatment or whether by not taking into account the 

ìGrantee effect,î the success of a strategy was discounted. Because no other grantee had such a 

close relationship with a lead hazard control strategy, the Evaluation team decided to exclude the 

ìGrantee effect.î However, caution should be used when drawing conclusions about the effects 

of Interior Strategy 06/07. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-20

7.3.3.2 Other Effects 

7.3.3.2.1 Surface Condition 

The effect of adding the condition of the wiped surface at clearance and the surface type 

(painted, unpainted and, for floors, carpeted) to the previously described clearance models was 

examined. The Evaluation team recognized that the surface condition is related to the interior 

strategy; higher-level strategies are more likely to create better surface conditions (Table 7-9). 

Therefore, if clearance surface condition had been included in the original models, the effects of 

strategy on dust lead could have been different. 

The effect of the condition of the wiped surface at clearance was significant in all analyses. The 

surfaces in better condition at clearance had lower clearance dust lead loadings and lower failure 

rates. The Evaluation team hypothesized that when surface condition at clearance was included 

in the models, the reductions in dust lead attributed to higher intensity strategies would be 

dampened because those effects would be attributed to the surface condition. Although this 

hypothesis proved true, the significant differences between Interior Strategies generally remained 

the same. There was one exception: when clearance surface condition was included, failure rates 

on entry floors were significantly related to Interior Strategy. The results suggest that when the 

impact of improving the surface condition is removed from the Interior Strategy effects, the other 

elements of interior lead hazard control had no significant difference on failure rates on entry 

floors. 

Table 7-9: Arithmetic Mean Surface Condition of Wipe Surfaces 

at Clearance by Interior Strategy 

Surface Interior Strategy 

02 03 04 05 06 

Entry 1.4 1.4 1.3 1.2 1.0 

Bare Floors 1.3 1.3 1.2 1.2 1.0 

All Floors 1.3 1.3 1.3 1.2 1.0 

Window Sill 1.3 1.2 1.2 1.2 1.0 

Window Trough 1.6 1.2 1.1 1.1 1.0 

Surface Condition: 1= Good, 2=Fair, 3=Poor 

Data from: Form 19 

Data as of: June 1, 2000 

Source of Data: Descriptive Statistics Associated with Clearance Models 

 (Outcome: Continuous Variable)
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-21

7.3.3.2.2 Pre-Intervention Occupancy 

Dwellings that were occupied prior to intervention were more likely to fail clearance dust testing. 

Overall, 28 percent of occupied dwellings failed versus 23 percent of vacant dwellings using a 

floor dust lead comparison value of 100 μg/ft2

. These results could offer support to the 

hypothesis that it is easier to treat and clean a dwelling unit that is vacant. Contractors did not 

have to work around occupants who did not relocate, nor did they have to work around 

belongings left by relocated households. However, support for this hypothesis is tempered by a 

supplemental examination of overall clearance failures (i.e., a failure on any surface) which 

found that when both the ìGrantee effectî and the occupancy of the dwelling were considered, 

initial clearance failure rates for vacant units and occupied units were not significantly different 

(p = 0.45). 

Model predicted floor and window sill clearance dust lead loadings in occupied dwellings were 

higher than those in vacant dwellings, after controlling for all other factors. However, it is 

important to recognize that pre-intervention dust lead loadings were among the factors controlled 

for in the clearance models. If pre-intervention dust lead loadings were the same in occupied and 

vacant units, then occupied dwellings were predicted to have higher dust lead loadings than 

vacant dwellings at clearance. Yet, as reported in Section 4.3.2, vacant dwellings had 

significantly higher dust lead loadings on floors and window sills at pre-intervention than 

occupied dwellings. The actual clearance dust lead loadings in occupied dwellings are not higher 

than in vacant dwellings. The geometric mean floor dust lead loading at clearance in occupied 

dwellings was 14 μg/ft2

 versus 15 μg/ft2 in vacant dwellings. The geometric mean window sill 

dust lead loading at clearance in occupied dwellings was 28 μg/ft2

 versus 34 μg/ft2 in vacant 

dwellings. 

The findings do not necessarily support a policy of preferentially selecting vacant dwellings for 

treatment. Waiting for occupied dwellings to become vacant and sit unoccupied for a period of 

time, as did units in the Evaluation, would be expected to result in higher pre-intervention dust 

lead loadings. While dust lead loadings declined from pre-intervention to clearance by a greater 

percentage in dwellings that were vacant, it is not apparent from the findings that treating a 

vacant dwelling would result in lower clearance dust lead levels than treating the same dwelling 

before it became vacant. 

7.3.3.3 Overview of Initial Clearance Results. Even though statistically significant differences 

in clearance dust lead loadings were identified between interior strategies, all interventions 

performed well. The maximum strategy specific geometric mean dust lead loadings for floors, 

window sills and troughs at initial clearance were: 18 μg/ft2

, 43 μg/ft2, and 142 μg/ft2, 

respectively (Table 7-7). These dust lead loadings were each at least 80 percent lower than the 

respective clearance standards (200, 500, and 800 μg/ft2 ) commonly used during the Evaluation. 

While some strategies performed better than others, no strategy could be considered ineffective 

at clearance. 

The focus of this section has been on the initial clearance dust lead loadings. Because dust lead 

loadings would have further declined following recleaning and retesting in the 20 percent of 

dwellings that failed to pass initial clearance, the dust lead loadings presented on Table 7-7 are 

higher than the final levels following all clearance activities. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-22

As discussed earlier, a principal measure of success at clearance is the creation of an 

environment where dust lead loadings are below applicable standards. This is achieved by 

conducting an intervention that creates as little lead dust as possible, properly contains the leaded 

dust that is created, and then removes as much of the original dust lead and newly generated dust 

lead as possible. This section examined differences in how well the interior strategies were 

successful in this task. However, clearance measurements cannot predict how well the different 

interior strategies will prevent the future generation of leaded dust. These outcomes are the focus 

of the analyses examined in Chapter 8. 

7.4 OCCUPANT PROTECTION

As discussed in Section 7.1, the HUD LHC Grant Program established the clearance testing 

requirements and other procedures to protect residents following treatments. At the same time, 

the HUD LHC Grant Program also had policies in place to protect residents while lead hazard 

control activities were underway. This section describes the measures that were taken to protect 

residents, their effectiveness as judged by resident satisfaction and by the incidence of blood lead 

increases of 5 μg/dL or more from pre-intervention testing to immediate post-intervention 

testing. 

7.4.1 Assessment Methods 

7.4.1.1 Methodology for Assessing Occupant Protection. Occupant protection was assessed using 

an occupant protection questionnaire. The purpose of the occupant protection questionnaire was 

to learn more about factors that determine the success or failure of the various occupant safety 

strategies used by grantees. Grantees were expected to administer the questionnaire to all 

households who were enrolled prior to intervention and who remained in the dwelling after 

intervention. The questionnaire determined whether families were temporarily relocated from the 

dwelling unit or were kept away from the work area but not relocated during the intervention. 

The questionnaire assessed the degree of, and reasons for, non-compliance of family members 

with grantee safety procedures (e.g., whether they returned to the home during the intervention 

and why). The Evaluation team also expected the information about occupant protection 

effectiveness to be an important modifier of change in blood lead levels after intervention. 

A total of 1,149 households participated in the occupant protection interviews. The Evaluation 

protocols called for the occupant protocol questions to be asked of an adult household member as 

soon as feasible after the completion of the lead hazard control intervention. Because the 

protocols required that this interview be conducted in person in each familyís home, the 

Evaluation team provided the grantee with the option of conducting it shortly after clearance 

(e.g., at the same time as the immediate post-intervention blood lead test) or during the 6-month 

follow-up inspection. In a small percentage of cases, the interviews were conducted during the 

12-month follow-up inspection. 

7.4.1.2 Methodology for Assessing Blood Lead Results. The HUD LHC Grant Program 

required grantees in Rounds One and Two to offer blood lead testing for children between the 

ages of six months and six years living in homes undergoing lead hazard control activities. Blood 

lead levels were to be used primarily to measure the safety and effectiveness of the lead hazard 

control activities that the grantees selected. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-23

The Evaluation team expected a substantial portion of the enrolled dwelling units to contain a 

child less than six years of age. Grantees often targeted homes for enrollment because the 

children inhabiting the homes had elevated blood lead levels or because the homes were in 

communities where children had an elevated risk of lead poisoning. Blood lead testing was to be 

conducted prior to intervention, immediately after intervention and 6 and 12 months after 

intervention. Parents decided whether their children would be tested for lead at each sampling 

phase. Neither the presence of a child nor the participation of the child in the Evaluation was a 

requirement for a dwelling unit to be eligible for LHC Grant funds. Section 3.1.1 provides details 

on the process used to obtain the participantís informed consent. 

The Evaluation protocols required the collection of the pre-intervention blood lead sample within 

six weeks before the lead hazard control intervention. This sample served as a baseline level for 

each child. The grantee was allowed to substitute a previously collected blood lead sample from 

a child for the pre-intervention sample as long as the grantee was able to verify the results 

through medical records. 

The protocols required the collection of the immediate post-intervention blood lead sample 

within six weeks after clearance was achieved. The second sample was used to help determine if 

a child was exposed to lead during the conduct of the intervention or occupant protection 

activities. The immediate post-intervention blood sample collection allowed Objective 8 of the 

study objectives to be fulfilled (i.e., to identify factors associated with blood lead increases equal 

to or greater than 5 μg/dL occurring between pre-intervention and post-intervention 

measurements). A 5 μg/dL change was selected as a level of concern because it is greater than 

the difference that might result from normal laboratory variation. 

A Generalized Estimating Equation (GEE) analysis was used to identify factors that were 

statistically significantly associated with the immediate post-intervention blood lead increases. 

Variables were considered significant at a p-value of 0.05. The variables tested in the analysis 

are listed on Exhibit 7-2 at the end of the chapter. 

7.4.2 Occupant Protection Findings 

Of the 1,548 households that were enrolled and participated in a household interview prior to the 

lead hazard control intervention, 1,082 households (70%) participated in an occupant protection 

interview after intervention. An additional 67 households were enrolled and completed an 

occupant protection intervention but did not complete the household interview prior to the 

intervention. Thus, a total of 1,149 occupant protection questionnaires were available for 

analysis. The households that completed the questionnaires resided in 1,133 dwelling units. The 

occupant protection interviews were generally conducted immediately after clearance (80%) 

although 207 (18%) were conducted approximately 6 months after clearance and 23 (2%) were 

conducted approximately 12 months after clearance. 

7.4.2.1 Relocated Households. For most households, occupant protection involved relocation 

from the dwelling unit for the total period of lead hazard control. Eight hundred nineteen (819) 6

households (71%) relocated during the lead hazard control work. Of the households who 

reported that they relocated, 776 (95%) relocated prior to the start of the work. 

 

6

 One household was known to have relocated based on other responses, but the specific point of relocation was not 

reported. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-24

Based on interview information, the median period of relocation was 13 days, with an 

interquartile range of 7 to 27 days. Twenty-two (22) percent of households (180) reported that 

someone in the household returned to the dwelling unit while the intervention was being 

conducted. The longer the relocation period, the less likely the family was to return (p<0.01). 

The return visits to the dwellings were often brief. Most households returning to their home spent 

less than one hour in the dwelling (125 households (69%)). Ten percent of returning households 

(18) spent less than eight hours in the dwelling. Most of the remaining 21 percent of households 

spent no more than four hours in the dwelling (34 households). 

For 112 of the 180 households that returned during relocation, a single person returned to the 

home. In 44 households, two people returned to the dwelling, while more than 2 people returned 

to the dwelling from the other 24 households. Ten percent of the households that returned during 

relocation included a child, including 20 children enrolled in the Evaluation. 

The primary reasons (besides ìotherî - 75 households) for returning home were to pick up 

personal belongings (77 households) and pick up mail (55 households). The primary reason 

given when households spent more than eight hours at the dwelling and the primary reason given 

when households returned with a child was ìthe work took longer than toldî (12 households). 

Over half of the households (438 (54%)) relocated outside the neighborhood. When the 

household remained in the neighborhood, 41 percent of the households remained in the same 

building in a different dwelling, while 12 percent of the households moved next door. The farther 

away a household relocated, the more likely a member was to return to the dwelling during 

intervention. Thirty percent of the households that relocated to a different neighborhood returned 

to the dwelling during intervention, while just five percent returned when they were relocated 

within the building. 

Sixty-one percent (496) of the households believed that they relocated to a ìlead-safeî home, 

while 21 percent (173) did not know whether the housing they moved to was ìlead-safe.î The 

Evaluation protocols did not define ìlead-safe,î so lead-safe status was based on the assessment 

of the respondent. 

7.4.2.2 Non-Relocated Households. Three hundred twenty-nine (329) households (29%) did not 

Three hundred relocate from the dwelling unit during lead hazard control work. As discussed in 

Section 7.2.1, HUD placed a number of requirements on grantees that chose not to relocate a 

household from a dwelling, and in general, it appeared that grantees complied with those 

requirements. Twenty-four percent of the households (78) stayed out of the dwelling unit during 

the work period but returned at night. Of the 2497

 households that remained in the dwelling unit 

during the day, 89 percent reported that they stayed out of the work area. Twenty-six households 

(8% of all non-relocated households) reported that they remained in the dwelling unit and 

entered or may have entered the work area. Half of these households reported that someone in 

the household entered the work area while work was in progress. 

Eighty percent of the 249 households that remained in the dwelling unit during the work reported 

that all dust and debris were cleaned up each day, and another five percent (13) were not sure. 

The remaining 38 households did not believe that dust and debris were completely cleaned up 

each day. 

 

7

 Two non-relocated households did not respond to the questions concerning activities during the work. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-25

7.4.2.3 Relationship of Relocation and Treatment Strategy. Homes where households did not 

relocate were expected to be treated with lower intensity treatments that would create little or no 

dust and debris. The grantees tended to follow this expectation. One hundred percent of the 

households that lived in abated units (Interior Strategies 06-07) were relocated and 83 percent of 

households that lived in dwellings treated with Interior Strategies 04-05 (window treatments or 

replacement) were relocated, while just 26 percent of households that lived in dwellings treated 

with Interior Strategies 01-02 (no interior work or cleaning/spot painting) were relocated. 

Although grantees tended to relocate families living in dwellings with higher intensity lead 

hazard control interventions, a substantial portion of the non-relocated households lived in 

homes with higher levels of treatment. One hundred thirty-two of the 329 non-relocated 

households (40%) lived in homes treated by Interior Strategy 04 or 05, while 94 such households 

(29%) lived in homes treated by Interior Strategy 03. The remaining8

 96 households (29%) that 

did not relocate lived in dwellings where no interior lead hazard control work was conducted (13 

households) or where Interior Strategy 02 (spot painting/cleaning) was done (83 households). 

7.4.2.4 General Occupant Findings. Overall, households felt that they were adequately protected 

by the occupant protection measures. Households that did not relocate had opinions about their 

protection that were not significantly different than relocated households. Overall, eighty-seven 

percent of interviewed households reported that they were adequately protected, while another 

seven percent were not sure or had no opinion.9

 Eighty-five percent of non-relocated households 

felt adequately protected compared to 88 percent of relocated households (Table 7-10). 

Households living in dwellings treated by Interior Strategy 01 or 02 felt more protected (94% 

adequately protected) than households living in homes treated by higher level interior strategies 

(86% adequately protected). This finding was found to be statistically significant in an analysis 

that controlled for the effects of grantee (p<0.01). 

Taken as a whole, the occupant protection findings suggest that grantees and households 

generally followed HUD guidance for occupant protection. Most households were relocated from 

the dwellings during the duration of the treatments and did not return to the worksite for 

intervention. When households were not relocated, treatments tended to be of a more limited 

nature. In addition, the vast majority (89%) of non-relocated households remained out of the 

work area and less than 20 households entered the work area while work was in progress. The 

sufficiency of the granteeís protective measures seems to be supported by respondentís opinions 

about the adequacy of the occupant protection. 

While the results were generally positive, six percent (59) of all households reported that they 

did not feel adequately protected. Over 20 percent of the households returned to the dwelling 

during intervention and another five percent did not relocate from the dwelling prior to the start 

of work. Data from the households that did not relocate or relocated late were combined and 

compared with data from households that fully relocated as part of the analysis of the effects of 

various factors on increases in childrenís blood lead levels. These findings are discussed in 

Section 7.4.3.1. 

 

8

 The interior strategy was not reported for seven of the dwellings where non-relocated households lived. 

9

 This analysis does not include responses from households living in New York City. The rationale for excluding 

these responses is found on Table 7-10. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-26

Table 7-10: Number and Percent of Households Who Reported that They Were Adequately 

Protected by Occupant Protection Activities by Interior Strategy 

(Households from New York City Excluded)a 

Number and Percent of Households Who Reported 

that They Were Adequately Protected 

Interior 

Strategy 

Total 

Householdsb

Relocated 

Households 

Non-Relocated Households All Households 

01/02 127 31 

94% 

89 

95% 

120 

94% 

03 105 38 

86% 

48 

79% 

86 

82% 

04 193 109 

87% 

53 

78% 

162 

84% 

05 565 441 

88% 

54 

84% 

495 

88% 

06/07 11 9 

82% 

- 9 

82% 

All 1,001 628 

88% 

244 

85% 

872 

87% a

One hundred, thirty two responses from New York City was excluded from this table because the responses of its 

residents deviated substantially from the other grantees. Seven percent of all respondents outside of New York City 

had no opinion or did not know whether they were adequately protected, while 34 percent of respondents in New 

York City had no opinion/did not know. The next highest rate of this response by any other grantee was 11 percent. 

Five percent of all respondents outside of New York City felt they were not adequately protected, while 28 percent 

of respondents in New York City felt that they were not. 

b

In addition to the 132 responses excluded from New York City, 12 households did not respond to this question and 

133 households lived in treated dwellings for which strategy forms were not approved.

Data from: Form 06 

Data as of: June 1, 2000 

Source of Data: NCLSH Table (Revision of McL-027 and McL-036) 

7.4.3 Findings for All Children with Blood Lead Increases of 5 μg/dL or More 

Eighty-one (81) of the 869 children (9.3%) who had both pre-intervention and immediate postintervention blood lead samples had blood lead increases equal to or greater than 5 μg/dL 

between the two measurements. Blood lead increases ranged from 5 to 25 μg/dL with an average 

increase of 8.4 μg/dL. The 81 children resided at ten grantee sites. Alameda County, the State of 

California and New York City reported no children with increases of 5 μg/dL or more. New 

Jersey did not report any children with serial blood lead tests. 

Upon request from the Evaluation team, the ten grantee sites where the 81 children resided 

provided additional information about possible reasons for these blood lead increases. A 

checklist of nine potential reasons was developed to assist grantees in this process. Table 7-11 

presents the grantee responses. Grantees were given the option of writing in additional reasons, 

so the table includes two additional responses that were frequently reported by the grantees: 

hand-to-mouth activity and unabated exterior lead source. Often more than one explanatory 

category was selected, yielding a total of 163 responses for the 81 children. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-27

Table 7-11: Grantee Responses to Survey of Potential Reasons for Blood Lead Increases 

Equal to or Greater than 5 μg/dL from Pre-Intervention to Immediate Post-Intervention 

Reason for Blood Lead Increase Frequency 

Expected Seasonal Variation 29 

Sources of Lead in Other House(s) 

(sitter, relative, neighborhood, etc.) 

28 

Household Activities1 21 

Hand-to-Mouth Activity (excessive) 14* 

Expected Increase Due to Childís Age 10 

Job Exposures of Household Member 7 

Unabated Exterior Lead Source 7* 

Activities in Neighborhood 

(demolition, industrial or other) 

1 

Use of Traditional or Folk Remedies or Food/Beverage 

Containers Containing Lead 

0 

Other 28 

Unknown 18 

*Responses written-in by grantees 

1

Household Activities include home repairs or other hobbies that involve the use or disturbance of lead. 

Data from: UC Survey of Grantees ñ Reasons by Blood Lead Increases 

Data as of: June 1, 2000 

Source of Data: UC Table 

To verify these responses, other data reported by the grantees were examined to determine their 

consistency with the responses. Responses were compared to available data related to the childís 

age, month of blood lead collection, neighborhood point sources of lead, and possible 

occupational or recreational exposures to lead. Most of the responses were consistent with the 

other available data. For example, childís age appeared to be a viable reason for each of the ten 

cases when grantees provided this response. 

Information provided by grantees, including responses noted in the ìotherî category, indicated 

that elevated blood lead levels in nine children (9%) may have been related to the lead hazard 

control work conducted: four cases in Minnesota, three cases in Massachusetts, and one case 

each in Vermont and Wisconsin. For each of these nine children, one of the following situations 

reportedly occurred: 

• the family did not relocate during the intervention, 

• the family was present during at least part of the intervention, or 

• one or more family members visited the home while the intervention was underway. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-28

7.4.3.1 Findings for Children Fitting Evaluation Criteria. As described in Section 7.4.1.2, the 

Evaluation team conducted a multivariate analysis of factors associated with increases in blood 

lead levels of 5 μg/dL or more. Prior to running this analysis, however, data for the 869 children 

having pre-intervention and immediate post-intervention blood lead samples were studied in 

order to identify the subset of children whose data met specific study requirements and therefore 

could be included in the analysis. The 869 children described above included 216 children who: 

• Lived in dwellings that were missing other pre- or immediate post-intervention data, 

• Did not fall within the Evaluation protocols for age eligibility (6 months to 72 months 

of ages at pre-intervention), 

• Did not fall within the blood sampling time restrictions of sixteen weeks prior to the 

start of the intervention to four weeks after work started.10

• Lived in dwellings that were treated with rarely conducted Interior Strategies (i.e., 01, 

06 or 07) 

Because these 216 children did not meet the basic study requirements or lived in dwellings 

where a Strategy effect would not be evident (i.e., because the Strategy was used in less than 10 

of the dwellings), they were ineligible for multivariate analyses of factors associated with 

increases in blood lead levels of 5 μg/dL or more. Among the children excluded were 12 children 

(6%) with blood lead increases of 5 μg/dL or more. This percentage was significantly different 

from the 11 percent of children (69) within the group of 653 children who met the Evaluation 

criteria (p=0.03). 

Unlike the other statistical analyses contained in this report, evidence of the dwelling passing 

clearance was not required for inclusion in this model. The Evaluation team determined that the 

power of the analysis could be adversely affected by limiting eligibility with the clearance 

requirement. Eight-one (81) children in the analysis, including 13 children (16%) with blood lead 

increases of 5 μg/dL or more, lived in dwellings that did not have evidence of clearance. 

Evidence of clearance was not a variable tested in the full logistic regression analysis of factors 

associated with blood lead increases, but when tested in a bivariate analysis, the percentage of 

children with 5 μg/dL or greater blood lead increases was not significantly different in the subset 

of dwellings that passed clearance than in the subset that did not have evidence of clearance 

(p=0.08). 

In the full logistic regression analysis, four factors were significantly associated with blood lead 

increases of 5 μg/dL or more: childís age at pre-intervention, female caregiverís education, 

general exterior building condition and season of blood sample collection (immediate postintervention). 

 

10 The time restriction is more lenient than was originally stated in the Evaluation protocols, which called for preintervention blood sampling to be conducted between 6 weeks prior to the intervention and the start of the 

intervention. In addition, time restrictions were removed from the immediate post-intervention sample. The 

Evaluation team believes that the original restrictions could be relaxed to expand the analysis population, without 

compromising the integrity of the analysis. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

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Table 7-12: Predicted Odds Ratios for a Child Having a Blood Lead Increase Equal to or 

Greater than 5 μg/dL for various Pre-Intervention Ages Compared to a Child of Median 

Pre-Intervention Age (40Months) and Predicted Probabilities of a Child Having a Blood 

Lead Increase Equal to or Greater than 5 μg/dL by Childís Age (Pre-Intervention) 

Childís Age (Months) Odds Ratio of a Child 

Having a Blood Lead 

Increase of 5 μg/dL or 

Morea

Predicted Probability of a Child 

Having a Blood Lead Increase of 5 

μg/dL or Moreb

6 17.13 34.0% 

12 4.89 12.8% 

18 2.14 6.0% 

24 1.31 3.8% 

30 1.04 3.0% 

36 0.98 2.9% 

42 1.02 3.0% 

48 1.06 3.1% 

54 1.02 3.0% 

60 0.83 2.4% 

66 0.53 1.6% 

72 0.25 0.7% a

Odds Ratio compared to a child of age 40 months, pre-intervention (median age child) 

b

Model predicted values based on child living in home with: 

1. no exterior deterioration (modal value for all children), 

2. a female caregiver with more than high school education, 

3. window paint lead loading at the GM (1.3 mg/cm2

) 

4. post-intervention blood lead collected April 1 

Data from: Forms 01, 04, 05, 09 and 10 

Data as of: June 1, 2000 

Source of Data: Model Results for Blood ìSpikeî Model (#77d) 

7.4.3.1.1 Childís Age at Pre-Intervention 

The youngest children in the Evaluation had the highest risk of a blood lead increase of 5 μg/dL 

or more. When compared to the median age child in the analysis (a 40-month old child), the odds 

ratio was above 2 through age 18 months and primarily above 1 through age 54 months. Table 7-

12 presents these odds ratios. The table also presents the predicted probabilities for children of 

different ages with average educational attainment by the female caregiver (12 years), and no 

exterior building components that were deteriorated. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-30

7.4.3.1.2 Female Caregiverís Education11

In the statistical model, years of education were examined as a categorical variable, after 

preliminary analysis of the unadjusted data suggests that the effect of education should be split 

between caregivers who received less than 12 years of education, those who received 12 years 

or more, and those where the level of caregivers education was unknown (17 children) Children 

with a female caregiver who received 12 or more years of education had a lower risk of a blood 

lead increase of 5 μg/dL or more than children with a female caregiver who received less than 12 

years of education. Sixteen percent of children whose female caregiver had less than a high 

school education had an increase of 5 μg/dL or more; just seven percent of children whose 

female caregiver had a high school education or more had such an increase. 

7.4.3.1.3 General Exterior Building Condition 

Exterior building condition, as defined by the number of exterior building components broken or 

obviously deteriorated prior to intervention, was examined as a continuous variable in the 

statistical model. A child living in a building with more components exhibiting exterior building 

deterioration was more likely to have blood lead increases of 5 μg/dL or more. A more detailed 

analysis of the unadjusted data suggests that the effect of the general exterior building condition 

may be dichotomous. Children living in a dwelling with at least one exterior components with 

obvious deterioration had a higher risk of having a blood lead increase than children living in 

dwellings with no exterior deterioration. Sixteen percent of children living in a dwelling with one 

or two exterior components with obvious deterioration had an increase of 5 μg/dL or more; just 

eight percent of children living in dwellings with no exterior deterioration had such an increase. 

7.4.3.1.4 Season 

The leading response on the grantee surveys (seasonal differences) was also a significant factor 

in the model. When blood lead samples were collected during early summer, the incidence of 

blood lead increases was greater. The odds of a child having a blood lead increase of 5 ug/dL or 

higher in the summer were 146% higher than in the spring or fall and 434% higher than in the 

winter. 

In a subsequent examination of the effect of season on the change in blood lead levels, children 

were more likely to have increases in blood lead levels of 5 μg/dL or more when tested between 

winter and spring and spring and summer than when tested between summer and fall (p=0.03 and 

p<0.01, respectively) (Table 7-13). Children tested between winter and spring and spring and 

summer were not significantly more likely to have an increase of 5 μg/dL or more than when 

tested between fall and winter: (p=0.49) and (p=0.27), respectively. 

 

11 The male caregiversí educational attainment was not examined because the data were frequently unavailable. 

Male caregivers were either not present or respondents did not provide these data on over half of the interview 

forms. Female caregivers were missing education data on just 5 percent of the forms. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-31

 

Table 7-13: Number and Percent of Children with Blood Lead Increase Equal to or 

Greater than 5 μg/dL between Pre-Intervention and Immediate Post-Intervention 

By Season 

Months when Immediate Post-Intervention Blood 

Lead Sample Collected 

Months when 

Pre-Intervention 

Blood Lead Sample 

Collected 

Number of Children 

Tested and Percent 

with Increase Equal to 

or Greater than 5 

μg/dL 

Winter 

(Jan-Mar) 

Spring 

(Apr-Jun) 

Summer 

(Jul-Sep) 

Fall 

(Oct-Dec) 

Winter 

(Jan-Mar) 

Number of Children 

Percent >= 5 μg/dL 

41 

12% 

112 

13% 

26 

15% 

1 

0% 

Spring 

(Apr-Jun) 

Number of Children 

Percent >= 5 μg/dL

8 

25% 

33 

15% 

116 

16% 

34 

9% 

Summer 

(Jul-Sep) 

Number of Children 

Percent >= 5 μg/dL

14 

0% 

0 

0% 

48 

13% 

97 

4% 

Fall 

(Oct-Dec) 

Number of Children 

Percent >= 5 μg/dL

76 

9% 

8 

0% 

2 

0% 

37 

0% 

All Number of Children 

Percent >= 5 μg/dL

139 

10% 

153 

13% 

192 

15% 

169 

4% 

Data from: Forms 05 and 09 

Data as of: June 1, 2000 

Source of Data: NCLSH Table (using Model #77d dataset) 

7.4.3.2 Discussion of Findings about Blood Lead Increases. In a previous study of children 

whose homes had undergone the ìtraditionalî form of lead abatement that was common in the 

early 1980s and earlier, over one-half of the children exhibited significant increases in blood lead 

probably related to the dust lead levels that also increased (Farfel 1990). In the current study, less 

than 10 percent of the children with reported pre-intervention and immediate post-intervention 

blood lead samples experienced an increase of 5 μg/dL or more between those sampling periods. 

The children in the Evaluation lived in at-risk housing and may have been exposed to untreated 

lead-hazards for a number of months between the time of the initial blood lead test and the 

beginning of the lead hazard control intervention. Furthermore, these children may have been 

exposed to lead outside of the housing environment being evaluated. Yet one cannot discount the 

fact that these children lived in dwellings that were undergoing interventions that potentially 

could have exposed them to additional hazards. 

The investigation suggests that on a case-by-case basis, some children may have been put at 

increased risk because of breakdowns in the occupant protection system. Grantees reported nine 

of the 81 children may have experienced increases in blood lead levels of 5 μg/dL or more 

because their family did not relocate, their family was present for at least part of the work period, 

or the family returned to the home. As individual cases, these reports cannot be discounted. Yet, 

overall, the statistical analysis did not find evidence that children living in households that either 

did not relocate or relocated for less than the full work period had a significantly different 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-32

likelihood of having a blood lead increase greater than or equal to 5 μg/dL than children living in 

households that fully relocated. 

This finding should not be misinterpreted to suggest that relocation was no more beneficial than 

not relocating, but instead suggests that the granteesí occupant protection decisions were 

appropriate. When grantees felt that households did not need to be relocated or could be partially 

relocated, the children were as protected (when measured by chance of blood lead increases) as 

when grantees felt that the households had to be relocated. 

The statistical model did not identify any interior strategy that had a significantly different effect 

on the likelihood of a child having an increase in blood lead levels of 5 μg/dL or more. Effects of 

Interior Strategy 02, 03, 04, and 05 were compared to each other. The lack of significant effects 

does not prove that the lead hazard control interventions did or did not result in an increased 

exposure risk, but the available data did not reveal that any single interior strategy was any more 

or less risky than the others. 

Finally, some limitations to the modeling may explain why results of investigation by grantees 

are not fully supported by the analysis of blood lead increases. Of the top five reasons reported 

by grantees, two (Childís Age and Season) were found to be significant in the model. The second 

most common reason identified by the grantees, exposure at other peopleís homes, was not a 

question asked of the families during any Evaluation questionnaires so it could not be tested. 

Two other responses, exposure to lead from home activities and exposure to lead from workrelated activities, were harder to characterize in the analyses. Responses on household 

questionnaires indicated that although enrolled households were involved with over two dozen 

different home- and work-related lead activities, generally less than five percent of households 

were involved in any one lead activity. For the analyses in this report, the Evaluation team 

defined the home and work activities by the number of home- or work-related lead activities 

reported by a household member under the assumption that more activities would increase a 

childís exposure. If this assumption is not correct, it is possible that an alternative method of 

measuring home- or work-related lead exposures could have been significantly related to the 

blood lead increases as the grantees suggested. 

7.5 SUMMARY OF THE OBSERVED OUTCOMES IMMEDIATELY POST-INTERVENTION

7.5.1 Clearance Dust Lead Findings 

Seventy-six percent of all 2,842 dwellings treated by grantees passed the initial clearance 

examination using the local dust lead standards applicable at the time. For the 2,682 dwelling 

units with data available to demonstrate final clearance, 80 percent passed the initial clearance 

examination. For the dwellings that initially failed, an average of 1.13 recleanings and follow-up 

clearance tests were required to achieve final clearance. The findings offer strong evidence that 

clearance was achievable on the first attempt for the vast majority of interventions. When 

dwellings failed initial clearance, final clearance was generally successful after only one 

additional recleaning and retest. 

The interventions were most successful reducing dust lead levels below the clearance standards 

on window sills (6% of dwellings failed based on at least one sample, 3% failed based on 

dwelling mean), followed by window troughs (7%, 6%) and floors (20%, 8%). The intensity of 

treatments as characterized by interior strategy had a significant effect on clearance failure rates 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-33

and immediate post-intervention dust lead loadings. The effects varied by the sample type. 

Interior Strategy 05, the strategy that included window replacement, was correlated with lower 

initial clearance dust lead loadings and lower failure rates on both window sills and window 

troughs than other interior strategies. Low-intensity lead hazard control activities (Interior 

Strategies 02 and 03) generally performed as well or better than other strategies based on floor 

dust lead loadings and failures. 

Any conclusions to be drawn from this reportís findings on clearance failures must be tempered 

somewhat by the fact that the clearance standards in place today are at least half those used 

during the Evaluation. The differential effects identified between interior strategies may not be 

the same using the new standards as those reported here. 

Even though statistically significant differences could be identified between interior strategies, 

on average, all strategies performed well. The highest geometric mean dust lead loadings by 

strategy for floors, window sills and troughs were: 19 μg/ft2

, 43 μg/ft2, and 76 μg/ft2, 

respectively. These dust lead loadings were each at least one-tenth of the respective clearance 

standards (200, 500, and 800 μg/ft2

) used during the Evaluation. Furthermore, the number of 

clearance retests was not related to the interior strategy applied. While some strategies performed 

better than others, no strategy could be considered ineffective at clearance. 

7.5.2 Occupant Protection 

Seventy-one percent of households were relocated during the intervention. Twenty-two percent 

of those households reported that they returned to the dwellings during intervention, although in 

most cases the return visits were less than one hour and did not include a child. Eighty-eight 

percent of the relocated households felt that they were adequately protected during the 

intervention. 

For the households that did not relocate, 92 percent of the households remained out of the work 

area during the time that work was being done. When households were not relocated, treatments 

tended to be of a more limited nature. Eighty percent of non-relocated households reported that 

all dust and debris were cleaned up each day. Eighty-five percent of non-relocated households 

felt that they were adequately protected during the intervention. 

Taken as a whole, the findings suggest that grantees followed HUD guidance and occupants 

were adequately protected. Analyses of childrenís blood lead levels immediately postintervention did not identify a difference in the probably that a child would experience a blood 

lead increase of 5 μg/dl or more from pre-intervention based on whether the child was relocated 

or not. The analyses also did not identify a differential effect by interior strategy. 

At the same time, the cases where households were possibly exposed to an on-going lead hazard 

control worksite are of concern. Approximately 10 percent of the children with pre-intervention 

and immediate post-intervention blood lead samples experienced an increase of 5 μg/dl or more 

between the sampling periods. Grantees reported that for 9 of the 81 children who experienced 

such blood lead increases, the increase may have been related to no family relocation, relocation 

during only part of the intervention, or a familyís return to the home during the intervention. 

Grantees must remain vigilant to offer households the necessary support and incentives to stay 

out of the work areas and be properly protected. 

 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-34

Exhibit 7-1: List of Variables Used in Clearance Dust Lead Models: 

Logistic Models of Clearance Failure and 

Nested Models of Dust Lead Loadings 

(Initial Clearance Dust Lead Data Used) 

Variables Used in Both Sets of Models 

Seasonality of Dust Sample Collected (at Clearance)

Paint Lead on Interior Doors/Trims (mg/cm2) (A.M. of log(XRF)) 

Paint Lead on Interior and Exterior Windows (mg/cm2

) (A.M. of log(XRF)) 

Paint Lead on Other Exterior Components (mg/cm2

) (A.M. of log(XRF)) 

Number of Interior Elements with Deterioration (Pre-Intervention) 

Roof Leak (Yes/No) 

Plumbing Leak (Yes/No) 

Number of Exterior Elements with Deterioration (Pre-Intervention) 

Entry Height in Stories 

Occupancy Status (Pre-Intervention) 

Interior LHC Strategy Level 

Exterior LHC Work (Yes/No) 

Site LHC Work (Yes/No) 

Number Units Abated by Each Contractor 

Interaction of No. Interior Elements with Deterioration and Interior LHC Strategy 

Interaction of No. Exterior Elements with Deterioration and Interior LHC Strategy 

Interaction of Paint Lead on Interior Doors/Trims and Interior LHC Strategy 

Interaction of Paint Lead on Interior and Exterior Windows and Interior LHC Strategy 

Interaction of Paint Lead on Exterior Other and Exterior LHC work 

Interaction of Surface Type and Condition of Entry Floor (Pre-Intervention) 4

Interaction of No. Interior Elements with Deterioration and Exterior LHC Work 

Variables Used Only in Nested (Loading) Models 

Dust Lead Loading on the Appropriate Surface1 (Pre-Intervention) 

Surface Condition for the Appropriate Surface1

 (Pre-Intervention) 

Surface Type (Pre-Intervention) 7 

Interaction of Surface Type and Condition for the Appropriate Surface (Pre-Intervention) 7

Indicator for Entry vs. Non-entry (Yes/No)2

Interaction of Dust Lead on the Appropriate Surface1

 (Pre-Intervention) and Interior LHC Strategy 

Interaction of Condition for the Appropriate Surface1

 (Pre-Intervention) and Interior LHC Strategy 

Variables Used Only in Secondary Analysis of Nested (Loading) Models 

Surface Condition for the Appropriate Surface1 (at Clearance) 

Surface Type (at Clearance) 7
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-35

Exhibit 7-1- continued: List of Variables Used in Clearance Dust Lead Models: 

Logistic Model of Clearance Failure and 

Nested Model of Dust Lead Loadings 

(Initial Clearance Dust Lead Data Used) 

Variables Used Only in Logistic (Failure) Models

Average Dust Lead Loading on the Appropriate Surface1

 (Pre-Intervention) 

Number Samples Taken on Surface (at Clearance) 

Average Surface Condition for the Appropriate Surface1

 (Pre-Intervention)3

Percent Painted for Appropriate Surface1,3

Surface Type (Hard, Painted or Carpet) of Entry Floor (Pre-Intervention)4

Percent of Painted Floors5

Percent of Hard Floors5

Percent of Carpeted Floors2

Percent of Painted Floors*Average Surface Condition5

 of Painted Floors 

Percent of Carpeted Floors* Average Surface Condition2 of Carpeted Floors 

Percent of Hard (Unpainted) Floors* Average Surface Condition5 of Hard (Unpainted) Floors 

Interaction of Average Surface Condition of Appropriate surface (Pre-Intervention) and Interior LHC 

Strategy1,8

Interaction of Average Dust Lead on the Appropriate Surface1

 (Pre-Intervention) and Interior LHC 

Strategy 

Variables Used Only in Secondary Analysis of Logistic (Failure) Models

Average Surface Condition for the Appropriate Surface1 (at Clearance)3,6

Surface Type (Hard, Painted or Carpet) of Entry Floor (at Clearance)4

1

For floor models (ìentryî, ìbare floorsî and ìall floorsî), floor surface used; 

For ìwindow sillî model, window sill surface used; 

For ìwindow troughî model, window trough surface used. 

2

Tested only in ìall floorsî model. 

3

Tested only in ìwindow sillî and ìwindow troughî models. 

4

Tested only in ìentry floorî model. 

5

Tested only in interior floor models (ìbare floorsî and ìall floorsî).

6

For ìall floorî model, two variables used ñ one for bare floors and one for carpets.

7

For ìall floorsî and entry floor models, surface type is carpeted, painted or bare. For window models and 

ìbare floorî model, surface type is painted or unpainted. 

8

 In all models except the ìentry floorî model. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-36

Exhibit 7-2: List of Variables Used in 

Generalized Estimating Equations (GEE)/Blood Spike Model 

Lead Hazards 

Pre-intervention Variables: 

Entryway Dust Lead Loading 

Surface Type of Entry Floor (Hard, Painted or Carpet) 

Surface Condition of Entry Floor 

Average Interior Floor Dust Lead Loading 

Percent of Painted Floors 

Percent of Hard Floors 

Percent of Carpeted Floors 

Percent of Painted Floors * Average Surface Condition 

Percent of Carpeted Floors * Average Surface Condition 

Percent of Hard Floors * Average Surface Condition 

Average Window Sill Dust Lead Loading 

Average Surface Condition of Window Sills 

Percent Painted Window Sills 

Average Window Trough Dust Lead Loading 

Average Surface Condition of Window Troughs 

Percent Painted Window Troughs 

Percent Dust Collected in Same Room for Each Component 

(Entries, Floors, Window Sills, Window Troughs) 

Average Paint Lead on Interior Doors/Trim (Mean of Log(XRF)) 

Average Paint Lead on Windows (Mean of Log(XRF)) 

Average Paint Lead on Exterior Components (Mean of Log(XRF)) 

Average Paint Condition of Interior Doors/Trims 

Average Paint Condition of Windows 

Average Paint Condition of Exterior Components 

Interaction between Paint Lead Loading and Paint Condition for Each Component 

 (Interior Doors/Trim, Windows, Exterior components) 

Interaction between % Dust Collected in Same Room and Dust Lead Loading (Pre-Intervention) for 

Each Component (Entries, Floors, Window Sills, Window Troughs) 

Interaction of Surface Type and Condition of Entry Floor 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-37

Exhibit 7-2-continued: List of Variables Used in 

Generalized Estimating Equations (GEE)/Blood Spike Model 

Immediate Post-intervention (Clearance) Variables: 

Entryway Dust Lead Loading 

Surface Type of Entry Floor (Hard, Painted or Carpet) 

Surface Condition of Entry Floor 

Average Interior Floor Dust Lead Loading 

Percent of Painted Floors 

Percent of Hard Floors 

Percent of Carpeted Floors 

Percent of Painted Floors *Average Surface Condition 

Percent of Carpeted Floors * Average Surface Condition 

Percent of Hard Floors * Average Surface Condition 

Average Window Sill Dust Lead Loading 

Average Window Trough Dust Lead Loading 

Average Surface Condition of Window Sills

Average Surface Condition of Window Troughs 

Interaction of Surface Type and Condition of Entry Floor 

Pre-Intervention Building/Dwelling Condition 

Number of Interior Elements with Deterioration 

Roof Leak (Yes/No) 

Plumbing Leak (Yes/No) 

Number of Exterior Elements with Deterioration 

Living Space of Dwelling at Pre-intervention (sq. ft) 

Entry Height in Stories 

Household Characteristics 

Pre-intervention Variables:

Was Home Renovated (Yes/No) 

Years of Education of Female Parent 

Presence of Cleaning Equipment (Percent) 

Frequency of Cleaning the House 

Frequency of Washing Exterior Window Sills 

Cleanliness of the Home 

(1=Appears clean, 2=Some evidence of cleaning, 3=No evidence of cleaning) 

Household Income ($) 

Number of Children Less than 6 Years 

Number of People between 6-18 Years 

Number of People in Home 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-38

Exhibit 7-2-continued: List of Variables Used in 

Generalized Estimating Equations (GEE)/Blood Spike Model

Immediate Post-intervention (Clearance) Variables: 

Cleanliness of the Home 

(1=Appears clean, 2=Some evidence of cleaning, 3=No evidence of cleaning) 

Frequency Change of Cleaning House (between Pre-Intervention-Clearance) 

Frequency Change of Washing Exterior Window Sills (between Pre-Intervention-Clearance) 

Child Characteristics (Pre-Intervention unless noted) 

Childís Blood Lead Level (Pre-Intervention) 

Childís Blood Lead Level (at Clearance) 

Indicator of Pre-Intervention Blood Samples Collected after Start of Intervention 

(Yes = after start of intervention, No = Up to 16 wks prior to start of intervention) 

Childís Age, Age Square, Age Cubic 

Race of Child 

Sex of Child 

Frequency of Putting Fingers into Mouth 

Frequency of Putting Toys into Mouth

Number of Hours Awake per Week 

Number of Hours Away from Home per Week 

Number of Hours inside the House per Week

Number of Hours outside the House per Week 

Parent Report Previous Child Lead Poisoning (Yes/No) 

Child Received WIC Benefit (Yes/No) 

Fully Relocated during Intervention (Yes/No) 

Interaction between Entry Dust Lead and Mouthing Behavior 

Interaction between Interior Floor Dust Lead and Mouthing Behavior 

Interaction between Mouthing Behavior and Age, Age2

, Age3 

Interaction between Blood Lead and Age, Age2

, Age3

Other Characteristics

Season of Blood Sample Collection (Pre-Intervention) 

Season of Blood Sample Collection (at Clearance) 

Season of Dust Sample Collection (Pre-Intervention) 

Season of Dust Sample Collection (at Clearance) 

Building Type (Single unit, 2-4 units, >4 units) 

House Age (by decade) 

Occupancy Status (Pre-Intervention) 

Ownership (1=Rented, 2=Owner occupied, 3=Other) 

Market Value 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 

 7-39

Exhibit 7-2-continued: List of Variables Used in 

Generalized Estimating Equations (GEE)/Blood Spike Model

Intervention (These variables only used in alternative models) 

Interior LHC Work (by Strategy) 

Exterior LHC Work (Yes/No) 

Site LHC Work (Yes/No) 

Interaction between Interior LHC Work and Exterior LHC Work 

Interaction between Interior LHC Work and Site LHC Work 

Interaction between Blood Lead and Interior Strategy 

Interaction between No. of Exterior Elements with Deterioration and Interior Strategy 

Interaction between No. of Interior Elements with Deterioration and Interior Strategy 

Interaction between Floor Dust Lead (Pre-Intervention) and Interior Strategy 

Interaction between Entry Dust Lead (Pre-Intervention) and Interior Strategy 

Interaction between Window Sill Dust Lead (Pre-Intervention) and Interior Strategy

Interaction between Window Trough Dust Lead (Pre-Intervention) and Interior Strategy 

Interaction of Average Floor Surface Condition (Pre-Intervention) and Interior Strategy 

Interaction between Average Surface Condition of Window Sills and Interior Strategy 

Interaction between Average Surface Condition of Window Troughs and Interior Strategy 

Interaction between Paint Lead on Interior Doors/Trim and Interior Strategy 

Interaction between Paint Lead on Windows and Interior Strategy 

Interaction between Paint Lead on Exterior Components and Exterior Strategy 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-1 

8.0 EFFECTS OF INTERVENTIONS ON DUST LEAD LOADINGS 

8.1 INTRODUCTION

The purpose of the HUD Lead Hazard Control Grant Program was to implement lead hazard 

control interventions that would reduce a childís exposure to lead-based paint, dust lead and 

possibly soil lead. Such reductions were expected to provide health benefits to children currently 

living in the treated dwellings (secondary prevention) and provide health benefits to very young 

children or children moving into or born into the dwelling in the future (primary prevention). 

Although a primary way to assess long-term treatment effects is to study post-intervention blood 

lead levels (see Chapter 9), it was recognized from the start of the Evaluation that confounding 

factors influencing childrenís blood lead levels would limit the use of blood lead as an outcome 

measure. In addition, while blood lead levels would be a lagging indicator of the effects of the 

intervention, the post-intervention dust lead loadings would serve as an immediate measure of 

how well interventions reduced lead exposures and maintained those levels. Thus, while 

improvements in childrenís health were the ultimate goal of the Lead Hazard Control Grant 

Program, the intermediate effects of interventions on post-intervention dust lead loadings proved 

to be the best measure of treatment effectiveness in the Evaluation. 

Previous studies have established that interior dust lead loadings are important predictors of a 

childís blood lead level. (Lanphear 1996a and 1998) Treatments that would limit the creation of 

leaded dust in the future as well as directly reduce levels of leaded dust in the childís 

environment were expected to have beneficial effects on the childís blood lead level. 

The lead hazard control interventions implemented through the Lead Hazard Control Grant 

Program were expected to have four main effects on dust lead loadings. 

(1) Interventions would generate varying levels of leaded dust depending on how and 

how much lead-based paint was disturbed during work; 

(2) Interventions would change surface conditions on the areas to be sampled that could 

influence the post-intervention ìcleanabilityî of the surfaces by both the contractors 

and by residents; 

(3) Interventions would require a final cleaning by the contractor that would reduce 

leaded dust and debris to levels that were at least below the clearance levels at 

immediate post-intervention; and 

(4) Interventions were expected to have varying long-term influences on the potential 

generation of leaded dust. 

 

The first three effects of interventions had an immediate influence on clearance dust lead 

loadings; those effects are discussed in Chapter 7. With respect to the fourth effect, treatments 

that abated lead through the removal of the lead-based paint either by removing the building 

component or the paint on the surface were expected to permanently prevent the generation of 

dust lead from that surface. Treatments that abated lead through the enclosure or encapsulation 

of lead-based paint were expected to prevent the generation of dust lead for at least 20 years (i.e., 

well beyond the duration of the evaluation). Treatments that made the lead-based paint intact 

were expected to stop dust lead from being generated for an undetermined period of time until 

the paint began to deteriorate. Finally, decisions to not treat lead-based painted surfaces that were 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-2 

intact or had only de minimus amounts of deterioration were expected to stop dust lead 

generation for an unknown period until the paint began to deteriorate. 

This chapter will explore the long-term effects of interventions on dust lead loadings. The 

grantees generally selected a mixture of interim control treatments and abatements on various 

interior and exterior building components. At a limited percentage of buildings, grantees also 

treated the lead-contaminated soil, most commonly with interim controls. The effect of the 

interim controls was expected to change with time; as the interim controls of lead hazards lost 

their effectiveness and lead-based paint deteriorated, dust lead loadings were expected to rise. 

The Evaluation team planned to assess this effect by measuring the rate of reaccumulation of the 

dust lead loadings (Objective 4) and determining the longevity of different intervention 

strategies. The study design also called for an examination of factors that influenced postintervention dust lead loadings (Objective 5) and the measurement of changes in dust lead 

loadings from pre-intervention to post-intervention (Objective 9). 

For many reasons, the assessment of the effects of the different intervention strategies on postintervention dust lead loadings turned out to be more complicated than originally expected. 

Grantees selected intervention strategies that were based on, among other factors, baseline 

environmental and building conditions. This presented a confounding relationship. Grantees that 

had more hazards in the dwellings they treated tended to select more intensive treatments, so that 

distinguishing the effects of interventions on post-intervention dust lead from the effects of 

baseline environmental conditions was hampered. Grantees also chose a mixture of intervention 

measures for the housing: applying a combination of strategies for housing components (e.g., 

replacing some windows and stabilizing paint on others). In addition, dust lead loadings did not 

always follow the expected pattern of declining at clearance and then rising at varying rates after 

clearance. For example, dust lead loadings on floors tended to decline further after clearance, not 

rise. As explained in Section 8.2, the methodology used to assess dust lead loadings in the study 

evolved as the constraints of the study became apparent, and hypotheses about changes in dust 

lead loadings were revised. 

Midway through the collection of data, preliminary post-intervention dust lead findings 

suggested that there were unique grantee effects that could not be explained by the available 

data. The Evaluation team hypothesized that soil lead and exterior dust lead might help explain 

some of the observed differences in dust lead loadings. With support from HUD, a study 

involving a special one-time collection of exterior dust and soil samples was performed by the 

University of Cincinnati on a subset of 500 buildings in the Evaluation. These data were 

analyzed to determine the pathways of exterior lead sources into dwellings and the magnitude of 

effects of the lead on interior dust lead. These findings are presented in Section 8.5. 

As explained in Section 8.6, examination of the relationship of treatment failures to dust lead 

loadings was not possible because the data on treatment failures was not considered to be of 

adequate quality. Instead, analyses of treatment failures are presented which offer inferential 

evidence of how the different treatment intensities may influence the observed dust lead 

outcomes. 

The assessment of effects of interventions on dust lead loadings focused on the impact of 

interventions at the dwelling unit level. The interior intervention strategies defined in Chapter 5 

were the primary focus of these comparative analyses (Table 8-2). These analyses also 

considered the effect of exterior and/or site work on the dust lead outcomes. In a separate set of 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-3 

analyses, the effects of individual lead hazard control treatments to specific housing components 

on dust lead loadings were also assessed (see Section 8.7). This assessment focused primarily on 

the difference in the intensity of window treatments (e.g., window replacement and window paint 

stabilization). 

8.2 METHODOLOGY

During the first two funding rounds of the HUD Lead Hazard Control Grant Program, dust lead 

testing was conducted prior to intervention, at clearance and six and twelve months after 

intervention. These collection times were called phases. Dust lead samples were collected from 

interior floors, window sills and window troughs (previously known as window wells). Interior 

dust lead loadings were used as a measure of the safety and effectiveness of the lead hazard 

control interventions that the grantees selected. 

8.2.1 Dust Collection Methodology 

The Evaluation protocols further defined the dust lead testing requirements. Dust lead samples 

were collected from floors at the interior entry to the dwelling, the childís playroom (or a living 

area), the kitchen, and the two youngest childrenís bedrooms during each sampling phase of the 

study. Floor dust lead samples were collected near the primary doorway to the room. Dust lead 

samples were also collected at each phase from window sills in the kitchen and youngest childís 

bedroom and from window troughs in the playroom and the next youngest childís bedroom. 

Because dust lead sampling is in practice a ìdisruptiveî sampling method that removes leaded 

dust from the surface, efforts were made to reduce the effect of sampling of a prior phase on the 

sampling of a later phase. Therefore at each successive sampling phase, samples were taken from 

half of the window sill and trough with the location of the sample alternating from phase to 

phase. Likewise, floor samples were taken from alternate sides of the doorway. 

The Evaluation protocols required the collection of the pre-intervention dust lead samples to 

occur within six weeks prior to the lead hazard control intervention1

. This sampling would serve 

as a baseline dust lead level for the dwelling. The specific locations of the windows and 

doorways that were sampled were recorded so that data collectors could return to a location 

adjacent to the same spot during subsequent sampling phases. The Massachusetts and Wisconsin 

grantees collected two pre-intervention dust lead samples from a majority of their dwellings. A 

second sample was collected either because the first sample was taken too early or because 

educational efforts of the grantee might have changed the baseline conditions of the dwelling. 

When two samples were collected, the pre-intervention dust sample that was closest to the 

intervention was used in the statistical analyses of the effectiveness of lead hazard controls. 

Samples collected at clearance were used to represent the immediate post-intervention dust lead 

loadings at the dwelling. As described in Chapter 7, multiple clearance dust lead sampling events 

were sometimes required when the dwelling did not pass clearance on the initial or subsequent 

attempts. Unlike Chapter 7, which focused on the initial clearance results, this chapter used the 

final clearance sampling results. 

 

1

 For statistical analysis, dust samples collected between 16 weeks before the start of intervention and 4 weeks after 

the start of intervention were accepted as eligible pre-intervention samples. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-4 

Dust lead samples were also collected at 6 and 12 months after the date of final clearance. When 

HUD approved the extension of the Evaluation, the protocols were amended to require additional 

dust lead samples to be collected two- and three years after the clearance date, for selected 

dwellings from grantees participating in the extension. 

Dust lead samples were most commonly collected using a standard dust wipe sampling 

procedure described both in the Evaluation protocols and subsequently in the 1995 HUD

Guidelines for the Evaluation and Control of Lead-Based Paint Hazards in Housing (HUD 

1995). All samples were collected by single-surface sampling; composite dust lead sampling was 

not permitted. 

Originally, the protocols called for wipe sampling to be conducted only on uncarpeted surfaces 

of the floor; wipe sampling on carpets was not approved. However, one year after the protocols 

were issued, and before most Evaluation data were collected, the Evaluation team notified 

grantees that dust wipe samples from carpeting were acceptable if the floor by the doorway was 

carpeted. The Evaluation protocols allowed, and originally encouraged, grantees to collect 

carpeted floor samples using the University of Cincinnati DVM vacuum sampling method (Que 

Hee 1985). However, only one grantee routinely collected vacuum samples. Because the number 

of vacuum sample results was limited and because vacuum sample results are not comparable to 

wipe sample results, vacuum sample results are not included in this report. 

Each grantee selected its own laboratory (or laboratories) to analyze the dust samples. Each 

laboratory was required to show evidence that it was proficient under the Environmental Lead 

Proficiency Analytical Testing Program. Laboratories were not required to be accredited under 

the EPA National Lead Laboratory Accreditation Program because the study began early in that 

programís existence and few laboratories were as yet recognized. Lead was measured by flame 

atomic absorption, graphite furnace atomic absorption spectrophotometry or inductively coupled 

plasma-atomic emission spectrometry. Grantees were required to submit double blind quality 

control samples provided through the Evaluation and blank samples at a specified rate. More 

details on QA/QC procedures for dust lead samples and the procedures for the substitution of 

dust lead values below the levels of detection are presented in Section 3.2. 

8.2.2 Objectives of Data Analysis Methodology 

As mentioned earlier the selection of intervention strategies was not made on a random basis and 

thus the distribution of pre-intervention conditions were not the same for each of the strategies. 

Since the impact of interventions frequently depends on the pre-intervention conditions, 

differences in pre-intervention must be taken into account in evaluating the impact of 

interventions on these three measures of intervention success. The Evaluation team considered 

three measures of intervention success: 

• dust lead loadings at a point in time after intervention, 

• changes (%) in dust lead loadings from baseline to a point in time after intervention, and 

• percent of dust lead loadings above a given level at a point in time after intervention. 

Each measure has advantages and disadvantages as an assessment tool. Before looking at the 

specific findings of the study, the relative benefits and drawbacks of each of the measures are 

first presented. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-5 

8.2.2.1 Post-Intervention Dust Lead Loadings as a Measure of Effectiveness. One measure of 

effectiveness tested whether the dust lead loadings at a point in time after intervention differed 

by the intervention strategy. Ultimately, the risk to the children is based on the amount of lead to 

which they are exposed in their residence. If, one year after treatment, the floor dust lead 

loadings associated with one strategy are significantly higher than the loadings associated with a 

second strategy other things being equal, then arguably the first strategy was less effective than 

the second. Similarly, if a year after intervention, there is no significant difference between the 

intervention strategies, then the interventions may be considered equally effective. 

8.2.2.2 Changes (%) from Pre-Intervention to Post-Intervention Dust Lead Loadings as a 

Measure of Effectiveness. A second measure of effectiveness tested whether the percent change 

in dust lead loadings from baseline to a point in time after intervention differed by the 

intervention strategy. This measure has a potential advantage over the dust lead loading measure 

because it reduces the possibility of attributing success to an intervention when the preintervention conditions were a more likely cause. For example, if a particular strategy yielded an 

average post-intervention dust lead loading that was not significantly different from preintervention, then this strategy appears ineffective, regardless of its comparative postintervention loading. 

8.2.2.3 Percent of Dwellings with Dust Lead Loadings Above a Given Level as a 

Measure of Effectiveness. A third measure of effectiveness tested whether the percentage of 

dwellings with a maximum dust lead loading above a given level at a point in time after 

intervention differed by the intervention strategy. The previous measures provide information 

about the relative differences in the effects of interventions, but they may not answer the 

practical question: did the different interventions achieve levels that might be considered safe? 

The post-intervention dust lead loadings associated with one strategy might be significantly 

higher than all of the other strategies, but if few dwellings for any strategy were above the 

selected level, then all strategies would appear to meet a minimum criteria for effectiveness. This 

measure examined the actual outcomes and compared those outcomes across strategies. 

Because the standards of lead safety changed since the Evaluation data were collected, this 

measure is not as easily interpretable as it once might have been. For example, window sill dust 

lead loadings should be less than 250 μg/ft2 under current standards, but because the sills were 

only required to clear at 500 μg/ft2 during the Evaluation period, it may be unfair to suggest that 

interventions could not achieve and maintain the current standard. As a result, both levels were 

examined. Likewise, the floor standard has changed from 200 to 100 to 40 μg/ft2 since the 

Evaluation began. The association between the interior strategies performed and the probability 

that floor dust lead results in those dwellings were under the levels of 100 or 40 μg/ft2 is 

presented in this report. Even though most grantees cleared at 200 μg/ft2

, the 1990 clearance 

standard specified in the HUD Grant agreements, this level was not examined because so few 

dwellings exceeded this level one-year post-intervention. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-6 

8.2.2.4 Discussion of the Use of these Measures. The choice of a treatment intervention was 

often largely dependent on the pre-intervention conditions of the dwelling and the funds 

available. During field visits, the Evaluation team observed that dwellings with multiple lead 

hazards and building components in poor condition were generally judged to need substantial 

lead interventions to achieve clearance. Therefore, lower intensity strategies were less commonly 

applied to dwellings that had many lead hazards, and were instead generally used in dwellings 

with lower dust lead loadings on floors and window sills. Conversely, grantees tended to use 

higher intensity strategies (i.e., those that included window replacement) in dwellings that had 

higher pre-intervention dust lead loadings. However, such higher intensity strategies were also 

used in dwellings with a limited number of lead hazards. Grantees may have determined that 

leaded components that were currently maintained might not be maintained in the future, so 

abatement was appropriate. Alternatively, grantees may have been required by local laws or local 

standards of care to abate leaded surfaces regardless of their condition. 

As a result of the choices that grantees made, this Evaluation was able to look at the different 

effects of interventions when dwellings are in relatively good or fair condition compared to other 

older, grant eligible properties. The Evaluation had less power to examine the comparative 

effects of low intensity strategies in dwellings in relatively poor condition because such 

treatments were so rarely conducted. 

8.2.3 Statistical Methodology 

The 2,682 dwelling units that had dust samples collected at clearance and that had dust lead 

loadings below the grantee-specific clearance criteria were initially eligible for the statistical 

analyses on the effects of interventions on dust lead loadings through one-year post-intervention. 

Of the 2,682 dwellings that had evidence of clearance, 1,602 (60%) had pre-intervention and 

one-year post-intervention dust lead results available for all four dust lead sampling surfaces of 

interest (entry floors, interior floors, window sills and window troughs). Of the 826 dwellings 

enrolled in the extended Evaluation, 744 had evidence of passing clearance and were initially 

eligible for two-year and three-year post-intervention analyses. Of these 744 dwellings, 452 

(61%) had pre-intervention and three-year post-intervention dust lead results available for all 

four dust lead sampling surfaces of interest. 

Dust lead loadings were generally analyzed as the dwelling unit average of each type of 

component sampled (floors, window sills and window troughs). After preliminary analyses, an 

exception was made for floors. Entry floors were analyzed separately from other interior floor 

results because entry floor loadings were consistently higher than those of other interior floors 

and were likely indicative of the pathway of leaded dust from the building exterior or common 

areas into the dwelling.2

 On average, the interior floor result was the arithmetic mean of three 

samples, the window sill result was the mean of two samples and the window trough result 

represented a single sample3

. 

 

2

 Carpeted floors and painted floors were both found to have significantly different dust lead loadings than 

uncarpeted and unpainted floors, but because they did not represent unique pathways, they were not treated 

separately. A variable for floor type was examined in all models with interior floor dust lead as an outcome measure. 

3

 In less than a third of the dwellings, a second bedroom was sampled; thus, only three interior floors and one 

window trough sample was available for a majority of the dwellings. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-7 

Three principal methods of statistical modeling were employed to examine variables influencing 

post-intervention dust lead loadings. Repeat measures (RM) modeling was used to assess the 

trends in dust lead loadings across sampling phases. Multiple regression methods were used to 

investigate factors that influence post-intervention dust lead loadings. Structural equation models 

(SEMs) were fit to determine pathways and predictors of dust lead measures as well as examine 

how the interventions changed the pathways found in the pre-intervention SEM model. 

The SAS procedure PROC SYSLIN was used to run the SEM models and PROC MIXED was 

used to run the multiple regression and RM models. All lead variables (i.e., dust lead and paint 

lead) were transformed to their natural logarithm to normalize their statistical distributions. All 

modeling is based on the log of the household arithmetic mean dust lead loading and tables 

present the geometric means of the appropriate groups of household arithmetic means. Volume I 

of the Compendium presents a detailed explanation of how each model was developed and run. 

Summaries are provided below for the repeated measures models, multiple regression models, 

and the SEM models. 

8.2.3.1 Repeated Measures Models. The RM models are employed to analyze multiple phases of 

dust results per dwelling. The models examined trends in post-intervention dust lead loadings 

from clearance onward. The RM models analyzed entry floor, interior floor, window sill, and 

window trough dust lead outcomes at final clearance, six-months and one-year post-intervention 

for dwellings in the base Evaluation. The RM models also analyzed entry, interior floor, window 

sill, and window trough dust lead outcomes at clearance, six-months, one-, two- and three-years 

post-intervention for dwellings in the extended Evaluation. Overall four base Evaluation and four 

extended Evaluation RM models were run. Phase, interior strategy and interaction of phase and 

interior strategy were entered as possible predictors of post-intervention dust lead loading. A 

backward elimination of insignificant independent variables (p>0.05) was performed; the interior 

strategy was retained in each model regardless of statistical significance to allow for a test of its 

effects in the final model. The dependent variable in each RM model is the log of the household 

arithmetic mean dust lead loading for the sample type. 

8.2.3.2 Multiple Regression Models. Multiple regression models were used to explore the 

predictors of dust lead loading at one post-intervention time. Multivariate models analyzed entry, 

interior floor, window sill, and window trough dust lead outcomes at one-year for dwellings in 

the base Evaluation and three years for dwellings in the extended evaluation. Possible predictors 

included environmental measures and housing characteristics and conditions. A backward 

elimination of insignificant independent variables (p>0.05) was performed; the interior strategy 

was retained in each model regardless of statistical significance to allow for a test of its effects in 

the final model. The dependent variable in each multiple regression model is the log of the 

household arithmetic mean dust lead loading for the sample type. 

Dwellings were eligible for the base Evaluation dataset if they cleared and had pre-intervention 

and one-year post-intervention dust lead data from all four sample types (entry floor, interior 

floors, window sills and window troughs). Dwellings were also required to have complete data 

for all the variables identified in Exhibit 8-1 for the four one-year post-intervention multiple 

regression models for inclusion. Similar rules applied for the extended Evaluation dataset. 

8.2.3.3 Post-Intervention Structural Equations Models. A Structural Equations Model (SEM) is a 

means of estimating direct and indirect effects within or on a set of interrelated variables. The 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-8 

effects of environmental and demographic data on entry floor, interior floor, window sill and 

window trough dust lead loading was assessed. The relationships between dust lead loadings on 

the four sample types was also explored. A pre-intervention dust SEM was developed to 

establish the baseline pathways of lead through the home environment. The predictors of the preintervention outcomes established in the pre-intervention model were included as predictors (see 

section 8.4.3.1) of pre-intervention outcomes in the post-intervention model. No step-wise 

inclusion or elimination of pathways was performed for pre-intervention outcomes. All variables 

specified in Exhibit 8-1 were included as possible predictors of post-intervention outcomes. 

Backward elimination of insignificant predictors of the post-intervention outcomes was 

performed, followed by forward inclusion steps to re-enter, as needed, previously excluded 

pathways. The variable interior lead hazard control strategy was forced into the one year postintervention SEM model. However, if interior strategy was not a significant variable, it was not 

included in the final output figures. 

8.3 EFFECTIVENESS OF ALL INTERVENTIONS ON LONGITUDINAL DUST LEAD LOADINGS

This section presents information on the overall impact of the HUD LHC Grant Program on dust 

lead loadings post-intervention as measured by unadjusted results. One set of descriptive 

statistics is presented for the dwellings that had dust lead results for all four dust lead sampling 

surfaces of interest (entry floors, interior floors, window sills and window troughs) at both preintervention and one-year post-intervention and met the statistical model requirements for the 

one-year multiple regression analyses. A second set of descriptive statistics is presented for the 

dwellings that had dust lead results available on all four sampling locations at both preintervention and three years post-intervention and met the statistical model requirements for the 

three-year multiple regression analyses. These same datasets were used for the analyses of 

specific intervention effects discussed in Section 8.4 (with the exception of the SEM models). 

8.3.1 Dwellings Meeting the Requirements in the Base Evaluation 

The 1,034 dwellings available in this dataset were not a random sample of dwellings from the 

whole population, but were dependent on the willingness of residents and owners to participate 

in the longitudinal study as well as availability of data for all sampling locations in dwellings. 

Certain grantees and certain interventions were more likely to have a greater percentage of the 

dwellings in the dataset (Table 8-1). 

The data in the one-year post-intervention dust lead analysis dataset also had somewhat different 

housing characteristics than the dwellings in the clearance dataset. Twenty-five percent were 

owner-occupied as compared to 20 percent in the clearance dataset. The dwellings were more 

likely to be in single-family buildings (41% v. 31%) and less likely to be in buildings with more 

than four units (21% v. 29%). 

The overall dust lead findings were heavily influenced by dust lead results from dwellings 

treated with Interior Strategy 05 (see Table 8-2 for strategy definitions).4

 Dwellings treated with 

this strategy contributed 65 percent of the dwellings in the one-year longitudinal dataset 

 

4 See Section 5.2 for a more detailed description of dwelling unit interventions. Effects of Interior Strategy 01 (No 

Interior Work) are not presented in this chapter because less than 20 dwellings were treated with these interventions. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-9 

(compared with 55 percent in the clearance dataset). The data would have been even more 

heavily weighted toward higher intensity treatments, except that the reduction of dwellings from 

New York City dropped the percentage of results from Interior Strategy 06/07 dwellings from 

seven percent in the clearance dataset to three percent in the one-year post-intervention dataset. 

8.3.2 Dwellings Meeting the Requirements in the Extended Evaluation 

Like the base Evaluation dataset, the 278 dwellings available in the extended Evaluation dataset 

were not a random sample but were dependent on resident and owner participation, availability 

of needed data, and the grantees that participated in the extended Evaluation. In general, just 

over one quarter of the dwellings that had data available for the analysis of the base Evaluation 

dust lead data also had data available in the extended Evaluation (Table 8-1). With just 744 

dwellings with evidence of clearance funded for participation in the extended Evaluation, these 

278 dwellings include 37 percent of the available homes. 

The three-year post-intervention dust lead dataset contained dwellings that were more likely to 

be owner-occupied and in single-family dwellings than those in the clearance dataset. Thirtyfour percent were owner-occupied as compared to 20 percent in the clearance dataset. Fifty-three 

percent of dwellings were in single-family buildings (v. 31%) and just six percent were in 

buildings with more than four units (v. 29%). Dwellings treated with Interior Strategies 04 and 

05 accounted for 21 and 63 percent, respectively, of the dwellings in extended Evaluation dust 

lead dataset (v. 16 and 55% in the clearance dataset). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-10 

Table 8-1: Number of Dwellings that Cleared and Number of Dwellings in One-Year and 

Three-Year Dust Lead Analysis Datasets by Grantee 

Grantee Number of Dwellings 

Cleared 

Number of Dwellings in 

One-Year Dataseta

Number of Dwellings in 

Three-Year Datasetb

Alameda County 167 (6%) 6 (<1%) 1 (<1%) 

Baltimore 393 (15%) 244 (24%) 68 (24%) 

Boston 68 (3%) 36 (3%) 33 (12%) 

California 103 (4%) 1 (<1%) 5 (2%) 

Chicago 120 (4%) 84(8%) - 

Cleveland 152 (6%) 58 (6%) - 

Massachusetts 134 (5%) 84 (8%) - 

Milwaukee 223 (8%) 93 (9%) 59 (21%) 

Minnesota 143 (5%) 66 (6%) 41 (15%) 

New Jersey 27 (1%) 1 (<1%) - 

New York City 420 (16%) 132 (13%) - 

Rhode Island 160 (6%) 106 (10%) 26 (9%) 

Vermont 391 (15%) 85 (8%) 27 (10%) 

Wisconsin 181 (7%) 80 (8%) 18 (6%) 

All Grantees 2,682 1,034 278 

a

Dwellings were eligible for the base Evaluation dataset if they cleared and had pre-intervention 

and one-year post-intervention dust lead data from all four sample types (entry floors, interior 

floors, window sills and window troughs). Dwellings were also required to have all the variables 

listed in Exhibit 8-1 for the four one-year post-intervention multiple regression models for 

inclusion. 

b

Dwellings were eligible for the extended Evaluation dataset if they cleared and had preintervention and three-year post-intervention dust lead data from all four sample types (entry 

floors, interior floors, window sills and window troughs). Dwellings were also required to have 

all the variables listed in Exhibit 8-1 for the four three-year post-intervention multiple regression 

models for inclusion. 

NOTE: Alameda County, California and New Jersey had less than 5 percent of their cleared 

dwellings in either data set. Reasons for loss of one-year post-intervention data are presented 

below (as well as % of cleared units in each category): 

 Ala.Co. Calif. N.J. Others 

 Pre- or Post-Int. Dust Not Collected/Eligible* 36 (22%) 47 (46%) 2 ( 7%) 566 (24%) 

 Pre-Intervention Trough Samples Not Collected 54 (32%) 28 (27%) 23 (85%) 123 ( 5%) 

 Pre-Int. Entry Samples Not Collected/Eligible** 30 (18%) 0 ( 0%) 0 ( 0%) 30 ( 1%) 

 Other Dust Samples Missing/Not Eligible 24 (14%) 22 (21%) 1 ( 4%) 105 ( 4%) 

 Other Required Data Missing 17 (10%) 5 ( 5%) 0 ( 0%) 535 (22%) 

Eligible 6 ( 4%) 1 ( 1%) 1 ( 4%) 1,026 (43%) 

 

 *When the lab quality for a set of dust lead samples did not meet study criteria, the dust lead samples were ineligible. 

 **Alameda County had a higher percentage of ineligible entry floor samples because the samples were taken from a small area 

(< 6î on a side) indicating that they were collected from the threshold instead of inside the doorway. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-11 

Table 8-2: Interior Strategy Code Definitions 

Strategy Definition 

Interior 01 No Action 

 02 Cleaning, Spot Paint Stabilization Only 

 03 Level 02 plus 

Complete Paint Stabilization, Floor Treatments 

 04 Level 03 plus 

Window Treatments 

 05 Level 04 plus 

Window Replacement, Wall Enclosure/Encapsulation 

 06 All Lead-Based Paint Enclosed, Encapsulated, or Removed 

(Meets Public Housing Abatement Standards) 

 07 All Lead-Based Paint Removed 

Glossary of Treatments

Encapsulation - The application of a covering or coating that acts as a barrier between lead-based paint and the 

environment, the durability of which relies on adhesion and which has an expected life of at least 20 years. 

Enclosure - The application of rigid, durable construction materials that are mechanically fastened to the substrate to 

act as a barrier between lead-based paint and the environment. 

Paint Stabilization - The process of repainting surfaces coated with lead-based paint, which includes the proper 

removal of deteriorated paint and priming. 

Paint Removal - The complete removal of lead-based paint by wet scraping, chemical stripping, or contained 

abrasives. 

Removal/Replacement - The removal/replacement of a building component that was coated with lead-based paint. 

Window Treatments - The process of eliminating lead-containing surfaces on windows that are subject to friction or 

impact through the removal of paint or enclosure of certain window components.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-12 

8.3.3 Floor Dust Lead Findings 

• One-year post-intervention, the geometric mean interior floor dust lead loading was 12 

μg/ft2. This represents a 70 percent decline from the pre-intervention levels (Table 8-

3/Figure 8-1). 

• One-year post-intervention, 18 percent of the dwellings had an interior floor dust lead 

loading at or above 100 μg/ft2

. This represents a 55 percent decline from the preintervention percentage (40%). Using the current standard of 40 μg/ft2

, the percentage of 

dwellings with a single floor dust lead loading at or above the standard declined 41% 

from pre-intervention to one-year post-intervention (56% to 33%, respectively) (Table 8-

4/Figure 8-3). 

• Geometric mean interior floor dust lead loadings did not increase from final clearance to 

one-year post-intervention (13 μg/ft2 to 12 μg/ft2

). However, at one year postintervention, the percentage of dwellings failing floor clearance standards of 100 μg/ft2 

increased from 11% at clearance to 18%. 

• Three-years post-intervention, the geometric mean interior floor dust lead loading was 9 

μg/ft2 (Table 8-5). This represents a 78 percent decline from the pre-intervention levels. 

The percentage of dwellings with an interior floor dust lead loading at or above 100 

μg/ft2 remained at 18 percent, while the percentage of dwellings with an interior floor 

dust lead loading at or above 40 μg/ft2

 declined to 30 percent (Table 8-6). 

 

The effect of interventions on dwelling unit entry floor dust lead loadings was similar to the 

effect on interior floors, but average entry floor dust lead levels were higher. Geometric mean 

entry floor dust lead loadings were generally 10 to 20 percent higher than interior floor dust lead 

loadings across all phases of the evaluation. 

8.3.4 Window Dust Lead Findings 

On windows, the overall reductions in geometric mean dust lead loadings were even more 

dramatic. The effects of interventions on window sill and window trough post-intervention dust 

lead loadings were similar to each other but window trough dust lead levels were higher. At preintervention, geometric mean window trough dust lead loadings were 8 to 12 times higher than 

window sill dust lead loadings, while post-intervention, the trough dust lead loadings were 

generally 4 to 6 times higher than sill dust lead loadings. (At clearance, the trough dust lead 

loadings remained higher than the sill dust lead loadings, but the relative difference was much 

smaller.) 

• There was an overall reduction of 434 μg/ft2 (88%) in geometric mean window sill lead 

loadings from pre-intervention to one-year post-intervention. Geometric mean window 

trough dust lead loadings declined 4,288 μg/ft2

 (93%) from pre-intervention to one-year 

post-intervention (Table 8-3/Figure 8-2). 

• Window sill dust lead loadings rose 45 μg/ft2 from clearance to six months postintervention before declining 7 μg/ft2

 from six-months to one-year post-intervention. 

Geometric mean window trough dust lead loadings rose 367 μg/ft2

 from clearance to six 

months post-intervention before declining 75 μg/ft2

 at one-year post-intervention. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-13 

• One-year post-intervention, 14 percent of the dwellings had window sill dust lead 

loadings at or above 500 μg/ft2

. This represents a 75 percent decline from the preintervention percentage (55%). Using the current standard of 250 μg/ft2

, the percentage 

of dwellings with a single floor dust lead loading at or above the standard declined 63 

percent from pre-intervention to one-year post-intervention (67% to 25%, respectively) 

(Table 8-4/Figure 8-3). Thirty-four percent of the dwellings had a one-year window 

trough dust lead loading at or above 800 μg/ft2

, a 56 percent decline from the preintervention percentage (77%). Using the current standard of 400 μg/ft2

, the percentage 

of dwellings with a single floor dust lead loading at or above the standard declined 42 

percent from pre-intervention to one-year post-intervention (84% to 49%, respectively) 

• Three-years post-intervention, the geometric mean window sill dust lead loading was 62 

μg/ft2, an 89 percent decline from pre-intervention and a 13 percent decline from oneyear post-intervention (Table 8-5). The geometric mean window trough dust lead loading 

was 363 μg/ft2

, a 95 percent decline from the pre-intervention levels and a 28 percent 

decline from one-year post-intervention. The percentage of dwellings with a window sill 

dust lead loading at or above 500 μg/ft2

 declined to 12 percent, while the percentage of 

dwellings with a window trough dust lead loading at or above 800 μg/ft2

 declined to 24 

percent (Table 8-6). 

Discussion 

Although the number of dwellings that met the extended Evaluation dust dataset criteria was 

about one quarter the size of the population that met the base Evaluation dust dataset criteria, the 

overall changes and observed trends were similar. It is of interest that the extended Evaluation 

pre-intervention geometric mean window sill and trough dust lead loadings were 14 and 67 

percent higher, respectively, than those of the base Evaluation dataset, but percentage changes in 

window dust lead loadings between pre-intervention, six-months and one-year post-intervention 

were roughly equivalent. 

The findings demonstrate that the lead hazard control activities undertaken by the grantees can 

dramatically reduce the floor dust lead loadings in treated dwellings and those levels can be 

maintained for at least three years. The fact that geometric mean floor dust lead loadings were 12 

μg/ft2 and 14 μg/ft2 on interior floor and entry floors three years after clearance further suggests 

that in housing likely to receive this type of Federal lead-hazard control assistance, the 

interventions used in the Evaluation can reduce floor dust lead loadings below the current 

Federal hazard standard (40 μg/ft2

) for an extended period of time. 

The interventions were equally effective on window dust lead loadings. Three years postintervention, the geometric mean window sill dust lead loading was 62 μg/ft2

, or one quarter of 

the current Federal hazard standard (250 μg/ft2

) for sills. The interventions used in the 

Evaluation resulted in 95 percent reductions in window trough dust lead loadings one year postintervention and 97 percent reductions in those loadings three years post-intervention. Although 

the federal government does not have a standard for window trough dust lead hazards, the 

geometric mean window trough dust lead loading at three-years post-intervention, 363 μg/ft2

, 

was below the current clearance standard for troughs (400 μg/ft2

). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-14 

Table 8-3: Geometric Mean Dust Lead Loading at Each Sampling Phase of the 

Evaluation by Surface Sampled: One- Year Post- Intervention Dataset 

Sampling Phase Entry Floor 

GM (GSD) 

μg/ft2

Interior Floors 

GM (GSD) 

μg/ft2

Window Sills 

GM (GSD) 

μg/ft2

Window Troughs 

GM (GSD) 

μg/ft2

Pre-Intervention 45 

(7) 

40 

(6) 

496 

(7) 

4,621 

(11) 

Clearance 13 

(3) 

13 

(3) 

24 

(4) 

41 

(4) 

Six-Months PostIntervention 16 

(4) 

13 

(4) 

69 

(4) 

408 

(6) 

One-Year PostIntervention 14 

(4) 

12 

(4) 

62 

(4) 

333 

(6) 

Table 8-4: Percent of Dwellings with at Least One Dust Lead Loading at or Above Given 

Standards at Each Sampling Phase of the Evaluation by Surface Sampled: One-Year PostIntervention Dataset 

Entry Floor 

Percent at or above 

Standard 

Interior Floors 

Percent at or above 

Standard 

Window Sills 

Percent at or above 

Standard 

Window Troughs 

 Percent at or 

above Standard 

Sampling Phase 

100 

μg/ft2

40 

μg/ft2

100 

μg/ft2

40 

μg/ft2

500 

μg/ft2

250 

μg/ft2

800 

μg/ft2

400 

μg/ft2

Pre-Intervention 32% 48% 40% 56% 55% 67% 77% 84% 

Clearance 4% 21% 11% 34% 0% 7% 0% 7% 

Six-Months PostIntervention 10% 25% 23% 37% 16% 27% 37% 53% 

One-Year PostIntervention 8% 21% 18% 33% 14% 25% 34% 49% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-15 

Figure 8-1: Geometric Mean Entry Floor and Interior Floor Dust Lead 

Loading from Pre-Intervention to One-Year Post-Intervention

0

5

10

15

20

25

30

35

40

45

50

-2 0 2 4 6 8 10 12

Months Post-Intervention

Dust Lead Loading (μg/ft2

)

Entry Interior Floor

Pre-Int.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-16 

Figure 8-2: Geometric Mean Window Sill and Trough Dust Lead Loading 

from Pre-Intervention to One-Year Post-Intervention

0

100

200

300

400

500

600

-2 0 2 4 6 8 10 12

Months Post-Intervention

Dust Lead Loading (μg/ft2

)

Sill Trough

Pre-Int.

?4621
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-17 

Figure 8-3: Percent of Dwellings with at Least One Dust Lead Loading at or 

Above 100 μg/ft2

 on Floors, 500μg/ft2 on Window Sills or 800 μg/ft2 on 

Window Troughs from Pre-Intervention to 

One-Year Post-Intervention

0

10

20

30

40

50

60

70

80

-2 0 2 4 6 8 10 12

Months Post-Intervention

Percent at or Above Standard

Entry Floor Int. Floor Sill Trough

Pre-Int.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-18 

 

Table 8-5: Geometric Mean Dust Lead Loadings at Each Sampling Phase of the Evaluation 

by Surface Sampled: Three-Year Post-Intervention Dataset 

Sampling Phase Entry Floor 

GM (GSD) 

μg/ft2

Interior Floors 

GM (GSD) 

μg/ft2

Window Sills 

GM (GSD) 

μg/ft2

Window 

Troughs 

GM (GSD) 

μg/ft2

Pre-Intervention 48 

(7) 

40 

(6) 

576 

(8) 

7,725 

(9) 

Clearance 16 

(4) 

14 

(3) 

28 

(3) 

40 

(4) 

Six-Months PostIntervention 

16 

(4) 

11 

(4) 

86 

(5) 

560 

(7) 

One-Year PostIntervention 

14 

(4) 

12 

(4) 

71 

(4) 

503 

(7) 

Two-Years PostIntervention 

12 

(4) 

10 

(5) 

61 

(5) 

390 

(9) 

Three-Years 

Post-Intervention 

10 

(5) 

9 

(6) 

62 

(5) 

363 

(9) 

Table 8-6: Percent of Dwellings with at Least One Dust Lead Loading at or Above Given 

Standards Each Sampling Phase of the Evaluation by Surface Sampled: Three-Year PostIntervention Dataset 

Entry Floor 

Percent at or 

above Standard 

Interior Floors 

Percent at or 

above Standard 

Window Sills 

Percent at or 

above Standard 

Window 

Troughs 

 Percent at or 

above Standard 

Sampling Phase 

100 

μg/ft2

40 

μg/ft2

100 

μg/ft2

40 

μg/ft2

500 

μg/ft2

250 

μg/ft2

800 

μg/ft2

400 

μg/ft2

PreIntervention 36% 51% 44% 59% 59% 69% 86% 91% 

Clearance 8% 24% 13% 39% 0% 11% 0% 8% 

Six-Months 

PostIntervention 

11% 25% 21% 32% 23% 35% 48% 63% 

One-Year PostIntervention 11% 25% 22% 35% 14% 29% 44% 58% 

Two-Years PostIntervention 

11% 21% 18% 29% 16% 26% 41% 52% 

Three-Years 

Post-Intervention 

6% 19% 18% 30% 12% 24% 38% 51% 

 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-19 

The lead hazard control interventions were not only effective in reducing household maximum 

dust lead loadings below the 1990 HUD Guidance levels (200 μg/ft2

 on floors, 500 μg/ft2on 

window sills, and 800 μg/ft2

 on window troughs) at clearance, but they were able to maintain 

maximum dust lead loadings below those levels through three-years post-intervention. Although 

the grantees were not required to clear to a floor level of 40 μg/ft2

 or a window sill level of 250 

μg/ft2

, the treatments were fairly successful in reaching and maintaining these levels through 

three-years post-intervention. The treatments were less successful in maintaining window trough 

dust lead loadings below the current standard of 400 μg/ft2

, with over half of the dwellings 

having exceeding the standard one to three years after clearance. 

8.4 RELATIVE EFFECTIVENESS OF INTERVENTION STRATEGIES ON DUST LEAD LOADINGS

The overall statistics offer the reader a context to identify apparent trends in dust lead loadings 

across time. However, the focus of the objectives of the Evaluation was to determine whether the 

various lead hazard control treatments used by grantees had differential effects on dust lead 

loadings. This section of the report examines in detail the relative effectiveness of various 

interior and exterior lead hazard control treatments on post-intervention dust lead loadings. 

This section is divided into three subsections. The first subsection uses the RM models described 

in Section 8.2.3 to look at the effect of interior strategies on post-intervention dust lead loadings 

without consideration of other variables. The second subsection examines the effects of interior 

strategies and other lead hazard control work on post-intervention dust lead loadings when other 

factors are considered with multiple regression models. The third subsection observes the 

pathways of paint and dust lead both pre-intervention and one-year post-intervention and 

considers how the lead hazard control interventions modified those pathways with SEMs. 

8.4.1 Relationships Between Interior Strategy and Post-Intervention Dust Lead Loadings 

Without Consideration for Other Factors 

This section presents the observed associations between interior strategy and dust lead loadings 

without consideration of other factors. As will be presented in Section 8.4.2, these bivariate 

associations are generally similar to the relationships between the two variables when other 

factors are considered. The multivariate models will demonstrate that other factors can influence 

the relationships between the interior interventions and dust lead loadings, but a presentation of 

the non-model adjusted findings offers important context for the later findings. 

8.4.1.1 Floor Dust Lead Loadings: One-Year Post-Intervention. Findings for the geometric mean 

pre- and one-year post-intervention floor dust lead loadings by Interior Strategy are presented on 

Tables 8-7 and 8-8. These tables also present the percentage of dwellings at pre- and one-year 

post-intervention with the entry or at least one interior floor sample above5

 100 or 40 μg/ft2 by 

Interior Strategy. 

 

5

 Even though most grantees cleared at 200 μg/ft2, the 1990 clearance standard specified in the HUD Grant 

agreements, this level was not examined because so few dwellings exceeded this level one-year post-intervention. 

One hundred (100) μg/ft2 represents the 1995 HUD interim guidance standard for floors while 40 μg/ft2 represents 

the current Federal clearance standard. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-20 

Table 8-7: Geometric Mean Entry Dust Lead Loadings and Percent of Dwellings with 

Entry Floor Dust Lead Loadings at or Above 40 or 100 μg/ft2

 at Pre- and One-Year PostIntervention by Interior Strategy 

Geometric Mean 

Entry Floor Dust 

Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with the Entry Floor Sample at or 

Above: 

100 μg/ft2 40 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 1 Yr 

Post- Pre- 1 Yr Pre 1 Yr 

02 56 12 10 2% 5% 14% 13% 

03 122 23 12 11% 7% 24% 16% 

04 147 46 15 31% 14% 48% 31% 

05 675 55 15 38% 8% 55% 22% 

06/07 34 80 7 47% 0% 62% 3% 

All 1,034 45 14 32% 9% 48% 21% 

Table 8-8: Geometric Mean Interior Floor Dust Lead Loadings and Percent of Dwellings 

with at Least One Interior Floor at or Above 40 or 100 μg/ft2

 at Pre- and One-Year PostIntervention by Interior Strategy 

Geometric Mean 

Interior Floor Dust 

Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with at Least One Interior Floor 

Sample at or Above: 

100 μg/ft2 40 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 1 Yr 

Post- Pre- 1 Yr Pre 1 Yr 

02 56 10 6 11% 2% 23% 13% 

03 122 17 9 13% 7% 31% 20% 

04 147 38 9 31% 11% 53% 22% 

05 675 50 15 48% 24% 64% 41% 

06/07 34 95 6 56% 0% 71% 3% 

All 1,034 40 12 40% 18% 56% 33% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-21 

Post-clearance trends of entry and interior floor dust lead loadings by strategy were also explored 

(Figures 8-4 and 8-5, respectively). The dust lead loadings displayed differing trends by 

intervention after the treatments were completed. At final clearance, the geometric mean dust 

lead loadings on floors treated with Interior Strategies 02 and 05 were lower than those of other 

strategies (see Section 7.3.2.3 for further discussion). In dwellings treated with Interior Strategy 

05, geometric mean dust lead loadings on both entry floors and interior floors significantly 

increased until six months post-intervention. During the same time period, dust lead loadings of 

interior floors treated with Interior Strategies 03, 04 and 06/07 significantly declined from 

clearance to six months post-intervention. Entry floor dust lead loadings in dwellings treated 

with Interior Strategy 06/07 also significantly decreased until six months post-intervention. 

Between six months and one-year post-intervention, geometric mean entry floor and interior 

floor dust lead loadings generally remained constant or declined slightly (1-2 μg/ft2

) regardless 

of the intervention. 

 

Discussion 

The longitudinal finding of most interest is that across all strategies, there was no indication that 

dust lead loadings on floors increased between clearance and three-years post-intervention. 

Indeed, dust lead loadings declined between these two sampling phases. If any lead-based paint 

deteriorated and generated dust lead, it likely was removed from the floors through routine 

cleaning and use. Although the sample sizes for dwellings treated with Interior Strategies 02 and 

03 are small (therefore limiting the significant differences that might have been observed 

between strategies), the trends of the different interior interventions on post-intervention dust 

lead loadings were comparable. 

These longitudinal trends, especially the trends from clearance to six-months post-intervention, 

offer important insights into the changes in dust lead loadings following clearance. Although the 

study originally anticipated that the clearance dust lead loadings would be the lowest loadings 

observed during the course of the study, post-intervention dust lead loadings showed continuing 

declines for three out of five of the strategies. After occupants returned to dwellings treated with 

Interior Strategies 03, 04 and 06/07, additional dust lead was removed from these dwellings. 

These same interventions had the highest floor dust lead loadings at clearance, suggesting that 

worksite containment and cleaning were not as effective in these dwellings as in dwellings 

treated with Interior Strategy 02 or 05. In fact, for a small percentage of the dwellings, the 

treatment left more leaded dust in the home than existed prior to work (see Section 8.4.2.1.2). 

Interestingly, dwellings treated with Interior Strategy 05 had significant increases in dust lead 

loadings between clearance and six-months post-intervention. Previous studies have observed 

that following final clearance, dust lead loadings can reaccumulate rapidly. Results from the 

Baltimore Repair and Maintenance Study identified an increase in dust lead loadings that 

occurred within two months of the intervention before loadings leveled off (EPA 1997a). The 

investigators in that study suggested that when families returned to their dwellings, leaded dust 

was brought into the dwelling from external sources. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-22 

Figure 8-4: Entry Floor Dust Lead Loading from Clearance to One-Year 

Post-Intervention by Interior Strategy

0

5

10

15

20

25

0 6 12

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05

06/07

Figure 8-5: Interior Floor Dust Lead Loading from Clearance to One-Year 

Post-Intervention by Interior Strategy

5

10

15

20

0 6 12

Months Post-Intervention

Dust Lead Loading (ug/ft

2

02

03

04

05

06/07
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-23 

These findings suggest that the measurement of dust reaccumulation as originally conceived by 

the Evaluation team did not consider other substantial factors. Beyond the effects of deteriorating 

interior paint lead adding to the leaded dust in the dwelling, the effects of occupancy and the 

effects of external sources of leaded dust appear to have affected changes in dust lead 

immediately after clearance. Therefore, the use of the clearance loadings as a ìbaselineî for 

reaccumulation of leaded dust from treatment failures would not be appropriate. Furthermore, the 

findings of the dwellings treated with Interior Strategy 06/07 suggest that after one year, dust 

lead loadings in these dwellings was still approaching, but had not reached equilibrium (i.e., a 

point where the removal of leaded dust by routine cleaning was balanced by the introduction of 

leaded dust from environmental sources). 

8.4.1.2 Floor Dust Lead Loadings: Three-Years Post-Intervention. Three-year post-intervention 

dust lead data were examined to determine whether the trends observed in the base Evaluation 

continued for two additional years and whether any new trends emerged between one- and threeyears post-intervention. Unfortunately, comparisons between strategies were less robust in the 

extended Evaluation because of low sample sizes. The number of available dwellings dropped 

from 1,034 dwellings in the base Evaluation to 278 in the extended Evaluation. Furthermore, the 

sample sizes for some of the intervention strategies were quite small. The main contributor of 

dwellings treated with Interior Strategy 03 or 06/07, New York City, did not participate in the 

extended Evaluation. Too few Interior Strategy 06/07 dwellings (7) were available in the 

extended Evaluation to draw meaningful conclusions, so this strategy was not analyzed. Just 20 

dwellings were treated with Interior Strategy 02 and 23 dwellings treated with Interior Strategy 

03. When other factors are considered, comparisons between strategies will likely be limited to 

the effects of Interior Strategy 05 versus Interior Strategy 04. 

Findings for the geometric mean three-year post-intervention floor dust lead loadings and the 

percentage of dwellings with the entry or at least one interior floor sample above 100 or 40 μg/ft2

by Interior Strategy are presented on Tables 8-9 and 8-10. 

Table 8-9: Geometric Mean Entry Dust Lead Loadings and Percent of Dwellings with 

Entry Floor Dust Lead Loadings at or Above 40 or 100 μg/ft2

 at Pre- and Three-Years 

Post-Intervention by Interior Strategy 

Geometric Mean 

Entry Floor Dust 

Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with the Entry Floor Sample at or 

Above: 

100 μg/ft2 40 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 3 Yr 

Post- Pre- 3 Yr Pre 3 Yr 

02 20 12 11 5% 0% 20% 5% 

03 23 34 7 22% 4% 35% 13% 

04 59 35 10 25% 7% 42% 14% 

05 176 65 11 45% 7% 60% 23% 

All 278 48 10 36% 6% 50% 19% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-24 

Table 8-10: Geometric Mean Interior Floor Dust Lead Loadings and Percent of Dwellings 

with at Least One Interior Floor at or Above 40 or 100 μg/ft2

 at Pre- and Three-Years PostIntervention by Interior Strategy 

Geometric Mean 

Interior Floor Dust 

Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with the Interior Floor Sample at 

or Above: 

100 μg/ft2 40 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 3 Yr 

Post- Pre- 3 Yr Pre 3 Yr 

02 20 10 8 10% 0% 20% 10% 

03 23 16 5 22% 0% 43% 4% 

04 59 27 8 32% 12% 53% 25% 

05 176 60 10 55% 24% 68% 37% 

All 278 40 9 44% 18% 59% 30% 

The trends for post-intervention entry floor and interior floor dust lead loadings by interior 

strategy in the extended Evaluation dataset (Figures 8-6 and 8-7) were similar to those in the 

base Evaluation dataset between clearance and one-year post-intervention. However, no 

significant differences between interior strategies were identified for entry floors in the extended 

Evaluation dataset. 

Between one-year and three-years post-intervention, both entry floor and interior floor dust lead 

loadings in dwellings treated with Interior Strategies 03, 04 and 05 declined, while those in 

dwellings treated with Interior Strategy 02 increased. For those floor dust lead loadings that 

declined, the dust lead loadings generally decreased 3-4 μg/ft2

, or roughly 30 percent in the two 

years of the extension. The changes for Interior Strategies 04 and 05 were statistically 

significant. 

Discussion 

As discussed in the one-year findings, the changes immediately after clearance may reflect the 

influence of activities other than the deterioration of interior lead-based paint, such as the 

movement of external sources of lead into a dwelling following treatment6

 and the routine 

cleaning of a reoccupied dwelling. Furthermore, the results reinforce the observation made with 

the base Evaluation data that because it takes time for dust lead loadings to reach equilibrium, it 

is difficult to identify a post-intervention ìbaselineî from which to measure the potential 

reaccumulation of dust lead. 

 

6

 A study by NCHH in Cambridge, Massachusetts observed that after dwellings were treated and cleared, work 

continued in the common areas and hallways and within one month of clearance entry dust lead loadings within the 

dwellings increased dramatically. The external sources may reflect sources at the property being treated as well as in 

the local environment. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-25 

Figure 8-6: Entry Floor Dust Lead Loading from Clearance to 

Three-Years Post-Intervention by Interior Strategy

5

7

9

11

13

15

17

19

21

0 12 24 36

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05

Figure 8-7: Interior Floor Dust Lead Loading from Clearance to 

Three-Years Post-Intervention by Interior Strategy

0

5

10

15

20

0 12 24 36

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-26 

8.4.1.3 Window Dust Lead Loadings: OneñYear Post-Intervention. Findings for the geometric 

mean pre- and one-year post-intervention window dust lead loadings by Interior Strategy are 

presented on Tables 8-11 and 8-12. These tables also present the percentage of dwellings at preand one-year post-intervention with at least one window sill sample above 500 or 250 μg/ft2

 or at 

least one window trough sample above 800 or 400 μg/ft2

 by Interior Strategy. 

 

Table 8-11: Geometric Mean Window Sill Dust Lead Loadings and Percent of Dwellings 

with at Least One Window Sill Dust Lead Loading at or Above 250 or 500 μg/ft2

 at Preand One-Year Post-Intervention by Interior Strategy 

Geometric Mean 

Window Sill Dust 

Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with the Window Sill Sample at 

or Above: 

500 μg/ft2 250 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 1 Yr 

Post- Pre- 1 Yr Pre 1 Yr 

02 56 117 91 25% 20% 43% 29% 

03 122 168 102 27% 21% 41% 38% 

04 147 479 84 52% 19% 64% 33% 

05 675 685 53 63% 11% 75% 21% 

06/07 34 518 30 59% 9% 71% 18% 

All 1,034 496 62 55% 14% 67% 25% 

Table 8-12: Geometric Mean Window Trough Dust Lead Loadings and Percent of 

Dwellings with at Least One Window Trough Dust Lead Loading at or Above 400 or 800 

μg/ft2

 at Pre- and One-Year Post-Intervention by Interior Strategy 

Geometric Mean 

Window Trough 

Dust Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with at Least One Window 

Trough Sample at or above: 

800 μg/ft2 400 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 1 Yr 

Post- Pre- 1 Yr Pre 1 Yr 

02 56 2,860 1,630 71% 63% 84% 73% 

03 122 1,178 266 54% 28% 69% 40% 

04 147 6,605 679 78% 51% 83% 61% 

05 675 5,881 266 82% 28% 87% 46% 

06/07 34 2,456 208 71% 35% 76% 47% 

All 1,034 4,621 333 77% 34% 84% 49% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-27 

The window dust lead loadings displayed similar trends after clearance for all interior 

intervention groups except Interior Strategy 06/07 (Figures 8-8 and 8-9). The dust lead loadings 

on windows treated with Interior Strategies 02-05 all increased from clearance to six-months 

post-intervention on both window sills and window troughs. These changes were all significant. 

Between six-months and one-year post-intervention, however, window dust lead loadings stayed 

the same or declined slightly on all of these surfaces, except window troughs treated with interior 

Strategy 02. Only in dwellings treated with Interior Strategy 05 did dust lead loadings on 

window sills and troughs significantly change (decline) after six months post-intervention. 

Window trough dust lead loadings in dwellings treated with Interior Strategy 06/07 also 

increased until six months post-intervention, but the magnitude of the change was much smaller 

and was not statistically significant. Dwellings treated with Interior Strategy 06/07 had the 

highest window trough dust lead loadings among the intervention groups at clearance; six 

months later it was the lowest. Yet, between six-months and one-year post-intervention, window 

trough dust lead loadings in dwellings treated with Interior Strategy 06/07 continued to increase, 

with this change being significant. By one-year post-intervention, the window trough dust lead 

loadings in these dwellings were comparable to those on troughs in dwellings treated with 

Interior Strategies 03 and 05. 

Window sill dust lead loadings exhibited an opposite pattern in dwellings treated with Interior 

Strategy 06/07. Unlike all other strategies, between clearance and six-months post-intervention, 

the sill dust lead loadings declined slightly, though not significantly. After six-months postintervention, window sill dust lead loadings in dwellings treated with Interior Strategy 06/07 

displayed similar patterns to windows treated with other interventions: the dust lead loadings 

declined slightly, though not significantly. Window sills treated with Interior Strategy 06/07 had 

among the highest dust lead loadings at clearance, but by one-year post-intervention they were 

significantly different (lower) than all other strategies. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-28 

Figure 8-8: Window Sill Dust Lead Loading from Clearance to OneYear Post-Intervention by Interior Strategy

0

25

50

75

100

125

0 6 12

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05

06/07

Figure 8-9: Window Trough Dust Lead Loading from Clearance to 

One-Year Post-Intervention by Interior Strategy

0

500

1000

1500

0 6 12

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05

06/07
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-29 

Discussion

Unlike floors, the longitudinal trends for window surfaces from clearance to six-months postintervention generally followed expectations as dust lead loadings rose after clearance. However, 

when considered in conjunction with the floor results, the reaccumulation in window dust lead 

raises questions about the source of this lead. It is possible that the rise in dust lead loadings 

support the original hypothesis that the increases reflect the deterioration of lead-based paint 

immediately after treatment. Yet, this would suggest that there were a large number of paint lead 

failures around the window surfaces immediately after treatment, but those failures essentially 

stopped between six-months and one-year after intervention. Alternatively, the increases in 

window dust lead loadings after interventions may offer further support for the theory suggested 

by the authors of an abatement study in Baltimore that immediately after clearance, dust lead 

loadings rise from external sources (Farfel 1991). If the cleaning by the contractors reduced 

window dust lead loadings to levels below the ambient levels in the environment, then the 

increases could reflect the window dust lead loadings seeking an equilibrium with that 

environment. Either theory is supportable by the results of the dwellings treated by Interior 

Strategy 06/07. Since these dwellings were fully abated, dust lead loadings would not be 

expected to rise post-intervention. At the same time, most of the Interior Strategy 06/07 

dwellings were in New York City where the limited amount of exterior lead on buildings and the 

taller buildings would be likely to introduce much less exterior leaded dust into a dwelling. 

8.4.1.4 Window Dust Lead Loadings: Three-Years Post-Intervention. Findings for the geometric 

mean pre- and three-year post-intervention window dust lead loadings by Interior Strategy are 

presented on Tables 8-13 and 8-14. These tables also present the percentage of dwellings at preand three-year post-intervention with at least one window sill sample above 500 or 250 μg/ft2

 or 

at least one window trough sample above 800 or 400 μg/ft2

 by Interior Strategy. 

 

Table 8-13: Geometric Mean Window Sill Dust Lead Loadings and Percent of Dwellings 

with at Least One Window Sill Dust Lead Loading at or Above 250 or 500 μg/ft2

 at Preand Three-Years Post-Intervention by Interior Strategy 

Geometric Mean 

Window Sill Dust 

Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with the Window Sill Sample at 

or Above: 

500 μg/ft2 250 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 3 Yr 

Post- Pre- 3Yr Pre 3 Yr 

02 20 174 136 30% 20% 50% 35% 

03 23 182 87 30% 17% 39% 35% 

04 59 570 124 59% 29% 69% 44% 

05 176 752 42 65% 5% 75% 15% 

All 278 567 62 59% 12% 69% 24% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-30 

Table 8-14: Geometric Mean Window Trough Dust Lead Loadings and Percent of 

Dwellings with at Least One Window Trough Dust Lead Loading at or Above 400 or 800 

μg/ft2

 at Pre- and Three-Years Post-Intervention by Interior Strategy 

Geometric Mean 

Window Trough 

Dust Lead Loading 

(μg/ft2

) by 

Intervention Phase 

Percent of Dwellings by Phase 

with at Least One Window 

Trough Sample at or Above: 

800 μg/ft2 400 μg/ft2

Interior 

Strategy 

Number of 

Dwellings 

Pre- 3 Yr 

Post- Pre- 3 Yr Pre 3 Yr 

02 20 8,625 1,753 90% 60% 95% 75% 

03 23 7,476 731 91% 48% 96% 52% 

04 59 15,216 622 92% 54% 93% 59% 

05 176 6,105 231 84% 28% 90% 45% 

All 278 6,037 310 86% 38% 91% 51% 

Window sill dust lead loadings in the extended Evaluation displayed similar trends across 

interior strategies (Figures 8-10). Between clearance and six-months post-intervention, window 

sill dust lead loadings increased dramatically. The geometric mean window sill dust lead 

loadings increased about three-fold from its clearance level (28 μg/ft2

). But between six-months 

and three-years post-intervention, window sill dust lead loadings declined 28 percent. The 

change from clearance to six-months post-intervention was significantly different as was the 

change from six-months post-intervention to three-years post-intervention. The magnitude of the 

changes in dust lead loadings varied by strategy but the overall direction and significance of the 

changes were the same across interior strategies, with the exception of dwellings treated with 

Interior Strategy 04. (In this case, dust lead loadings increased from six months to three-years 

post-intervention.) At clearance, dwellings treated with Interior Strategy 05 had significantly 

different (lower) dust lead loading than other strategies and this remained true three-years postintervention. 

The trends for window trough dust lead loadings (Figure 8-11) were similar to window sills, 

although the magnitude of the change from clearance to six-months post-intervention was much 

larger: overall, the geometric mean window trough dust lead loadings increased approximately 

14 times from its clearance level (40 μg/ft2

). The increases were larger for dwellings treated with 

Interior Strategy 02 and smaller for those treated with Interior Strategy 05. The window trough 

dust lead loadings for all strategies declined from six-months post-intervention to three-years 

post-intervention. At three-years post-intervention, dwellings treated with Interior Strategy 05 

had a significantly lower window trough dust lead loading than all other strategies, while 

dwellings treated with Interior Strategy 02 had significantly higher dust lead loadings than 

Interior Strategies 04 and 05. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-31 

Figure 8-10: Window Sill Dust Lead Loading from Clearance to ThreeYears Post-Intervention by Interior Strategy

0

50

100

150

0 12 24 36

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05

Figure 8-11: Window Trough Dust Lead Loading from Clearance to 

Three-Years Post-Intervention by Interior Strategy

0

1000

2000

3000

4000

5000

6000

7000

0 12 24 36

Months Post-Intervention

Dust Lead Loading (ug/ft2

)

02

03

04

05
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-32 

Discussion 

Between clearance and six-months post-intervention, something occurred around the windows 

that caused the dust lead loadings to dramatically rise. Because it occurred in dwellings where 

windows were abated as well as in dwellings where the window paint was treated with no more 

than limited paint stabilization, it does not appear as though the windows themselves are a likely 

source of the dust lead. However, observations presented in Section 8.6 suggest that other 

painted surfaces including exterior surfaces did experience substantial paint failure just in the 

first six months after interventions. It is also possible, as reported earlier, that the source was the 

ambient lead that settled on the windows sometime after clearance. 

Once the window dust lead loadings reached equilibrium with its environment, there was no 

indication that these dust lead loadings increased between six-months post-intervention and 

three-years post-intervention. If any change occurred, dust lead loadings declined between these 

two sampling phases. As with floors, if any lead-based paint deteriorated and generated dust 

lead, it was generally removed from the windows through routine cleaning and use. The effects 

of the different interior interventions were fairly comparable after intervention. 

8.4.2 Relationships Between Lead Hazard Control Interventions and 

Post-Intervention Dust Lead Loadings When Other Factors Are Considered 

Four multiple regression analyses were developed exploring factors that significantly affected 

the one-year post-intervention dust lead loadings (see Section 8.4.2 for details). The analyses 

produced models that separately examined the factors influencing dust lead on entry floors, 

interior floors, window sills and window troughs. The findings for the two floor dust lead models 

were similar as were the findings for the two window dust lead models, so each set of findings is 

presented jointly. 

8.4.2.1 One-Year Post-Intervention Floor Dust Lead Loadings

Factors that commonly influenced floor dust lead loadings were: 

Pre-intervention dust lead loadings log-trans. (lower levels : less dust lead) 

 Pre-intervention door/trim paint lead log-trans. (lower levels : less dust lead) 

 Pre-intervention floor surface condition (better condition : less dust lead) 

 Pre-intervention floor surface type (see below) 

 Building type (multi-unit : less dust lead) 

 Building age (newer : less dust lead) 

 Occupancy at pre-intervention (vacant : less dust lead) 

 Ownership (owner-occupied : less dust lead) 

 Height of Dwelling from Bldg Entrance (higher floors: less dust lead) 

Generally, these post-intervention findings were consistent with pre-intervention models that 

were developed (see Section 8.4.3.1). In two cases, the direction of the effect was reversed from 

pre-intervention. The direction of the effect of Occupancy Status changed for both entry floor 

and interior floor dust lead loadings and the direction of the effect of Floor Surface Type 

changed for entry floor dust lead loadings. These effects and changes in direction will be 

discussed in further detail in Section 8.4.2.1.3. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-33 

8.4.2.1.1 Intervention Effects on One-Year Post-Intervention Floor Dust Lead Loadings 

One-year post-intervention, all three measures of the lead hazard control interventions (Interior 

Strategy, Exterior LHC Work, and Site LHC Work) were significantly related to interior floor 

dust lead loadings. Dwellings where exterior lead hazard control work was performed had lower 

interior floor dust lead loadings than dwellings without such work, after controlling for other 

factors. Likewise, dwellings with site work had lower interior floor dust lead loadings than 

dwellings without these treatments. Interior floor dust lead loadings in dwellings not receiving 

exterior or site work were predicted to be 32 percent and 45 percent higher, respectively, than the 

dwellings receiving treatments. For an average dwelling, interior floor dust lead loadings at oneyear post-intervention were 3-4 μg/ft2

 higher in the dwellings that did not receive one of the 

interventions to the outside of the building or its immediate surroundings. (Similar effects of 

Exterior/Site Treatments are presented in Section 8.5.2.2). 

Because interior lead hazard control work was conducted at almost all dwellings, the effect of 

not performing interior work could not be assessed. However, there was enough diversity in 

Interior Strategies to assess differences in the effectiveness of the Interior Strategies on one-year 

post-intervention dust lead loadings. The Interior Strategies were found to interact with the preintervention floor dust lead loadings. In other words, the effects of Interior Strategies on postintervention dust lead loadings differed depending on the pre-intervention dust lead loading.7

 

Figure 8-12 presents the estimated one-year post-intervention interior floor dust lead loadings by 

Interior Strategy and pre-intervention interior floor dust lead loadings when keeping all other 

variables constant. All significant factors except exterior and site work8

 were set to their mean 

values. 

As displayed in the figure: 

• The effect of different Interior Strategies varied by the pre-intervention floor dust lead 

loadings. Interior Strategies 06/7 (full abatement) and 04 (window treatments) were not 

effected by the pre-intervention dust lead loadings, while Interior Strategies 02, 03 and 05 

had increasing dust lead loadings at one-year post-intervention as pre-intervention floor 

dust lead loadings increased. 

• The percent reductions in interior floor dust lead loadings increased as pre-intervention 

dust lead loadings increased. As a correlate to the previous observation, as preintervention floor dust lead loadings increased, dwellings treated with Interior Strategies 

06/07 and 04 displayed greater percent reductions than the other interior strategies. 

• Dwellings treated with Interior Strategies 06/07 had the largest reductions in interior floor 

dust lead loadings when compared with the other interior strategies, while dwellings 

treated with Interior Strategy 05 (window abatement) and Interior Strategy 03 (full paint 

stabilization) had the smallest reductions. At the median and 75th percentile pre-

 

7

 Pre-intervention interior floor dust lead loadings also interacted with the percentage of same rooms that were 

sampled at both pre- and one-year post-intervention. In dwellings where the floor dust lead samples were collected 

from the same rooms at both phases, post-intervention floor dust lead loadings increased with higher preintervention floor dust lead loadings. In dwellings where a smaller percentage of samples were collected from the 

same rooms, the relationship between pre- and post-intervention dust lead loadings was not as apparent. 

8

 For estimating purposes, exterior work was assumed to be performed, while site work was not. In this dataset, 76% 

of dwellings had exteriors treated and 13% of dwellings had the site treated. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-34 

intervention dust lead loadings, the reductions in interior floor dust lead loadings in 

dwellings treated with Interior Strategies 06/07 were significantly different than those in 

dwellings treated with Interior Strategy 03 or 05. Reductions in interior floor dust lead 

loadings when Interior Strategy 04 was used were also significantly different (greater) 

from those associated with Interior Strategy 03 or 05 in homes with pre-intervention floor 

dust lead loadings at or above the 75th percentile. At the median pre-intervention dust 

lead loading, post-intervention dust lead loadings in dwellings treated with Interior 

Strategy 05 were significantly different than those in dwellings treated with Interior 

Strategy 02 (cleaning/spot painting). 

Of interest, one-year post-intervention entry floor dust lead loadings were not significantly 

related to either different interior strategies or exterior/site lead hazard control work in the 

multiple regression analysis. Although a significant relationship was not identified between 

Interior Strategy and post-intervention entry floor dust lead in the analysis, the dust lead 

outcomes on entry floors and interior floors were fairly similar (Table 8-15 and 8-16). The 

influence of interior interventions on entry floor dust lead is further discussed in Section 8.4.3. 

8.4.2.1.2 Discussion of Intervention Effects

Although all interior strategies resulted in average dust lead loadings at one-year postintervention that were well below the current hazard standard of 40 μg/ft2

, different interior 

strategies resulted in significantly different post-intervention floor dust lead loadings. As an 

example, the multivariate modeling found that for dwellings with the median pre-intervention 

floor dust lead loading (30 μg/ft2

), full interior lead abatement (Interior Strategy 06/07) was 

associated with one-year post-intervention floor dust lead loadings that were 44 percent lower 

than loadings in homes treated with full paint stabilization (Interior Strategy 03). Such a finding 

matches expectations that the removal or permanent enclosure of all lead-based paint would 

eliminate most sources of lead dust in the home environment and result in lower dust lead 

loadings than lower intensity strategies. While some might debate whether these statistically 

significant differences are practically significant, previous studies demonstrating effects of floor 

dust lead on childrenís blood lead at levels below 40 μg/ft2 would suggest that these ìsmallî 

differences can have an impact on health outcomes. (Chapter 10 presents effect outcomes 

alongside the cost outcomes so that readers can assess cost-effectiveness.) 

Surprisingly, the second most intensive strategy (window abatement combined with additional 

treatments (Interior Strategy 05)) was not as effective in reducing floor dust lead loadings as 

cleaning or limited paint stabilization (Interior Strategy 02) or less extensive window treatments 

(Interior Strategy 04) at the median pre-intervention dust lead loading. Although Interior 

Strategy 05 was as effective at reducing floor dust lead loadings as most other strategies at 

clearance, something occurred between clearance and one-year post-intervention that increased 

the geometric mean floor dust lead loadings in these homes. During the same period, dwellings 

treated with Interior Strategies 03, 04 and 06/7 experienced declines in floor dust lead loadings. 

Evaluation researchers cannot account for the increase in floor dust lead loadings in the homes 

treated with Interior Strategy 05, but possible reasons include treatment failures, new interior 

lead-based paint deterioration, track-in or blow-in from exterior lead sources, or some other 

factor such as leaded dust on furnishings that had been stored during treatment. Section 8.4.2.2 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-35 

Figure 8-12: Predicted One-Year Post-Intervention Interior Floor Dust 

Lead Loading by Pre-Intervention Floor Dust Lead Loading and 

Interior Strategy 

5

7

9

11

13

15

17

19

0 50 100 150

Pre-Intervention Interior Floor Dust Lead Loading (ug/ft2

)

Predicted One-Year Post-Intervention 

Interior Floor Dust Lead Loading 

(ug/ft2

)

02

03

04

05

06/7

will present findings that window dust lead loadings in dwellings treated with Interior Strategy 

05 were lower than the loadings on windows treated with other less intensive strategies, yet these 

reductions did not correspond with lower floor dust lead loadings. Section 8.4.2.2 will also 

present findings that window sill and trough dust lead loadings in homes treated with Interior 

Strategy 05 more than tripled between clearance and six-months post-intervention suggesting 

that track-in and/or lead from furnishings were not the sole sources of the increases on floors. 

One serious limitation to the one-year analyses is the unequal distribution of interior strategies by 

pre-intervention dust lead loading (or more broadly, by baseline housing condition). Only a small 

number of dwellings (<15) with pre-intervention entry floor and interior floor dust lead loadings 

above the 75th percentile (167 and 134 μg/ft2

, respectively) were treated with either Interior 

Strategy 02, 03 or 06/07 (Tables 8-15 and 8-16). Anecdotally, grantees had concerns about the 

ability to achieve clearance using the lower intensity strategies on dwellings in poor condition so 

they chose not to apply them in the worst homes. Additional research would be needed to 

determine whether the effects of the lower intensity strategies on floor dust lead loadings are 

truly equivalent to (or better than) the effects of Interior Strategy 05. 

Although differential effects of interior lead hazard control strategies were observed in homes 

with higher pre-intervention dust lead loadings, for those dwellings where entry and interior floor 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-36 

dust lead loadings were initially low (<10 μg/ft2

), no intervention could be demonstrated to have 

a positive effect (Tables 8-15 and 8-16). This finding may be true for an assortment of reasons. 

Both the actual distribution of dust lead on a surface and the wipe sampling method are variable, 

so the selection of lower dust lead loadings as a baseline increases the chances that a second 

sample will be higher (i.e., regression to the mean). Furthermore, the objective of most 

contractors in the Evaluation was to pass floor clearance at a level of 100 or 200 μg/ft2

, so it 

would not be surprising if dust lead loadings on the ìcleanestî surfaces increased slightly after 

treatment. 

Table 8-15: Pre-Intervention and One-Year Post-Intervention Entry Floor Dust Lead 

Loadings by Interior Strategy and Pre-Intervention Entry Dust Lead Loading Quartile 

 

Pre-Intervention Entry Interior Strategy 

Dust Lead 02 03 04 05 06/07 

1st Quartile 

(<12 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

33 

6 

6 

0% 

29 

5 

8 

60% 

33 

5 

6 

20% 

159 

4 

8 

100% 

5 

1 

5 

400% 

2nd/3rd Quartile 

(12-167 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

22 

26 

22 

-15% 

85 

28 

13 

-54% 

78 

39 

17 

-56% 

317 

44 

16 

-64% 

15 

37 

6 

-84% 

4th Quartile 

(>167 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

1 

192 

5 

-97% 

8 

868 

27 

-97% 

36 

563 

25 

-96% 

199 

593 

27 

-95% 

14 

984 

10 

-99% 

All N 

GM Pre 

GM 1 Yr 

% Change 

56 

12 

10 

-17% 

122 

23 

12 

-48% 

147 

46 

15 

-67% 

675 

55 

15 

-73% 

34 

80 

7 

-91% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-37 

Table 8-16: Pre-Intervention and One-Year Post-Intervention Interior Floor Dust Lead 

Loadings by Interior Strategy and Pre-Intervention Interior Floor Dust Lead Loading 

Quartile 

Pre-Intervention Interior Interior Strategy 

Floor Dust Lead 02 03 04 05 06/07 

1st Quartile 

(<10 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

35 

5 

4 

-20% 

36 

5 

6 

20% 

27 

4 

6 

50% 

158 

5 

6 

20% 

4 

3 

6 

100% 

2nd/3rd Quartile 

(10-134 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

19 

24 

8 

-67% 

82 

26 

10 

-62% 

91 

28 

12 

-57% 

308 

38 

13 

-66% 

16 

28 

6 

-79% 

4th Quartile 

(>134 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

2 

389 

5 

-99% 

4 

562 

20 

-96% 

29 

806 

7 

-99% 

209 

449 

34 

-92% 

14 

1021 

7 

-99% 

All N 

GM Pre 

GM 1 Yr 

% Change 

56 

10 

6 

-40% 

122 

17 

9 

-47% 

147 

38 

9 

-76% 

675 

50 

15 

-70% 

34 

95 

6 

-94% 

8.4.2.1.3 Discussion of Other Factors 

At pre-intervention, occupied dwellings had lower dust lead loadings than vacant dwellings,

especially for floors. However, the predicted post-intervention dust lead loadings were higher in 

occupied dwellings after holding other factors constant. As discussed in Chapter 7, such a 

finding is likely a function of the dust loading (i.e., lack of cleaning) in the vacant dwelling (EPA 

1996b). When vacant and occupied dwellings have a similar pre-intervention dust lead 

concentration and the vacant dwelling has a higher dust loading, then the vacant unit will have a 

higher dust lead loading. Simply cleaning the vacant dwelling so its dust loading was equivalent 

to the occupied dwelling, would result in a lower post-intervention dust lead loading in the 

vacant dwellings. As discussed in Chapter 7, when pre-intervention dust lead loadings were not 

held constant for the occupancy groups, little difference in post-intervention dust lead loadings 

was observed between the two groups. 

For entry floors, floors that were painted prior to intervention and in better condition had lower 

dust lead loadings one-year post-intervention than unpainted or carpeted surfaces. At preintervention, painted entry and interior floors had higher dust lead loadings than the other 

surfaces. The finding may reflect an indirect influence of the intervention, since 43 percent of the 

painted entry surfaces changed to a different surface type post-intervention (as compared to 24% 

of carpeted entries and 13% of unpainted entries). Interestingly for interior floors, the outcomes 

post-intervention were similar to those pre-intervention with carpeted floors having the lowest 

predicted dust lead loadings and painted floors having the highest dust lead loadings. This may 

reflect the fact that Interior Strategy was a significant variable in this model. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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8.4.2.2 One-Year Post-Intervention Window Dust Lead Loadings

Factors that commonly influenced window dust lead loadings were: 

Pre-intervention dust lead loadings log-trans. (lower levels : less dust lead) 

 Pre-intervention paint lead log-trans. (lower levels : less dust lead) 

 Building age (newer : less dust lead) 

 Ownership (owner-occupied : less dust lead) 

The occupancy of the dwelling prior to intervention also influenced window sill dust lead 

loadings at one-year post-intervention, while the season of dust collection influenced window 

trough dust lead loadings. The condition of the exterior paint was related to window sill dust 

lead, while the exterior paint lead level was related to window trough dust lead. 

8.4.2.2.1 Intervention Effects on One-Year Post-Intervention Window Dust Lead Loadings 

Interior Strategies were significantly related to one-year post-intervention dust lead loadings on 

both window sills and window troughs. As with interior floors, the Interior Strategies were found 

to interact with the pre-intervention dust lead loadings for each of the respective sample types. 

Figures 8-13 and 8-14 present the estimated one-year post-intervention window sill and window 

trough dust lead loadings by Interior Strategy and pre-intervention dust lead loadings when 

setting all variables to their mean values. 

Figure 8-13: Predicted One-Year Post-Intervention Window Sill Dust 

Lead Loading by Pre-Intervention Sill Dust Lead Loading and Interior 

Strategy 

0

50

100

150

200

250

0 500 1000 1500 2000 2500

Pre-Intervention Window Sill Dust Lead Loading (ug/ft2

)

Predicted One-Year PostIntervention Window Sill Dust 

Lead Loading (ug/ft2

)

02

03

04

05

06/7
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-39 

Figure 8-14: Predicted One-Year Post-Intervention Window Trough 

Dust Lead Loading by Pre-Intervention Trough Dust Lead Loading 

and Interior Strategy 

0

500

1000

1500

2000

2500

3000

3500

4000

0 5000 10000 15000 20000 25000 30000 35000

Pre-Intervention Window Trough Dust Lead Loading 

(ug/ft2

)

Predicted One-Year PostIntervention Window Trough 

Dust Lead Loading (ug/ft2

)

02

03

04

05

06/7

? 30031

As displayed in the figures: 

• The percent reductions in window dust lead loadings increased as pre-intervention dust 

lead loadings increased. 

• Dwellings treated with window abatement including both Interior Strategy 05 and 06/07 

were associated with the largest percent reductions in window dust lead loadings. 

Dwellings treated with cleaning or limited spot painting (Interior Strategy 02) were 

associated with the smallest percent reductions in window dust lead loadings. 

• As the intensity of the Interior Strategy increased, the percent reductions in one-year 

post-intervention dust lead loadings on window sills increased. At the median and 75th

percentile pre-intervention dust lead loadings, all Interior Strategies were significantly (or 

marginally significantly) different from each other except Interior Strategies 02 and 03. 

• On window troughs, one-year post-intervention dust lead loadings were almost always 

significantly different (higher) in dwellings treated with Interior Strategy 02 than all other 

Interior Strategies across the interquartile range9

. Dwellings treated with Interior Strategy 

05 had significantly different (lower) one-year post-intervention window trough dust lead 

loadings than all other Interior Strategies except Interior Strategies 06/07. 

In addition to the differential effects of Interior Strategies, the regression models also identified a 

significant relationship between exterior lead hazard control treatments and one-year postintervention window sill dust lead loadings. Exterior work was associated with lower window sill 

 

9

 At the 25th percentile, Interior Strategies 02 and 04 were marginally significantly different. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-40 

dust lead loadings. Window sill dust lead loadings in dwellings not receiving exterior treatments 

were predicted to be 33 percent higher than the dwellings receiving treatments. 

8.4.2.2.2 Discussion of Intervention Effects on Window Dust Lead

The effect of interior interventions on post-intervention window dust lead loadings more closely 

matched expectations than their effects on floor dust lead loadings. Especially on window sills, 

as the intensity of the interior strategy increased, the reductions of the window dust lead loadings 

from pre-intervention to one-year post-intervention increased as well. Although window trough 

dust lead results did not follow in rank order, windows that were abated (Interior Strategies 05 

and 06/07) exhibited the largest reductions while windows that were only cleaned (Interior 

Strategy 02) displayed the smallest reductions. 

These findings may be a logical result of the Interior Strategies being defined more by their 

treatments to windows than to the other components in the dwelling. Although results presented 

in Chapter 5, as well as anecdotal evidence, suggest that dwellings treated with more intensive 

window treatments also had more intensive treatments to other components, the strategy 

definitions did not require this. Thus, it is reasonable that higher intensity interior strategies were 

more effective in reducing window dust lead loading than floor dust lead loading. 

As with the floor results, some might debate whether the statistically significant differences in 

window sill outcomes are practically significant, since the geometric mean dust lead loadings for 

individual strategies were all below the current Federal hazard standard. Although cleaning only 

(Interior Strategy 02) in dwellings with average baseline conditions was associated with one-year 

post-intervention floor dust lead loadings that were four times higher than loadings in similar 

homes treated with full interior lead abatement (Interior Strategy 06/07), the estimated geometric 

mean loading for a dwelling with a median pre-intervention dust lead loading was well below 

200 μg/ft2

. However, the findings suggest in the ìworstî quartile of housing, as measured by 

baseline dust lead loadings, the choice of strategy appears to have made a difference in whether 

window sill dust lead hazards would have existed one-year post-intervention. 

As previously discussed, a limitation to the one-year analyses is the unequal distribution of 

interior strategies by pre-intervention dust lead loading . Less than 15 dwellings treated with 

either Interior Strategy 02, 03 or 06/07 had pre-intervention interior window dust lead loadings 

above the 75th percentile (Tables 8-17 and 8-18). However, unlike floors, the tendency for 

windows treated with window abatement (Interior Strategies 05 and 06/07) to be associated with 

greater reductions in window dust lead loadings than windows treated with cleaning (Interior 

Strategy 02) is just as clear between the middle two quartiles as it is in the upper quartile. 

Similar to the findings for entry floors and interior floors, for those dwellings where window sill 

dust lead loadings were initially low (<122 μg/ft2

), no intervention except Interior Strategy 05 

had a positive effect (Table 8-17). The increases in dust lead loadings between pre-intervention 

and one-year post-intervention could be related to a variety of factors. For example, contractors 

in the Evaluation had to pass window sill clearance at 500 μg/ft2

, so it was acceptable to have 

increases in dust lead loadings when pre-intervention dust lead loadings were well below the 

clearance standards. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-41 

Table 8-17: Pre-Intervention and One-Year Post-Intervention Window Sill Dust Lead 

Loadings by Interior Strategy and Pre-Intervention Entry Dust Lead Loading Quartile 

Pre-Intervention Window Interior Strategy 

Sill Dust Lead 02 03 04 05 06/07 

1st Quartile 

(<122 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

28 

27 

51 

89% 

52 

43 

87 

102% 

38 

46 

51 

11% 

132 

46 

39 

-15% 

9 

36 

36 

0% 

2nd/3rd Quartile 

(122-2,106 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

24 

347 

118 

-66% 

59 

282 

108 

-62% 

75 

406 

92 

-77% 

343 

494 

51 

-90% 

16 

632 

23 

-96% 

4th Quartile 

(>2,106 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

4 

5,023 

1,147 

-77% 

11 

6,303 

163 

-97% 

34 

9,565 

120 

-99% 

200 

7,079 

71 

-99% 

9 

5,198 

42 

-99% 

All N 

GM Pre 

GM 1 Yr 

% Change 

56 

117 

91 

-22% 

122 

168 

102 

-39% 

147 

479 

84 

-82% 

675 

685 

53 

-92% 

34 

518 

30 

-94% 

Table 8-18: Pre-Intervention and One-Year Post-Intervention Window Trough Dust Lead 

Loadings by Interior Strategy and Pre-Intervention Interior Floor Dust Lead Loading 

Quartile 

Pre-Intervention Window Interior Strategy 

Trough Dust Lead 02 03 04 05 06/07 

1st Quartile 

(<846 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

18 

208 

249 

20% 

63 

230 

145 

-37% 

35 

216 

203 

-6% 

133 

179 

210 

17% 

10 

193 

64 

-67% 

2nd/3rd Quartile 

(846-30,000 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

30 

4,074 

2,020 

-50% 

46 

3,092 

366 

-88% 

68 

6,082 

736 

-88% 

354 

5,688 

259 

-95% 

19 

4,084 

380 

-91% 

4th Quartile 

(>30,000 μg/ft2

) 

N 

GM Pre 

GM 1 Yr 

% Change 

8 

276,482 

50,113 

-82% 

13 

105,430 

1,605 

-98% 

44 

113,829 

1,559 

-99% 

188 

73,953 

331 

-100% 

5 

57,406 

228 

-100% 

All N 

GM Pre 

GM 1 Yr 

% Change 

56 

2,860 

1,630 

-43% 

122 

1,178 

266 

-47% 

147 

6,605 

679 

-90% 

675 

5,881 

266 

-95% 

34 

2,456 

208 

-92% 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-42 

8.4.3 Pathways of Dust Lead and the Effect of Interventions on Those Pathways 

A Structural Equations Model (SEM) is a means of estimating direct and indirect effects within 

or on a set of interrelated variables. A pre-intervention dust SEM was developed to establish the 

baseline pathways of lead through the home environment. Once the baseline pathways were 

established, a one-year post-intervention dust SEM was created to examine the effects of the lead 

hazard control interventions on the pathways. These analyses help better explain how the 

interventions influenced the changes in dust lead outcomes that were observed.10

8.4.3.1 Pre-intervention Structural Equation Model. The effects of all available pre-intervention 

environmental and demographic data on entry floor, interior floor, window sill and window 

trough dust lead loadings were assessed. Over 70 potential variables were identified (Exhibit 8-

1). Complete data were available to run the pre-intervention dust SEM for 1,401 dwellings. 

The model was developed based on a priori judgments of the likely pathways of lead in the 

home environment. Window trough dust lead was assumed to be able to affect the three other 

surfaces sampled, while window sill dust lead was assumed to be able to affect only the entry 

floor and/or the interior floors. Because entry floors had higher dust lead loadings than interior 

floors and entry floors were assumed to be an intermediate source of leaded dust being tracked in 

from the exterior, entry floors were postulated to be able to affect interior floors. Since the SEM 

allows pathways to move in only one direction, interior floors were not expected to affect any 

other surfaces sampled. 

As displayed in Figure 8-15, all of these expected pathways proved to be significant with one 

exception. Window trough dust lead loadings did not have a direct effect on interior floor dust 

lead loadings. However, because window trough dust lead did directly affect window sill and 

entry floor dust lead loadings, the window trough lead loadings had an indirect effect on the 

interior floor dust lead outcomes. 

At least one of the grantees has argued that because window troughs tend to be physically below 

window sills, the pathway between sills and troughs should be in the opposite direction. The 

Evaluation team considered this argument but felt that because wind currents at a window would 

tend to blow in, because those currents could move dust from the trough up to the sill, and 

because trough lead loadings were much higher than window sill loadings, the pathway as 

originally conceived was appropriate. Likewise, questions were raised about how window sill 

dust lead loadings could directly affect entry floor lead loadings which were sometimes in rooms 

without windows. The pathway may represent interior floor dust lead that is tracked out to the 

entry. 

Several additional environmental factors directly influenced dust lead loadings (Figure 8-15). 

Five factors influenced both entry floor and interior floor dust lead loadings: 1) the surface type 

of the floor (i.e., carpeted, painted or other); 2) surface condition of the floor; 3) the paint lead 

level of interior trim and doors; 4) the interior building condition; and 5) the occupancy status of 

the dwelling. Additional factors that directly influenced interior floor dust lead loadings included 

 

10 A three-year post-intervention SEM was also created but because only a small number of dwellings in the model 

were treated with Interior Strategies other than 05, comparisons between Interior Strategies were not very 

informative. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-43 

the season of dust collection, the market value of the dwelling, and the number of people in the 

dwelling. An additional factor that directly influenced entry floor lead loadings was the size of 

the dwelling living space. 

Seven factors influenced both window sill and window trough dust lead loadings: 1) surface 

condition, 2) paint lead level on windows, 3) building type (e.g., single-unit, 2-3 units, other), 4) 

the exterior building condition, 5) season of dust lead collection, 6) the market value of the 

dwelling, and 7) the occupancy status of the dwelling. Other factors that directly influenced 

window sill dust lead loadings included paint lead level of interior trim and doors and evidence 

of a prior roof leak. Other factors that directly influenced window trough lead loadings included: 

paint lead level of exterior components, frequency of cleaning the troughs and ownership of 

dwelling (e.g., rental v. owner-occupied). 

8.4.3.2 One-Year Post-Intervention Structural Equation Model. A second SEM was created using 

data available at one-year post-intervention. Analysis of the one-year post-intervention data 

focused on the relationship between pre-intervention environmental measures and one-year 

intervention dust lead loadings, as mediated by the lead hazard control. The methodology for 

preparing the model is described in Section 8.2.3.3. 

In addition to the pre-intervention variables, variables representing the intervention (i.e., interior 

strategy levels, any exterior lead hazard control work and any site lead hazard control work) and 

the post-intervention dust lead levels and conditions (e.g., surface condition and surface type of 

surfaces sampled for dust lead and season of dust lead collection at one-year post-intervention) 

were included in the model as possible modifiers of the dust lead pathways (Exhibit 8-1). The 

results of the one-year post-intervention dust SEM are presented in Figure 8-16. Because the 

final variables in the model differed somewhat from those in the multiple regression models in 

Section 8.4.2, the sample size was slightly larger (1,040 dwellings). 

The pathways between dust lead sample types that were observed at pre-intervention were again 

significant predictors for the one-year post-intervention dust lead outcomes. The variable, 

Interior Strategy, had significant effects on one-year post-intervention dust lead loadings for all 

sample types. For window sills and window troughs, Interior Strategy interacted with preintervention dust lead loadings of those sample types. The interactions were similar to the 

interactions presented in Section 8.4.2.2.1. In general, the effects of the interior strategies on 

post-intervention dust lead loadings that were observed using SEM modeling corresponded well 

with the outcomes observed using the multiple regression models. 

Exterior lead hazard control work had a significant effect on the one-year post-intervention 

window sill dust lead loadings, while site lead hazard control work had a significant effect on the 

one-year post-intervention dust lead loadings on both entry floors and interior floors. In all cases, 

the implementation of lead hazard controls was associated with lower post-intervention dust lead 

loadings. 
Figure 8-15: Pre-Intervention Dust Lead Exposure Pathway 

 (Data as of: June 1, 2000) 

 (N=1401) 

Note: Solid line indicates that a statistically significant coefficient was found. 

 All coefficients are significant at P<0.05 

Condition of Painted Floors Occupancy Condition of Hard Floors Paint Lead on Interior Doors/Trims # of Int. Elements with Deterioration Number of People in Home 

Percent of Hard Floors Season of Dust Sample Collection Market Value 

Entry Dust Lead 

 (ug/ft2) 

Floor Dust Lead 

 (ug/ft2) 

Window Trough 

Lead 

(ug/ft2) 

Window Sill Lead 

 (ug/ft2) 

Surface Condition of Window Troughs Building Type Paint Lead on Interior/Exterior Windows Paint Lead on Ext. Other Components Frequency of W ashing Ext. Window Sills Season of Dust Sample Collection Occupancy Market Value # of Ext. Elements with Deterioration Ownership 

Occupancy Surface Condition of Window Sills Building Type Paint Lead on Interior Doors/Trims Market Value Paint Lead on Interior/Exterior Windows # of Ext. Elements with Deterioration Season of Dust Sample Collection Roof Leak 

Occupancy Surface Type of Entry Surface Condition of Entry Floor Paint Lead on Interior Doors/Trims # of Int. Elements with Deterioration Living Space of Dwelling 

GM=43 GSD=7.1 R2=0.47 

GM=4188 GSD=11.2 R2=0.32

GM=38 GSD=6.7 R2=0.62

GM=482 GSD=7.3 R2=0.35

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

8-44
Figure 8-16: One Year Post-Intervention Dust Lead Exposure Pathway 

(Data as of: June 1, 2000) 

 (N=1040) 

Percent of Hard Floors (Phase 01) Building Type Interior Strategy Condition of Floors (Phase 04) Percent of Painted Floors (Phase 01) Ownership Paint Lead on Int. Doors/Trims Site Strategy 

Entryway Dust Lead (Phase 01) Surface Condition of Entry Floor (Phase 04) Interior Strategy Paint Condition of Int. Doors/Trims Site Strategy 

Window 

 Trough Lead  (ug/ft2) 

Phase 04

Window Sill Lead 

 (ug/ft2) 

Phase 04

Condition of Window Sill (Phase 04) Window Sill Dust Lead * Int. Strategy Occupancy Interior Strategy House Age Paint Lead on Interior/Exterior Windows Ownership Paint Condition of Ext. Other Comps Exterior Strategy Season of Dust Sample Collection (Phase 01) 

Window Trough Dust Lead (Phase 01) Window Trough Dust Lead * Int. Strategy Interior Strategy Entry Height in Stories Paint Lead on Ext. Other Components Paint Lead on Interior Doors/Trims Season of Dust Collection (Phase 04) House Age Market Value Ownership 

GM=335 GSD=6.4 R2=0.25

Entry Dust Lead 

 (ug/ft2) 

 Phase 04 

Floor Dust Lead 

 (ug/ft2) 

Phase 04 GM=14 

GSD=4.0 R2=0.24 

GM=12 GSD=4.2 R2=0.50

GM=63 GSD=4.4 R2=0.23

Note: All coefficients are significant at P<0.05 

8-45 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-46 

 

In addition to the direct influence of the intervention variables on the dust lead loadings, the 

surface condition of the surfaces sampled post-intervention was a significant predictor of dust 

lead loadings for all four sample types. Further analysis of surface condition on windows 

demonstrated that the findings reflect both a direct effect of condition and an indirect effect of 

the Interior Strategies. Treatments and surface condition were intercorrelated; higher level 

Interior Strategies tended to result in better surface conditions. Thus, replacement windows 

resulted in lower dust lead loadings in part because the immediate lead exposure source was 

removed and in part because the surfaces were in good (smooth and cleanable) condition. 

Although the findings of the one-year post-intervention dust SEM closely match the findings of 

the four multiple regression models of one-year dust lead loadings, one area of disagreement was 

observed. The multiple regression model for entry floor dust lead identified no significant 

relationship between interior strategy, exterior work or site work and the one-year postintervention dust lead loadings on entry floors. The one-year post-intervention dust SEM 

identified direct associations with Interior Strategies and site work and indirect associations with 

Interior Strategies and exterior work (through window sill and trough dust lead). Estimates of 

entry floor dust lead loadings in dwellings that were treated with Interior Strategy 05 were higher 

than those in dwellings treated with other strategies, controlling for other factors. Interior 

Strategy 05 was significantly different than Interior Strategies 02, 04 and 06/07 and marginally 

significantly different than Interior Strategy 03. 

Discussion 

The advantage to structural equations analyses is their ability to suggest causal chains by 

simultaneously examining outcomes of interest. The one-year post-intervention dust SEM 

suggests that not only are all four dust lead sample types directly influenced by the differential 

effects of the five levels of Interior Strategies, but Interior Strategies indirectly influenced dust 

lead loadings along the dust lead pathways. For example, interior floor dust lead loadings at oneyear post-intervention were both directly influenced by Interior Strategies and indirectly 

influenced by the effect of Interior Strategies on window trough, window sill and entry floor 

post-intervention dust lead loadings. 

The pathway analysis suggests that exterior lead hazard control work has a direct influence on 

window sill dust lead loadings and an indirect effect on floor dust lead loadings. Site lead hazard 

control work directly influenced floor dust lead loadings, but did not affect window dust lead 

loadings. These findings correspond to the results of the multiple regression model for interior 

floors, which identified significant relationships between both exterior and site work and oneyear post-intervention dust lead loadings. 

Because the two multivariate analyses had two different goals and the SEM included certain 

post-intervention variables, the similarity of the predicted effects of the lead interventions in the 

two models offers support to the strength of the findings. At the same time, differences between 

the two models were expected and they should not be seen as exposing problems about either 

analysis. Rather, they point to areas where the conclusions that can be drawn from the findings 

must be viewed with more caution. Specifically, the entry floor findings suggest that because 

these samples are collected from a point where interior, exterior and site treatments all may have 

a significant effect, the ability to discern the exact variables exerting the primary effect is not as 

strong as on other surfaces. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-47 

 

A central premise of the structural equations analyses is that there are causal links between the 

four dust sample types. It is assumed that dust lead loadings on floors are correlated with dust 

lead loadings on windows because the dust on the windows moves from the windows to the 

floors. The results of both the pre-intervention and one-year post-intervention dust SEMs offer 

support to this hypothesis. Both before and after intensive lead hazard remediation, similar 

pathways of dust lead were observed suggesting that a strong relationship exists between the four 

sample types. A practical conclusion from these results would be that the lead exposure sources 

in a dwelling unit must be looked at as a whole system and to reduce floor dust lead loadings, 

lead exposure sources on windows must be addressed. 

An alternative hypothesis should also be recognized. The dust lead loadings on all four sample 

types may be associated post-intervention because the clearance requirements caused contractors 

to clean the dust on all surfaces with a similar intensity. The model results clearly show that the 

dust lead loadings on the four sample types were correlated, but the assumption of causation is 

not a certainty. As presented in Section 8.4.1.3, across the different Interior Strategies, geometric 

mean dust lead loadings on window troughs increased at least ten-fold and geometric mean dust 

lead loadings on window sills doubled and tripled between clearance and six-months postintervention, but entry floor and interior floor dust lead loadings remained fairly constant during 

the same period. Furthermore, no lagging effects on floors was observed, as floor dust lead 

loadings remained stable or declined in the succeeding phases of the study. These data would 

suggest that dust lead loadings on windows could rise significantly without influencing the 

floors. 

Ultimately, whether the reader accepts the pathways presented in the model or not, it must be 

recognized that the pathways from windows to floors contributed just a small percentage of the 

dust lead down the causal chain. Treating all surfaces of concern is important, because only 

treating the ìup-streamî hazards would not result in substantial ìdown-streamî dust lead 

reductions. Consider the Interior Strategy that was most commonly selected by grantees: Interior 

Strategy 05 (window abatement). This strategy was generally associated with the lowest dust 

lead loadings on windows, yet compared with dwellings treated with other strategies, these same 

dwellings had the highest geometric mean one-year post-intervention floor dust lead loadings. 

While window abatement was demonstrated to be the most effective measure to reduce dust lead 

loadings on windows, this treatment would need to be performed in conjunction with treatments 

that influence predictors of floor dust lead (e.g., floor surface type and condition, door and trim 

paint and general interior building condition, as well as exterior dust/soil lead) in order to most 

effectively control that exposure source. 

8.5 EFFECT OF EXTERIOR DUST AND SOIL ON POST-INTERVENTION DUST LEAD LOADINGS

As part of a supplemental project to the Evaluation, members of the Evaluation team collected 

post-intervention exterior dust lead and soil lead samples from 503 buildings to assess the 

relationship between these sources of lead and post-intervention interior dust lead loadings. 

These data were analyzed to determine the pathways of exterior dust lead and soil lead into a 

dwelling and to estimate the magnitude of their effects on interior dust lead loadings. 

The sampling of soil lead and exterior dust lead was not required under the NOFA for the HUD 

LHC Grant Program, but grantees were given the option of collecting soil samples as part of a 

routine lead risk assessment. Recognizing that soil lead levels might influence the interior dust 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-48 

 

lead loadings and ultimately, the observed effects of the intervention, the Evaluation protocols 

encouraged grantees to collect soil samples in a systematic manner at each sampling phase. The 

Evaluation protocols did not include methods for collecting or analyzing exterior dust samples. 

After most pre-intervention data were collected, it became apparent that most grantees had not 

taken the opportunity to test soil. In addition, preliminary post-intervention findings suggested 

that there were unique grantee effects that could not be explained by the available variables. The 

Evaluation team hypothesized that soil lead and exterior dust lead might help explain regional 

effects as well as effects at individual dwellings. HUD agreed to support the collection of both 

soil and exterior dust samples from a subset of buildings enrolled in the Evaluation. Grantees that 

were participating in the extended Evaluation or that still had a significant number of one-year 

inspections to be completed as of 1998 were approached about participating in the this 

supplemental project. Sampling teams from UC collected samples from 12 of the 14 grantees; 

Massachusetts and New Jersey did not participate. The exterior dust and soil samples were 

analyzed at the University of Cincinnati. 

8.5.1 Methodology 

8.5.1.1 Sample Collection. Exterior sample collection occurred during the summer and fall of 

1998 for all grantees except Alameda County and California. At these two sites, sampling 

occurred during February 1999. For most of the housing included in the supplemental project, 

the exterior samples were collected in close proximity to the two- or three-year post-intervention 

sampling visit made by the grantee. For Chicago, Cleveland and New York City, which did not 

participate in the extended Evaluation, exterior samples were collected in close proximity to the 

one-year post-intervention sampling phase. 

Two composite exterior dust samples were collected: an exterior entry sample and a street 

sample. The exterior entry sample was a composite of two to three subsamples from the primary 

entrances to the building. Each subsample was collected from an area that was expected to have 

the heaviest dust lead loading, but not more than six feet from the door. Most commonly, this 

area was the sidewalk immediately adjacent to the doorway or the porch step. The street sample 

was a composite of two subsamples from the street curb in front of the dwelling. These samples 

were generally taken where the front walkway and driveway intersected with the street. 

The exterior dust subsamples were collected by first collecting dust from a one square foot area, 

as outlined by a template of 24 inches by 6 inches in size, using a small scoop and brush. Any 

remaining dust was removed using three passes by a portable hand-held vacuum sampler. All 

collected exterior dust was deposited in a plastic sampling bag for analysis. The exterior dust 

collection method is described in more detail in Clark et al (Clark 2004). 

One composite soil sample was collected from the perimeter of each building.11 The sample 

included a total of 10 subsamples from all sides of the building where soil was present. 

Optimally, subsamples were collected at least two feet away from each other and from the 

foundation of the building. The top half-inch of soil was collected in a core sampling device and 

placed in a plastic sampling bag. When possible, bare soil was collected. 

 

11 A play area or mid-yard soil sample that is commonly collected during lead risk assessments was not collected as 

part of this study because of financial constraints. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-49 

 

UCís Hematology and Environmental Laboratory analyzed all samples. Both exterior dust 

samples and soil samples were prepared for analysis by oven drying each sample to a constant 

weight and then passing it through a 250 μm sieve. Particles less than 250 μm were 

homogenized, and an aliquot was taken for analysis. Analysis was conducted using flame atomic 

absorption. Exterior lead dust results were expressed in terms of both lead loading (i.e., the 

amount of lead by area, or μg/ft2

) and mass concentration of lead (i.e., the amount of lead by 

weight of sample or parts per million- ppm). Soil lead results were expressed in terms of 

concentration (ppm). 

8.5.1.2 Statistical Methodology. A structural equations model (SEM) was fit to the longitudinal 

dust lead data to determine pathways between interior and exterior dust lead loadings and soil 

lead levels. Exhibit 8-1 presents the possible predictors examined in the model. This model is 

referred to as the Exterior Dust/Soil SEM. The Exterior Dust/Soil SEM was developed so that 

the outcome measures from the closest available post-intervention Grantee sampling phase to the 

collection of exterior dust and soil were used as primary outcomes. Forty (40) percent of the 

exterior dust and soil samples were collected closest to the one-year post-intervention sampling 

phase; 32 percent were collected closest to the three-year post-intervention sampling phase and 

16 percent were collected closest to the two-year post-intervention sampling phase. Other 

sampling phases associated with the exterior dust and soil samples were clearance (7%) and sixmonths post-intervention (5%).12

The SEM developed for the pre-intervention dust data was used as a starting point for the 

Exterior Dust/Soil SEM. The predictors of the pre-intervention outcomes established in the preintervention model (see Section 8.4.3.1) were included as predictors of pre-intervention 

outcomes in this post-intervention model. No stepwise inclusion or elimination of variables was 

performed for pre-intervention outcomes. All variables presented in Exhibit 8-1 were included as 

possible predictors of post-intervention dust and soil measures. Backward elimination of 

insignificant predictors of the post-intervention outcomes was performed, followed by forward 

inclusion steps to re-enter, as needed, previously excluded variables.

Descriptive statistics of the results by grantee are presented below. The findings include both 

loading and concentration results for exterior dust lead. In the statistical model, loading was used 

as the measure of exterior and interior dust lead. 

Both the exterior dust lead variables and the soil lead variables were transformed to their natural 

logarithm in the model to normalize their statistical distributions. For 48 percent of the dwellings 

(26% of the buildings) in the model, it was not possible to collect soil samples because of the 

absence of soil on the property. For those buildings, the soil concentration was assigned a value 

of one ppm. (A value of zero could not be used because it could not be transformed into its 

natural logarithm.) 

Because exterior dust and soil sampling was done on a building basis, not a dwelling basis, the 

addition of the exterior dust and soil pathways necessitated accounting for multiple dwellings 

within a building having the same exterior entry dust, exterior street dust and soil lead levels. 

 

12 Although exterior dust and soil samples were collected one year or more after clearance, at 17 percent of the 

dwellings, interior dust samples were not available from that sampling phase. At those dwellings, interior dust lead 

data from the closest available post-intervention sampling phase was used as the outcome measure.
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-50 

 

Furthermore, unlike the reportís other SEMs, which were cross-sectional at one point in time 

after intervention, the exterior dust and soil model included data from various sampling phases 

from clearance to three-years post-intervention. 

8.5.2 Findings 

8.5.2.1 General Descriptive Statistics. A total of 503 buildings were sampled as part this 

supplemental project. All buildings had exterior entry dust samples collected, 494 buildings had 

exterior street dust samples collected and 418 buildings had perimeter soil samples collected. 

The geometric mean exterior entry and street dust lead loadings were 807 μg/ft2

 and 1,833 μg/ft2, 

respectively. The geometric mean exterior entry and street dust lead concentrations were 1,397 

ppm and 295 ppm, respectively. The geometric mean perimeter soil lead concentration for 

buildings with soil samples was 1,017 ppm. 

Table 8-19 presents the median and 10th and 90th percentiles for the exterior dust and soil lead 

measurements. The exterior dust lead levels are presented as both concentrations and as loadings. 

The median dust lead loadings for exterior dust lead were similar to the geometric mean values 

presented above: 1,030 μg/ft2

 at the exterior entry and 1,890 μg/ft2 at the street. For nine of the 

twelve grantees, the median exterior dust loading at the street was higher than at the entry to the 

building. Only Baltimore, Milwaukee and Minnesota had median exterior entry dust lead 

loadings that were higher than their median street dust lead loadings. 

Median exterior dust lead as measured by concentration displayed a different pattern than the 

levels as measured by loading. The median exterior dust lead concentration at streets (308 ppm) 

was lower than the concentration at building entries (1,500 ppm). This pattern was true for all 

twelve of the grantees participating in the Exterior Dust and Soil Project. The median 

concentration value at the street was six times lower than the median loading value (308 v. 1,890 

ppm), while the median concentration value at the building entry was almost 50 percent higher

than the median loading value (1,500 v. 1,050 μg/ft2

). The findings show that the amount of nonleaded dust was much higher at the street than at the building exterior. 

The exterior dust lead findings played an important role in the development of the Exterior 

Dust/Soil SEM. The higher exterior dust lead loadings at the street relative to the exterior 

building entry initially suggested that the leaded dust from the street was carried by foot or by 

the air to the building entry. However, the finding that median exterior dust lead concentrations

at the street were lower than those at the exterior building entry raised questions about that 

assumption. Under the principle that particles move from a level of higher concentration to lower 

concentration, the Evaluation team concluded that the most likely pathway of lead in the exterior 

was from the entry of the building to the street. The Exterior Dust/Soil SEM was developed 

based on this determination. 

8.5.2.2 Model Results. Of the 503 buildings sampled, 289 buildings (and 541 dwellings) had all 

necessary data available to be included in the Exterior Dust/Soil SEM. As reported earlier, these 

buildings included 76 buildings (and 250 dwellings) where soil was not present so no soil could 

be collected. To include these dwellings in the model, each was assigned a soil lead 

concentration of 1 ppm. Table 8-20 presents the number of buildings and dwellings included in 

the model by grantee. 
Table 8-19: Exterior Dust and Soil Lead Concentrations and Exterior Dust Lead Loadings 

Exterior Entry Dust Street Dust House Perimeter Soil 

Concentration (ppm) Loading (

μg/sq ft) Concentration (ppm) Loading (

μg/sq ft) Concentration (ppm) Grantee No. of 

Bldgs 10th 

%tile Median 90th %tile 10th %tile Median 90th %tile 10th %tile Median 90th %tile 10th %tile Median 90th %tile 10th %tile Median 90th %tile 

Alameda County 20 274 539 1,450 12 101 540 101 271 596 96 718 3,620 180 501 1,600 Baltimore 54 644 2,600 9,580 334 2,240 11,100 298 703 2,010 327 1,790 5,900 484 1,040 2,140 Boston 30 821 2,590 7,280 244 1,570 4,960 316 762 1,780 633 5,100 33,700 1,060 2,830 6,470 California 29 211 846 1,570 13 315 2,560 119 323 680 69 532 3,080 205 613 1,380 Chicago 53 487 2,330 11,800 159 1,170 10,800 155 279 494 915 2,680 12,700 480 1,480 3,250 Cleveland 51 764 2,250 5,950 106 2,490 18,000 240 477 1,220 1,420 12,700 48,000 749 1,760 3,930 Milwaukee 50 857 3,160 16,000 213 4,000 29,900 231 439 913 409 2,350 9,790 500 1,550 4,160 Minnesota 56 136 802 5,570 19 881 5,900 35 111 247 115 761 4,940 243 924 2,320 New York City 31 613 2,190 10,500 86 729 4,970 440 941 1,740 368 1,290 4,040 52 73 4,310 Rhode Island 34 178 1,370 5,230 55 645 6,230 32 286 1,240 432 2,000 17,400 185 812 2,220 Vermont 46 51 317 1,330 13 226 3,620 19 70 255 150 1,220 6,520 203 920 1,940 Wisconsin 47 185 627 5,370 26 674 4,990 34 88 402 110 839 5,850 87 753 2,660 All Grantees 503 2,530 1,500 7,520 43 1,030 10,600 52 308 1,100 230 1,890 13,600 270 1,190 3,330 June 2000 Dataset

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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The geometric mean soil lead concentration for all buildings in the model was 1,003 ppm at the 

building perimeter (Table 8-20). This average represents the level for all properties where soil 

was present and does not include properties without soil. Geometric mean soil lead 

concentrations in Boston were more than twice the all-grantee geometric mean, while Alameda 

County, California and Wisconsin had geometric mean soil lead concentrations that were less 

than half of the all-grantee level. 

The geometric mean exterior dust lead loadings for all buildings in the model were 1,633 μg/ft2

at the street and 954 μg/ft2

 at the primary building entries. Exterior dust lead loadings varied 

among grantees. In Cleveland, geometric mean exterior dust lead loadings for both sampling 

locations were twice as high as the loadings for all grantees combined. Boston and Chicago also 

tended to have higher street dust lead loadings, while Milwaukee and Baltimore tended to have 

higher exterior entry dust lead loadings. Conversely, Alameda County and California had 

geometric mean exterior dust lead loadings at both locations that were half those for all grantees 

together. Vermont and Minnesota also tended to have lower exterior entry dust lead loadings. 

The geometric mean exterior dust lead loadings were higher than the geometric mean dust lead 

loading (11 μg/ft2

) measured at the interior entry of the dwelling unit closest to the building 

entry. This finding supports previous evidence that dust lead loadings on building exteriors tend 

to be higher than those on interior entryways (Lanphear 1995). However, the magnitude of the 

percent difference between the loadings (>8500%) is expected to be an overestimate. Because 

the sampling methodologies were different for the two locations (i.e., vacuum sampling versus 

wipe sampling), a more precise comparison between the loadings is not possible. 

Figure 8-17 presents the significant endogenous and exogenous variables that influenced dust 

and soil lead outcomes in the Exterior Dust/Soil SEM. Of interest, exterior entry dust loading 

had a direct effect on both exterior street dust lead loading and interior entry dust loading. 

Through both direct and indirect pathways, exterior entry dust lead also influenced dust lead 

loadings on interior floors. Soil lead concentrations were a predictor of exterior street dust lead 

loadings. 

No variables other than soil lead concentration and exterior entry dust lead loading were 

predictors of exterior street lead loading. Exterior entry dust had three predictors: window paint 

lead levels, exterior paint lead levels and the use of a site/soil intervention. Buildings with higher 

exterior paint lead levels and buildings with no soil treatments had higher exterior entry dust lead 

loadings. Soil lead concentration had one predictor: the use of an exterior intervention. Buildings 

with no treatments to the building exterior were associated with higher soil lead concentrations. 

The exterior entry dust lead loadings had significant yet varying direct and indirect effects on 

dust lead loadings on the interior entry and the other interior floors. Table 8-21 presents the 

effect of increases in exterior dust lead loadings on the ìdownstreamî dust lead loadings. For 

example, a 930 percent increase in exterior dust lead loadings was associated with a 20 percent 

increase in interior entry floor dust lead loadings and a 26 percent increase in other interior floor 

dust lead loadings. As addressed earlier, dust lead loadings on exterior entries were measured 

using a substantially different sampling method than loadings on interior surfaces, so the 

difference in magnitudes of effects may be somewhat misleading. Exterior entry dust lead 
Table 8-20: Geometric Mean Exterior and Interior Dust Lead Loadings (

μg/ft2) and Soil Lead 

Concentration (ppm) 

for Dust SEM-Exterior Dust and Soil

Num. of Buildings

Grantee 

Dwellings 

Exterior 

Entry

GM (GSD) 

Exterior 

Street

GM (GSD)

Soil1 

GM (GSD)

Interior 

Entry

GM (GSD)

Interior 

Floor 

GM (GSD)

Window 

Sill 

GM (GSD) 

Window 

Trough

GM (GSD)

6 Alameda 

County 6 

126 (4) 325 (5) 383 (2) 

n=6 8 (3) 3 (3) 29 (9) 81 (17) 

54 Baltimore 

54 

2,282(4) 1,570 (4) 1,084 (2) 

n=6 44 (3) 56 (4) 76 (3) 527 (4) 

30 Boston 

40 

1,373 (4) 4,895 (5) 2,758 (2) 

n=29 8 (3) 5 (2) 62 (4) 46 (5) 

9 California 

11 

178 (8) 946 (4) 496 (3) 

n=9 8 (3) 7 (3) 32 (5) 112 (10) 

21 Chicago 

25 

1,494 (6) 3,854 (3) 1,476 (2) 

n=20 23 (3) 22 (3) 144 (6) 374 (13) 

10 Cleveland 

43 

3,766 (6) 4,049 (4) 1,636 (3) 

n=9 19 (4) 13 (3) 86 (4) 159 (7) 

28 Milwaukee 

41 

1,821 (9) 2,278 (3) 1,278 (2) 

n=28 13 (4) 9 (3) 161 (4) 1430 (8) 

37 Minnesota 

38 

537 (11) 786 (4) 773 (2) 

n=36 8 (4) 8 (3) 50 (3) 772 (5) 

25 New York 

City 185 

844 (5) 1,052 (3) 1,011 (10) 

n=3 11 (3) 9 (3) 65 (5) 189 (4) 

24 Rhode Island 

37 

518 (8) 2274 (5) 747 (3) 

n=21 6 (2) 5 (3) 36 (5) 118 (4) 

18 Vermont 

29 

281 (8) 1,031 (5) 1,057 (2) 

n=18 6 (5) 2 (10) 33 (5) 618 (5) 

27 Wisconsin 

32 

636 (6) 803(4) 459 (4) 

n=27 3 (9) 2 (4) 18 (3) 77 (5) 

289 All Grantees 

500 

954 (7) 1,633 (5) 1,003 (3) 

n=213 11 (4) 9 (4) 62 (5) 237 (7) 

1 Excluding Buildings without soil 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

8-53
Figure 8-17 

 Post-clearance* Lead Exposure Pathway Including Exterior Dust and Soil Lead 

(Data as of: June 1, 2000) 

 (N=541) 

Note: Solid line indicates that a statistically significant coefficient was found.

 All coefficients are significant at P<0.05.  Soil, exterior street dust, entry dust samples were collected by University of Cincinnati.  Other data were collected by Grantees.  * The housing data that were closest to the exterior dust collection were used.  ** Pre-intervention variable 

Paint Lead on Interior/Exterior Windows**Interior Strategy Exterior Treatment 

Building Type Living Space of Dwelling Interior Floor Dust Lead ** Surface Condition of Floor

Season of Dust Collection 

Windo

w

Trough Lead 

(ug/ft2) 

(Post) 

Window Sill Lead 

(ug/ft2) 

(Post) 

Market ValueInterior Strategy Window Trough Dust Lead **Entry Height in Stories Building Type 

Ownership Building Type Entry Surface Type ** Season of Dust Collection Surface Condition of Entry Floor Surface Condition of Entry Floor ** 

Exterior

Entry Dust Lead

(ug/ft2) GM=982 

GSD=7.1 R2=0.06 

GM=237GSD=6.7 R2=0.20

GM=8.8GSD=4.2 R2=0.51

GM=62GSD=4.6 R2=0.19

Interior 

Entry Dust Lead 

(ug/ft2) 

(Post) GM=11

GSD=4.3 R2=0.24 

Soil Lead

(ppm) 

GM=1043 GSD=2.9 R2

Site Treatment Paint Lead on Exterior Other Components Paint Lead on Int./Ext. Window

=0.34 Exterior Treatment 

GM=1518 GSD=4.3 R2=0.12 

Floor Dust Lead

 (ug/ft2) 

(Post) 

Exterior 

Street Dust Lead 

(ug/ft2) 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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loadings collected by vacuum sampling ranged from 1 to 151,999 μg/ft2

, with 10th and 90th

percentiles of 70 and 10,147 μg/ft2

, respectively. Interior entry dust lead loadings collected by 

wipe sampling ranged from 0 to 2,053 μg/ft2

, with 10th and 90th percentiles of 2 and 65 μg/ft2, 

respectively. 

 

Table 8-21: Percent Increase in Interior Entry and Other Interior Floor Dust Lead 

Loadings by Percent Increase in Exterior Entry Dust Lead Loadings 

Exterior Entry Dust Lead 

Loading 

Percent Increase 

Interior Entry Dust Lead 

Loading 

Percent Increase 

Other Interior Floor Dust Lead 

Loading 

Percent Increase 

14,400%1 47% 60% 

930%2 20% 26% 

500% 15% 20% 

100% 6% 8% 

1

Percent Increase from 10th to 90th percentile (70 to 10,147 μg/ft2)

2

Percent Increase from 25th to 75th percentile (310 to 3,197 μg/ft2) 

Discussion 

The model identifies two significant relationships between lead hazard interventions and soil 

concentrations and exterior entry dust lead loadings: 1) the use of site/soil interventions was 

associated with lower exterior entry dust lead, and 2) the use of exterior building interventions 

was associated with lower soil lead concentrations. Any interpretation of these findings must be 

made with caution, since the causal relationships may be misconstrued. For example, it would 

appear to be incorrect to infer from the model that the use of the exterior building treatments 

caused the lower soil lead concentrations. Masonry multi-unit buildings in Cleveland and New 

York City and masonry rowhouses in Baltimore generally did not have soil at their perimeter and 

these buildings often did not receive exterior lead hazard control interventions because lead 

hazards were not present. Because few other buildings lacked soil, a relationship was identified 

between the buildings having soil or not and the use of exterior lead hazard control treatments. 

When buildings without soil were removed from the model, there was no significant relationship 

between soil lead levels and the use of exterior treatments on the building. 

Further exploration of the relationship between the use of site/soil interventions and exterior 

entry dust samples did not identify anything that would question a causal relationship. At the 28 

buildings with soil interventions, the geometric mean exterior entry dust lead loading (467 μg/ft2

) 

that was less than half those of the other buildings. The exploration found that all of these 

buildings also had exterior building interventions conducted, raising questions about whether the 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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exterior interventions were an important contributor. However, when the 231 buildings without 

soil lead interventions were examined, these buildings had comparable geometric mean exterior 

entry dust lead loadings regardless of whether or not exterior lead interventions were conducted 

(1011 μg/ft2

 v. 1137 μg/ft2, respectively). The model estimated that the use of site interventions 

reduced exterior dust lead loadings by 69 percent and consequently reduced interior entry dust 

lead loadings by 3 percent. 

It may appear contradictory that site/soil interventions would be associated with exterior entry 

and interior dust lead loadings, but that perimeter soil lead concentrations would not be 

associated with either outcome. This could be related to the fact that the soil interventions often 

treated areas other than, or in addition to, the building perimeter. Furthermore, the treatments 

selected often did not remove or otherwise significantly change the soil lead content; the 

predominant treatments were the introduction of ground cover (see Section 5.3.2). 

8.5.3 Summary of Findings 

A direct relationship between exterior entry dust lead loading and interior entry dust lead loading 

was identified. Based on past studies that have demonstrated that dust lead loadings on exterior 

locations are higher than interior locations, it was assumed that exterior leaded dust is tracked 

into the dwelling from the exterior. Because the sampling methodologies for interior and exterior 

dust lead sampling were different, this hypothesis could not be confirmed with the Exterior Dust 

and Soil Project data. However, the fact that exterior entry dust lead loadings were more than 85 

times the interior entry dust lead loadings does not appear to challenge the hypothesis. 

The higher exterior dust lead concentrations at the exterior entry sample locations relative to 

those at the exterior street sample locations suggested that leaded dust migrated from the 

building perimeter to the street. With this pathway predefined, the models did not identify 

exterior street dust as a source of lead for the leaded dust in the dwellings. A pathway where 

exterior street dust lead moves onto the window sill or window trough was not significant. In 

other words, evidence of blown-in lead from the street was not present from these data. 

The analyses highlight the influence of exterior paint on exterior dust lead loadings and the 

subsequent migration of this lead into the building. Exterior paint lead both from the exterior 

cladding and trim and from the windows contributed to the exterior entry dust lead loadings. 

These leaded particles then migrated out to the street or into the building. This finding suggests 

that the deterioration of exterior leaded paint is a significant contributor to both interior and 

neighborhood dust lead loadings. 

The analyses did not identify a significant relationship between perimeter soil lead 

concentrations and exterior entry or interior dust lead loadings. A significant relationship was 

identified between the use of a site/soil lead intervention and the exterior entry dust lead loading. 

Buildings where a site/soil lead intervention was conducted to some area of the property had 

lower post-intervention dust lead loadings on exterior and interior entries and other interior 

floors than those that had no site/soil lead intervention. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-57 

8.6 TREATMENT LONGEVITY

A principal objective of the Evaluation (Objective 6) was to estimate the durability of lead 

hazard control treatments. The Evaluation designers were especially interested in the durability 

of treatments that left lead-based paint in a dwelling following treatment, such as paint 

stabilization. Although the Residential Lead-Based Paint Hazard Reduction Act (Title X of the 

Housing and Community Development Act of 1992) allowed interim controls such as paint 

stabilization to be used in Federally assisted housing, questions remained about the longevity of 

these treatments. The Evaluation offered HUD an opportunity to monitor the durability of these 

treatments for up to three years. The Evaluation also offered an opportunity to compare the 

longevity of encapsulants with non-encapsulating coatings (i.e., paints) and enclosures (i.e., 

materials applied to a lead-based painted surface with mechanical fasteners). 

The longevity of treatments was considered a potential modifier for the effects of treatments on 

dust lead loadings. Dwellings in which interim control treatments failed (i.e., lead-based paint 

became a hazard) were expected to have higher dust lead loadings than dwellings without 

failures, given similar pre-intervention conditions and similar treatments. The Evaluation 

designers were interested in the magnitude of the differences in dust lead loadings. 

During data collection, the Evaluation team recognized that part of the objective could not be 

fulfilled. Data collectors frequently did not follow the protocols for the assessment of treatment 

failures. The types of treatments applied and the components affected were frequently not listed 

during the follow-up inspections. In addition, data collectors used inconsistent standards to 

determine treatment failures. The Evaluation team informed grantees of these issues, conducted 

retrainings, and in some extreme cases, required reinspections of dwellings. On final review, 

however, the treatment longevity data were considered to have too much variability to reliably 

test the effect of treatment failures on longitudinal dust lead loadings. 

Even though the effect of treatment longevity on dust lead could not be assessed, the Evaluation 

team was able to screen out the most questionable data and use the remaining information to 

characterize trends in the longevity of treatments. The differences in assessment standards of 

data collectors may limit this reportís ability to quantify failure rates precisely, but these data 

remain valuable for comparative purposes. This section presents comparisons of failure rates by 

study phase, by type of component and by treatment category. 

8.6.1 Methodology 

When the Evaluation protocols were developed, the assessment of treatment failures after 

clearance was not a common practice in either a research or operational setting. Unlike most 

other study protocols, the development of a reporting form and procedures for the follow-up 

treatment assessments was done without the benefit of examples from prior field or research 

experience. This section reports not only the field assessment methods but also the operational 

issues that were encountered when these procedures were implemented. 

8.6.1.1 Field Assessment Procedures. Post-intervention inspections of treatment durability were 

conducted at each post-intervention phase (i.e., 6-months, 1-, 2- and 3-years post-intervention). 

Because all grantees used Specmaster software to report their treatments (see Section 5.1.2), 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-58 

the data collectors had the ability to print out the list of treatment specifications used in each 

room of the dwelling prior to conducting the inspection. Data collectors were instructed to take 

this list to the dwelling and systematically review the integrity of the treatments. The data 

collector was to identify each treatment that failed, its location, the magnitude of failure (e.g., 2 

square feet), the reason for the failure, and any follow-up treatment that was performed by the 

grantee. 

During training, data collectors were instructed to report all treatments where the physical 

integrity of the lead hazard control measure failed. Data collectors were not asked to assess 

whether the failure created a lead-based paint hazard. This decision was intended to improve the 

analysis of treatment cost-effectiveness. For example, the failure of new replacement windows 

would not be expected to generate a lead-based paint hazard, but it could have an impact on the 

relative cost-effectiveness of the treatment. If a low-cost replacement window was selected that 

was of comparable initial cost to a less effective treatment such as paint stabilization, the window 

replacement would be clearly considered more cost-effective. However, if a significant 

proportion of these low-cost windows were inoperable shortly after installation and repair or 

replacement was necessary at additional cost, then the cost-effectiveness equation would not be 

so obviously favorable to the replacement window. 

Data collectors were asked to record the reasons for treatment failure in order to better evaluate 

the effectiveness of the various treatments. Reasons for treatment failure were characterized 

using the following list of options: 

 * Adhesion failure * Failure of replaced component * Unknown 

 * Physical damage * Inadequate installation/application 

 * Substrate failure * Other 

8.6.1.2 Operational Issues. Certain problems were encountered during the follow-up inspections 

that impacted the final data quality. For example, the original form lacked fields to record the 

magnitude of the treatment failure. This information was later deemed critical if treatment 

failures were to be correlated with dust lead loadings. Therefore, a major revision to the followup inspection form was released to the grantees in August 1996, two years into the Evaluation. 

Additional trainings were provided to grantees about the final protocols, but the changes likely 

confused some of the data collectors. 

Beyond protocol issues, local constraints created barriers for the successful collection of 

treatment failure data. Because data collectors did not have prior experience assessing treatment 

failures, they lacked a frame of reference that would have been helpful to both the Evaluation 

team and the data collectors as they tried to establish common definitions of treatment failures. 

Data collectors also had limited encouragement from the occupants of dwellings to devote the 

time required for a comprehensive inspection. 

These operational issues may help explain why the Evaluation team, during scheduled quality 

control visits, observed data collectors frequently arriving at the dwelling units without a list of 

treatments conducted; moving rapidly through rooms of the dwelling; and ultimately, reporting 

fewer failures than the observer identified. The operational issues may also help explain why 10 

percent of the treatments that failed were not on the list of treatments for the dwelling or why 37 

percent of the units of quantity that failed were not comparable with the units of quantity treated 

(e.g., square feet versus linear feet). 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Due to these problems, the Evaluation team decided that the use of these data to explain dust lead 

loadings was inappropriate. The imprecise documentation of results as well as the variability 

across data collectors was likely to introduce too much error for the treatment failure rate 

variable to be a reliable indicator. 

At the same time, there was no indication that data collectors were systematically reporting 

biased results within a dwelling. For example, data collectors were not looking for failures on 

walls preferentially to trim. They were also not looking for paint failures preferentially to failure 

of replaced components. The lack of bias within a dwelling offered support for a decision to 

present the descriptive statistics for treatment failures. Acknowledging the imprecision of failure 

rates, these data still provide comparative information about treatment failures that should prove 

useful to understanding other results of the Evaluation and conducting future research on 

treatment failures. 

The analysis examined failures to the 25 most commonly used treatment equivalent categories13

(Table 8-22). These treatment categories included the 21 most commonly used interior 

treatments and the four most commonly used exterior treatments. The analysis was restricted to 

25 categories since they would be most representative of treatments of interest. The categories 

represented 96 percent of all lead hazard control treatments (roughly 66,000 of 69,000 

treatments). 

8.6.2 Treatment Failures 

Of the 10,613 treatment failures reported on follow-up inspection forms from six-months to three 

years post-intervention, 1,056 treatments (10%) were not on the associated list of treatments for 

the inspected dwelling. These unmatched treatments were excluded from further analysis. The 

remaining 9,577 treatment failures are further examined in this report. Overall, out of 73,046 

treatments in dwellings with six-month follow-up inspections, 3.4% of the treatments failed. 

Failure rates for other phases were 5.1%, 7.4% and 7.6% for one, two, and three-years postintervention, respectively. 

 

13 As explained in Section 5.1.2, similar lead hazard control specifications were collapsed into categories that were 

expected to have equivalent effects on dust lead generation. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Table 8-22: Top 25 Most Commonly Used 

Individual Lead Hazard Control Treatments 

Rank Treatment Number 

of Times 

Used* 

1 Trim ñ Stabilize Paint 10,025 

2 Window ñ Replace 9,002 

3 Wall/Ceiling ñ Stabilize Paint 7,949 

4 Door ñ Stabilize Paint 6,198 

5 Trim ñ Replace/Remove 4,619 

6 Trim ñ Remove Paint 3,798 

7 Wall/Ceiling ñ Enclose 3,149 

8 Window ñ Wrap Sill/Trough 2,721 

9 Door ñ Replace 2,543 

10 Floor/Stair ñ Enclose (wood/vinyl) 2,382 

11 Window ñ Stabilize Paint 2,323 

12 Exterior ñ Stabilize Paint 2,082 

13 Floor/Stair ñ Stabilize Paint 1,245 

14 Window ñ Remove Component 1,171 

15 Window ñ Replace Sash Only 883 

16 Window ñ Install Jamb Liner 814 

17 Window ñ Remove Paint 788 

18 Exterior ñ Remove Paint 707 

19 Window ñ Repair 673 

20 Exterior ñ Enclose 654 

21 Floor/Stair ñ Refinish 612 

22 Exterior ñ Replace Component 497 

23 Door ñ Remove Paint 496 

24 Door ñ Remove Component 475 

25 Trim ñ Encapsulate 358 

 *Number of Times Used (Per Room) During Interventions. Because not all dwellings were followed 

throughout the course of the study, the number of treatments that were monitored during any one phase 

were less than those reported here. 

Data from: Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Tables C2 and C3 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-61 

8.6.2.1 Treatment Failures by Time after Clearance. The treatment failures increased with time 

after clearance. On average, a dwelling had one treatment failure six months after intervention, 

two failures one and two years after intervention and three failures three years after intervention. 

The median number of failures per dwelling was zero at six months and one year after clearance 

and one at two and three years after clearance, suggesting an unequal distribution of failures. The 

percentage of treatments with a failure increased at each of the four post-clearance phases (6 

months, 1 year, 2 years and 3 years post-intervention): 4%, 6%, 9% and 10%, respectively. The 

14percentage of treatment failures appeared to level off between two years and three years postintervention. 

Interpretation of this trend is somewhat clouded because unlike classic ìsurvivalî analyses, the 

observation of a failure was not a permanent result. If either the grantee or the property owner 

corrected the failure, a treatment failure would not be present at a subsequent phase unless it 

failed again. At each phase of data collection, the treatment was examined without regard to 

previous results. The number of treatment failures reported at each phase after 6 months postintervention included treatments that failed previously and were not corrected,15 plus any 

treatments that failed since the last visit. 

It is important to emphasize that the grantees had no obligations under their LHC Grant 

agreements to conduct any follow-up treatments because maintenance is the duty of the property 

owner. Of the 9,577 failures identified by the inspections, less than 100 (1%) received additional 

treatment from the grantee. While data were not collected about whether specific treatments were 

conducted by the property owners without knowledge of the grantees, anecdotal evidence 

suggests additional work was not often completed. Based on this information, the trends suggest 

that most new failures occurred within the first six months after treatment and the rate of new 

failures declined at each subsequent phase until there was less than a ten percent increase from 

two to three years post-intervention. 

8.6.2.2 Treatment Failures by Component Treated. The components on which treatments were 

most likely to fail were (in order): 1) doors, 2) exterior cladding/porches, 3) floors/stairs, 4) 

windows, 5) interior trim and 6) interior walls/ceilings. These findings support expectations that 

treatments to components that are subject to routine impact, abrasion or weather are more likely 

to fail. Treatments to doors were two to two and a half times more likely to fail than treatments 

to interior trim or interior walls/ceilings. On doors, eight percent of treatments had a failure at six 

months post-intervention and the percentage increased to 18 percent at three years postintervention (Figure 8-18). The percentage of interior wall and ceiling treatments with a 

 

14 The average number of failures at six months and one-year post-intervention was the same in the base Evaluation 

and the extended Evaluation even though the sets of data differed. Therefore, results are not separated by dataset. 

15 Grantees were not required to correct treatment failures under their HUD LHC Grant agreement, although in some 

cases treatments were done. Property owners were expected to be notified of any lead-based hazards that existed at 

the property, but further action was dependant on the responsiveness of the property owner and/or the local 

enforcement agencies. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Figure 8-18: Percentage of Treatments Where at Least One 

Use of Treatment In a Room Failed by Component and 

Month of Post-Intervention Data Collection

0

5

10

15

20

0 12 24 36 48

Month of Post-Intervention 

Data Collection

Percent

Doors

Exteriors

Floor/Stairs

Windows

Trim

Wall/Ceilings

Figure 8-19: Percentage of Paint Stabilization Treatments 

Where at Least One Use Of Treatment Failed by Component 

and Month of Post-Intervention Data Collection

0

5

10

15

20

25

0 12 24 36 48

Month of Post-Intervention 

Data Collection

Percent

Doors

Exteriors

Windows

Floor/Stairs

Trim

Wall/Ceilings
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-63 

failure increased from three percent at six months post-intervention to seven percent at three 

years post-intervention. 

The results for treatments to windows and floor/stairs were influenced by the types of treatments 

that were applied to these components. The majority of treatments applied to windows and 

floor/stairs either replaced the component or enclosed it. All other components were more likely 

to be treated with paint stabilization. Because paint stabilization treatments were more likely to 

fail (see Section 8.6.2.3), the failure rates for windows, and to a lesser extent for floor/stairs, are 

closer to those of doors and exteriors when only the failures of paint stabilization treatments are 

considered (Figure 8-19). Three years after intervention, paint stabilization treatments to doors, 

windows or exteriors were each more than twice as likely to fail than paint stabilization 

treatments to interior trim or interior walls/ceilings. 

8.6.2.3 Treatment Failures by Treatment Class. Treatment failure rates varied by the class of 

treatment. Four classes of treatments were commonly conducted in the Evaluation: paint 

stabilization, component replacement or removal, component enclosure and paint removal. The 

failure rates for these classes of treatments are presented by phase of data collection in Figure 8-

20. 

At six months and one year post-intervention, treatment classes that were most likely to fail were 

(in order): 1) paint stabilization, 2) paint removal and repainting, 3) component 

replacement/removal, and 4) component enclosure. Paint stabilization treatments were three 

times more likely to fail than component replacement/removal or enclosure treatments. Six 

percent of paint stabilization treatments failed at six months post-intervention compared to two 

percent of both replacement/removal treatments and enclosure treatments. 

At two years and three years post-intervention, paint stabilization remained the class of treatment 

most likely to fail, while component replacement/removal treatments were least likely to fail. At 

three years post-intervention, paint stabilization (15% failures) was again three times more likely 

to fail than enclosure treatments (5% failures) and was six times more likely to fail than 

component replacement/removal treatments (2.5% failures). 

As discussed in Section 8.6.1, a failure of a treatment did not necessarily indicate that a leadbased paint hazard was created. Obviously, failures of replaced or removed components would 

not create a lead hazard. Failures of components where the lead-based paint was completely 

removed suggest that the new paint became deteriorated, but no new hazard was created. Even 

failures of enclosures may not have created a hazard if the enclosure was applied to create a 

smooth and cleanable surface rather than to enclose lead-based paint (e.g., a new layer of vinyl 

flooring). Of greatest concern were failures of components treated with paint stabilization, where 

the original lead-based paint may have become deteriorated as part of the failures. 

8.6.2.4 Examination of Failures to Individual Treatment Equivalent Categories. Of the 25 most 

commonly used treatment equivalent categories, six categories were at or above the mean failure 

rate in each of the four post-clearance data collection phases. Two other treatment categories 

were above the mean failure rate during the first two post- clearance phases. The failure rates of 

the eight treatment categories by phase are presented in Table 8-23. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Of interest, the treatment, the treatment category that had the highest percentage of failures in 

each phase was the installation of window jamb liners. Six months after installation, 17 percent 

of the rooms where jamb liners were installed had at least one jamb liner failure. Three years 

after installation, nearly half of the rooms with jamb liners (46%) failed; four and half times the 

average and twice that of the treatment with the next highest failure rate. Just over half of the 

jamb liner failures were attributed to inadequate installation, while 29 percent failed because they 

were physically damaged. 

Of the remaining five treatment categories that were most likely to fail at all four post-clearance 

phases, all were paint stabilization treatments. These treatments covered all components treated 

with paint stabilization with the exception of paint stabilization to interior walls/ceilings. The 

failure rates for paint stabilization treatments to interior walls/ceilings were just under the mean 

failure rate in all four phases. 

Two treatment categories had an above-average failure rate during just the first two postclearance phases: paint removal on doors and exteriors. The failure rates for both of these 

treatment categories were well below average at the dwellings that participated in the Extension 

of the Evaluation. 

Discussion 

This last observation may be due in part to differences in specification definitions. Both of these 

treatment categories included specifications that combined the paint removal with repainting, but 

the paint removal specifications used in dwellings in the Extension did not tend to include 

repainting (i.e., a separate repainting spec was used). Thus, the early failures of these treatments 

appear to reinforce the paint stabilization findings rather than reflect problems with paint 

removal. 

Figure 8-20: Percentage of Treatments Where at Least One Use of 

Treatment In a Room by Treatment and Month of Post-Intervention 

Data Collection

0

5

10

15

0 12 24 36 48

Month of Post-Intevention 

Data Collection

Percent

Paint Stabilization

Paint Removal

Enclosure

Replacement/Removal
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-65 

8.6.2.5 Treatment Failures of Encapsulants. As reported in Section 5.3.1, encapsulation 

treatments were infrequently applied to dwellings in the Evaluation and only trim encapsulation 

was in the top 25 most commonly used treatment categories (Table 8-22) while wall/ceiling 

encapsulation were ranked 30th. Although encapsulants were neither frequently used nor broadly 

applied across the grantee sites, components in over 100 rooms were treated with encapsulants 

on interior trim or interior walls/ceilings. The results for these treatments are presented here with 

the caveat that conclusions drawn from these few data should be made with caution. 

At one year post-intervention, encapsulants appeared to hold up better than paint stabilization, 

but after that, encapsulants generally had a failure rate equivalent to that of paint stabilization on 

both interior trim and interior walls/ceilings (Table 8-24). Both encapsulation and paint 

stabilization treatments on walls/ceilings were more likely to fail than the enclosure of walls. 

8.6.3 Summary of Findings 

Lead hazard control treatments tended to hold up for the three-year period for which they were 

observed. Out of roughly 73,000 treatments in dwellings with six-month follow-up inspections, 

3.4% of the treatments failed. Failure rates for other phases were 5.1%, 7.4% and 7.6% for one, 

two, and three-years post-intervention, respectively. 

The median dwelling in the Evaluation had only one failure two and three years postintervention. On average, 10 percent or less of the treatments had a failure at any of the postintervention phases of the Evaluation. The percentage of treatments that had at least one failure 

per room and yielded lead hazards was even lower because the reports included failures of 

abated surfaces where the original lead-based paint had been removed. 

Failures appeared to level off two years after clearance. For at least the first three years after the 

intervention, failures appeared to occur logarithmically, with the percentage of failures quickly 

rising over the first year after treatment, then more slowly over the next two years. Since most if 

not all of the treatments were expected to last three years, the early slope in failure rates suggests 

that these failures were more attributable to poor installation or poor surface preparation than to 

product failure. For example, inspectors attributed half of the jamb liner failures to inadequate 

installation. 

Comparisons of failures by class of treatment generally followed expected trends. Treatments 

that included paint stabilization were more likely to fail than treatments where lead hazard 

abatement (i.e., component enclosure, removal or replacement) was conducted. Although little 

data on encapsulants were available, the findings suggest that by two years after clearance, 

encapsulants performed similarly to paint stabilization. Although further study is needed, these 

results suggest that encapsulation does not perform better than stabilization. 

The comparisons of failure rates by component supports common assumptions that components 

subject to abrasion, impact or weather are more likely to experience paint failure than other 

components. During each post-clearance phase, paint stabilization of doors, windows and 

exterior components was more than twice as likely to fail than paint stabilization of interior trim 

and interior walls and ceilings. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Although the treatment failure data could not be used quantitatively in the models of 

effectiveness as measured by dust lead loadings, the data were used to identify trends. These 

trends correspond to findings presented earlier in this chapter that identified rising dust lead 

loadings on windows within one year of treatment with lower intensity treatments. One factor 

that may have contributed to these increasing dust lead loadings was the higher rates of paint 

stabilization failure on both windows and building exteriors. 

Table 8-23: Treatment Categories with Above-Average Percentages of Treatments 

that Failed by Phase of Data Collection 

 Six Months 

Post-Intervention 

One Year 

Post-Intervention 

Two Years 

Post-Intervention 

Three Years 

Post-Intervention 

Treatment 

Category 

Treatments 

Inspected

% 

Failed 

Treatments 

Inspected

% 

Failed

Treatments 

Inspected

% 

Failed

Treatments 

Inspected

% 

Failed

WindowJamb Liner 722 17% 713 21% 427 35% 261 46%

DoorStabilization 5334 9% 5307 16% 1825 24% 1414 23%

WindowStabilization 2067 8% 2063 12% 757 21% 651 23%

ExteriorStabilization 1704 10% 1773 13% 663 18% 561 22%

Floor/StairStabilization 1059 8% 1060 11% 352 13% 303 15%

TrimStabilization 8625 4% 8457 6% 2733 11% 2270 11%

ExteriorRem. Paint 546 6% 624 14% 192 6% 168 8%

DoorRem. Paint 407 14% 443 15% 84 5% 68 3%

Data from: Form 25 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Tables 370-03, 370-04, 370-05, 370-06 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Table 8-24: Comparison of Treatment Failure Rates for Encapsulation, 

Paint Stabilization and Enclosure Treatments to Trim and Walls/Ceilings 

 by Phase of Data Collection

 Six Months 

Post-Intervention 

One Year 

Post-Intervention 

Two Years 

Post-Intervention 

Three Years 

Post-Intervention 

Treatment 

Category 

Treatments 

Inspected

% 

Failed 

Treatments 

Inspected

% 

Failed

Treatments 

Inspected

% 

Failed

Treatments 

Inspected

% 

Failed

TrimEncapsulant 217 0% 217 2% 260 12% 267 18%

TrimStabilization 8625 4% 8457 6% 2733 11% 2270 11%

WallEncapsulant 196 2% 174 4% 156 6% 155 8%

WallStabilization 6833 4% 6877 6% 2108 7% 1722 9%

WallEnclosure 2769 1% 2835 1% 563 1% 431 2%

Data from: Form 25 and Specmaster 

Data as of: June 1, 2000 

Source of Data: NCLSH Tables 370-03, 370-04, 370-05, 370-06 with additional analysis 

8.7 EFFECTS ON INDIVIDUAL TREATMENTS ON DUST LEAD LOADINGS

The focus of this chapter has been the effect of different intervention strategies on the 

housing unit as a whole. The analyses previously discussed sought to determine how the 

different intensities of lead hazard control interventions (as defined by interior strategies 

and the presence or absence of exterior or site work) affected the average dust lead 

loadings in a dwelling. Such analyses address the basic questions of lead hazard control 

policy that were raised in the 1990s: can less intensive lead hazard control activities (i.e., 

interim controls) reduce lead hazards and successfully maintain those reductions over 

time, and how do such activities compare with the performance of more intensive lead 

hazard control activities? These analyses are limited in that they do not measure the 

effect of specific lead hazard control treatments. For example, the analyses of strategies 

are not specific enough to compare the effects of installing jamb liners versus replacing 

windows. This section goes beyond the analyses of treatments by intensity (i.e., Interior 

Strategy) and explores the effects of some specific lead hazard control treatments on 

specific building components within rooms. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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8.7.1 Introduction 

Part of Evaluation Objective 4 was to determine the effects of lead hazard control 

treatments on post-intervention dust lead loadings. To accomplish this objective, dust 

lead data were examined by room instead of by dwelling unit. These analyses were called 

room level models. By examining data at the room level, the Evaluation team was able to 

link a specific treatment directly to a specific dust lead result. The room level models 

controlled for the particular conditions of the component of interest, such as the leadbased paint levels and paint and surface conditions within the room and treatments to 

other components in the room. 

Four components (windows, doors, trim, floors) that were addressed with a variety of 

treatments were expected to be of interest. For example, comparisons between the effects 

of door replacement, door paint removal and door paint stabilization on floor dust lead 

loadings were expected to prove useful to select optimal treatments. Initially, a list of 14 

component/dust location combinations (e.g., window treatments on floors, window 

treatments on sills, door treatments on floors, etc.) was developed for exploration. 

However, early investigations had difficulty separating the factors that affect floor dust 

lead loadings in a room. Floor dust lead loadings were simultaneously affected by 

treatments to all four components within the room, as well as treatments to other rooms 

of the dwelling and treatments to the building exterior. Because these treatments were 

often related to each other, attributing a floor dust lead effect to a single component 

proved too difficult to model statistically. 

The 14 combinations of treatments were therefore reduced to six combinations. The 

combinations included: window treatments on window sill, window trough or floor dust 

lead; trim treatments on floor dust lead; door treatments on floor dust lead; floor 

treatments on floor dust lead; and the effect of paint removal from any component in the 

room on floor dust lead. When additional preparatory work was conducted, the 

Evaluation team determined there were an insufficient number of floor treatments to 

conduct an analysis. The Evaluation team also discovered that the trim treatments were 

often difficult to separate because grantees often replaced trim or removed trim paint and 

stabilized trim paint in the same room. As a result, the analyses reported here are limited 

to four treatment/dust location combinations: window treatments on window trough dust 

lead, window treatments on window sill dust lead, window treatments on floor dust lead 

and the effect of paint removal from any component in the room on floor dust lead. 

Because of concerns that the models could not appropriately control for the effect of 

carpeting on floor dust lead loadings, the models measuring effects on floors were limited 

to bare floor samples. 

8.7.2 Methodology 

Room level analyses explored the effect of specific treatments such as window 

replacement or window paint stabilization on individual dust lead loadings on a specified 

component in a room. The effects of the treatments were measured at one-year postintervention and three-years post-intervention. To conduct these analyses, the treatments 

of interest had to be defined and eligible rooms had to be identified. Because fewer 

dwellings participated in the Evaluation Extension, the number of eligible rooms was 

smaller at three-years than at one-year post-intervention. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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8.7.2.1 Selection of Eligible Rooms for Room Level Analyses. In order to be eligible for 

the room level analysis, a room had to have a dust lead loading result for the surface 

being examined (i.e., bare floor, window sill, window trough) at both pre-intervention 

and at the post-intervention period of interest (i.e., one-year or three years postintervention). Like all of the analyses in this chapter, the dwelling unit had to have 

evidence that it passed clearance. The room had to have one of the treatment categories 

described in Section 8.7.2.2 conducted. 

Rooms in dwellings with concurrent work were excluded from analysis. Rooms were also 

excluded when some lead hazard control work was reported as a universal treatment to 

the whole dwelling or when window treatments were reported as an exterior treatment 

and the location of room being treated could not be determined. In such cases, the effect 

of the additional work on the room of interest could not determined, so the room was 

excluded to protect against the additional work biasing the results. 

8.7.2.2 Selection of Treatments for Room Level Analyses. Two different groups of 

treatments are presented in this report: treatments to windows and paint removal 

treatments to any components in a room. The categories of window treatments were 

defined based on a subset of the equivalent treatment categories for effectiveness 

described in Section 5.3.1. Window treatments were divided into four categories for 

comparison: window - replacement, window - jamb liners, window - paint stabilization, 

and window ñ no treatment. The latter category included rooms where the window 

received no treatment other than cleaning16. A fifth category (window-encapsulation) was 

originally considered for analysis but not enough windows (<20) were treated with 

encapsulants to properly assess outcomes. When window treatments were being 

analyzed, paint lead measurements for a window in that room had to available. 

The total number of eligible rooms by window treatment was: window ñ replacement 

(1,366), window ñ jamb liner (93), window ñ paint stabilization (499), and window ñ no 

treatment (1,838). The numbers were smaller in the final dataset because of further 

requirements of the statistical analyses (Table 8-26). A room with more than one of the 

window treatments (replacement, jamb liners or paint stabilization) was classified as 

being treated with the most intensive treatment. Of the 1,366 rooms treated with window 

replacement, less than one percent were also treated with window stabilization (4) or a 

jamb liner (1). Of the 93 rooms treated with a jamb liner, 12 percent (11 rooms) also had 

the window paint stabilized. The Evaluation lacks information to determine whether the 

additional treatments were applied to the same window or a different window in the 

room. On average, two windows were treated per room. 

The rooms used in the room level analysis of the effect of paint removal were selected if 

any component in the room was treated with any one of 27 on-site paint removal 

specifications. Because the purpose of the analysis was to assess the possible negative 

impact of within-room paint removal on dust lead loadings, paint removal that was done 

off-site was not considered. The paint removal treatments were primarily conducted on 

 

16 For these analyses, no treatment was defined as no physical treatments to the window. In order to achieve 

clearance, the window sampling surfaces may have been cleaned. Because of reporting differences from 

grantee-to grantee, windows that were cleaned could not be separated from completely untreated windows. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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trim (23 specs, 875 uses), with some doors (1 spec, 26 uses) and walls (3 specs, 11 uses) 

also treated. In all, 694 eligible rooms had paint removal treatments, while 3,369 rooms 

did not have paint removal treatments. 

8.7.2.3 Statistical Method of Analysis. An examination of factors that could explain the 

variation in dust lead loadings at one year and three years post-intervention based on 

individual treatments was conducted using four separate nested analyses of covariance 

for each post-intervention period. Nested analyses were selected to account for the effects 

in multiple rooms in a dwelling. Each analysis considered a list of variables believed to 

be possible influences on the specific dust lead location given the component treated. The 

variables were categorized into four areas of interest: factors related to the dust sample 

location; factors related to the treated component; factors related to other components 

treated; and other factors. The specific variables considered are listed in Table 8-25. Dust 

lead loadings and paint lead levels were log-transformed. Backward elimination of 

insignificant covariates was performed. Variables were considered significant at a pvalue of 0.05. 

8.7.3 Findings of Room Level Models 

The dataset of eligible rooms at one-year post-intervention allowed for an examination of 

the effects of all four window treatment categories on dust lead loadings. The number of 

rooms available for each category in each of the models is presented on Table 8-26. A 

full description of the differential effects of the window treatments at one-year postintervention is presented in Section 8.7.3.1. At three years post-intervention, the number 

of eligible rooms dropped by 70 to 80 percent in the three models, leaving fewer 

opportunities for comparisons. In the three-year post-intervention window sill and 

window trough models, only window replacement and no treatment remained available 

for comparison. Given the limited number of comparisons, the effects at three years postintervention are only described briefly at the end of Section 8.7.3.1. 

In Section 8.7.3.2, the effects of paint removal from any component in a room on bare 

floor dust lead loadings are presented. At one year post-intervention, 1,768 rooms were 

eligible, with 336 rooms (19%) treated with paint removal. At three years postintervention, 466 rooms were eligible, with 82 rooms (18%) treated with paint removal. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Table 8-25: List of Variables Used in Room Level Models 

Factors Related to the Dust Sampling Location 

Dust Lead Loading of Dependent Variable (Pre-Intervention) 

Surface Type of Dependent Variable (Painted/Not Painted) (Post-Intervention) 

Surface Condition of Dependent Variable (Post-Intervention) 

Interaction of Surface Type and Condition of Dependent Variable 

Interaction of Pre-Intervention Dust Lead Loading of Dependent Variable and Occupancy

Factors Related to the Component Treatment 

Level of Treatment to Component 

 For Window: (Replacement, Jamb Liner, Paint Stabilization, No Treatment) 

 For Paint Removal: (Yes/No) 

Mean Paint Lead Level of Component 

Interaction of Level of Treatment and Mean Paint Lead Level 

Interaction of Level of Treatment and Pre-intervention Dust Lead Loading of Dependent 

Variable and Occupancy1

Interaction of Level of Treatment and Surface Type and Condition of Dependent Variable2

Factors Related to Other Components Treated 

Average Window Trough Dust Lead Loading Outside of Room (post-intervention) 3 

Level of Treatment to Trim/Door4

Mean Paint Lead Level of Trim/Door4

Interaction of Level of Trim/Door4

 Treatment and Trim/Door5 Paint Lead Level 

Level of Treatment to Wall/Ceiling 

Mean Paint Lead Level of Wall/Ceiling 

Interaction of Level of Wall/Ceiling Treatment and Wall/Ceiling Paint Lead Level 

Exterior LHC Work (Yes/No) 

Site LHC Work (Yes/No) 

Other Factors 

Season of Dust Sample Collection (at Post-Intervention) 

Building Type (Single unit, 2-4 units, >4 units) 

House Age (by decade) 

Occupancy Status (Pre-Intervention) 

1

Used Only in Window Treatment Models 

2

Used Only in Models with Window Sill or Trough as Dependent Variable 

3

Used Only in Models with Bare Floor or Window Sill as Dependent Variable 

4

Only Trim included in Models with Window Sill or Trough as Dependent Variable 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-72

 

Table 8-26: Number of Rooms Analyzed 

in the Room Level Models by Window Treatment Category

 

Bare Floor Models Window Sill Models Window Trough 

Models 

Total 

Rooms 

Avail. OneYear ThreeYear OneYear ThreeYear OneYear ThreeYear 

Replacement 1,366 638 181 609 138 406 108

Jamb Liner 93 49 25 42 - 29 -

Stabilization 499 216 51 170 - 125 -

No Treatment 1,838 711 213 359 120 212 66

All 3,796 1,614 470 1,180 258 772 174

Data from: Forms 1, 19 and Specmaster 

Data as of: June 1, 2000 

Source of Data: Descriptive Statistics Associated with Room Level Models

8.7.3.1 Effects of Window Treatments. Figure 8-21 presents the pre-intervention, 

clearance and one-year post intervention geometric mean dust lead loadings on bare 

floors, window sills and window troughs by the window treatment applied. Figure 8-22 

provides the percentage that the geometric mean dust lead loadings declined from preintervention to one year after clearance by window treatment. These results are 

unadjusted statistics and do not reflect the estimated effects after the models accounted 

for all significant factors. 

When the room level modeling was conducted, factors that influenced dust lead loadings 

on all three surfaces at one-year post-intervention were: 

Pre-intervention dust lead loadings log-transformed (lower pre-intervention loadings : 

lower post-intervention loadings); 

 Pre-intervention paint lead levels log-transformed (lower levels : lower loadings); 

Surface condition at post-intervention (better condition : lower loadings); Interaction of 

Pre-Intervention Dust Lead Loading and Occupancy Status at Pre-intervention17; 

Post-intervention trough dust lead loadings (log-transformed) outside room (see Section 

8.7.3.1.3); and 

Window Treatments (see discussion below). 

 

17 See Section 7.3.3.2 about how higher pre-intervention dust lead loadings that are associated with vacant 

dwellings may have influenced this finding. In summary, the differences between dust lead loadings in 

occupied and vacant dwellings at pre-intervention disappear after the intervention. 
Figure 8-21: Geometric Mean Dust Lead Loadings on Bare Floors, Window Sills 

and Window Troughs at Pre-Intervention, Clearance and One-Year Post-Intervention 

Bare Floors

29

22

20 20

10

15

20

13

11 10 9 12

50

353025201510

Replace Jamb

Liner

Stabilize Cleaning

Geometric Mean 

Dust Lead Loadings Pre Clearance 1 Year

Window Sills

259

237

83

105

15

43 49

21

42

136

71 65

0

50

300250200150100

Replace Jamb

Liner

Stabilize Cleaning

Geometric Mean 

Dust Lead Loadings Pre Clearance 1 Year

Window Troughs

5091

20662

469

1095

22

68 98

36

200

1099

155

562

1

10

100

1000

10000

100000

Replace Jamb

Liner

Stabilize Cleaning

Geometric Mean 

Dust Lead Loadings Pre Clearance 1 Year

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

8-73
-96%

-94%

-66%

-49%

-84%

-26%

-38%

-24%

-41%

-61%

-40%

-52%

1 10 100 1000 10000 100000

Geometric Mean Dust Lead (ug/ft2)

Replacement

Jamb Liner

Paint Stabilization

No Treatment

WINDOW TROUGHS

Replacement

Jamb Liner

Paint Stabilization

No Treatment

WINDOW SILLS

Replacement

Jamb Liner

Paint Stabilization

No Treatment

BARE FLOORS

Fi

gure 8-22: Pre-Intervention and One-Year Post-Intervention Geometric Mean Dust Lead 

Loadings (w/Percent Change) on Bare Floors, Window Sills, and Window Troughs by 

Window Treatment

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Window treatments significantly influenced dust lead loadings on bare floors, window sills and 

window troughs. Rooms treated with window replacement had lower one-year post-intervention 

dust lead loadings on window sills and window troughs18 than rooms treated with window paint 

stabilization, window jamb liners or no window treatments. Rooms where the windows received 

no treatment had higher bare floor dust lead loadings at one-year post-intervention than rooms 

where the windows received paint stabilization. Rooms where windows were not treated also had 

higher bare floor dust lead loadings than rooms where windows were replaced, although the 

results were only marginally significantly different (p=0.08). These findings support 

conventional wisdom that window replacement is the most effective treatment for windows and 

that the treatment of windows is an important component of an intervention aimed at reducing 

floor dust lead loadings. 

8.7.3.1.1 Effect of Window Paint Lead Levels on Window Trough Dust Lead Loadings 

Dust lead loadings on window troughs were influenced by an interaction between the window 

treatments and the window paint lead levels. When window paint was stabilized or the windows 

were replaced, the slope of the relationship between paint lead on windows and the window 

trough dust lead loading was not significantly different from zero (Figure 8-23). In other words, 

higher window paint lead levels did not change the effect of these window treatments on window 

trough dust lead loadings. When windows received no treatment or the windows were treated 

with jamb liners, the slope of the relationship was significantly different (positive) from the slope 

for paint stabilization. 

On untreated windows, as window paint lead levels increased, the window trough dust lead 

loadings increased. These findings support the hypothesis that treated windows are unaffected by 

paint lead levels on the windows because the treatments will remain protective for at least one 

year. Untreated windows would be more likely to experience paint deterioration after one year 

and as a result, the paint lead levels would affect the window trough dust lead loadings. 

When windows were treated with jamb liners, as window paint lead levels increased, the window 

trough dust lead loadings also increased. With just 29 rooms treated with jamb liners in the 

window trough lead model, the conclusions that can be drawn about this treatment should be 

made cautiously. However, as reported in Section 8.6, jamb liners had a rate of failure that was 

75 percent higher than the paint stabilization failure rate. The possibility that these failures 

resulted in higher dust lead loadings on window troughs warrants further examination of the 

effectiveness of jamb liners in future studies.

 

18 Window trough dust lead findings presented for a dwelling with the median window paint lead level. See Section 

8.7.3.1.1 for a discussion of interaction between window treatments and paint lead. 
Figure 8-23: Predicted One-Year Post-Intervention Window Trough Dust Lead Loadings by 

Window Paint Lead Level (Quartiles)

0

750500250

1000

0123456

Window Paint Lead Level (mg/cm2)

Window Trough Dust Lead Loading (ug/ft2)

Jamb LinerNo TreatStabilizeReplace

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Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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8.7.3.1.2 Effect of Surface Condition on Dust Lead Loadings 

The post-intervention surface condition of the wiped surface had a significant effect on the dust 

lead loadings in all analyses. Surfaces that were in worse condition had higher dust lead 

loadings. This variable demonstrated the importance of creating and maintaining smooth and 

cleanable surfaces. The Evaluation team realizes that surface condition may be related to the 

treatment that was selected. More intensive treatments such as window replacement were 

expected to create a good surface condition on window sills and window troughs that should 

have held up long after clearance. By including surface condition in the models as an 

independent variable, the magnitude of the effects attributable to the treatments could have been 

altered. An examination of surface condition by type of window treatment suggests that windows 

that were replaced did have better surface conditions on their sills and troughs than windows that 

were treated with other treatments or were untreated (Table 8-27). The surface condition of bare 

floors did not appear to be related to the window treatments suggesting that the surface condition 

variable in this model was less likely to ìoveradjustî the treatment effect. 

Table 8-27: Arithmetic Mean Surface Condition of Wiped Surfaces 

in the Room Level Models by Window Treatment Categories 

 

Bare Floor Models Window Sill Models Window Trough Models 

OneYear ThreeYear OneYear ThreeYears OneYear ThreeYears 

Replacement 1.3 1.2 1.2 1.1 1.0 1.1 

Jamb Liner 1.6 1.3 1.4 - 1.2 - 

Stabilization 1.3 1.2 1.4 - 1.4 - 

No Treatment 1.3 1.3 1.4 1.3 1.4 1.4 

All 1.3 1.2 1.3 1.2 1.2 1.2 

Surface Condition: 1= Good, 2=Fair, 3=Poor 

Data from: Form 19 and Specmaster 

Data as of: June 1, 2000 

Source of Data: Center Table 

8.7.3.1.3 Impact of Dust Lead Loadings Outside the Room on Treatment Effects 

The variable ìAverage Window Trough Dust Lead Loading Outside of Roomî was used in the 

bare floor and window sill models to represent the dust lead that was available to be blown into 

the room (or tracked in) from the exterior. This variable was not included in the window trough 

dust lead models because frequently there was only one trough sample available per dwelling. 

The window trough dust lead loading outside the room was one of the most influential factors in 

both the floor and sill room level analyses. 

After initial analyses were completed, the Evaluation team was concerned about the use of the 

trough variable to represent outside dust sources. As presented in Section 8.5, the exterior dust 

and soil project did not observe a significant relationship between exterior dust lead and window 

trough dust lead loadings, after controlling for all other variables. In addition, there were 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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practical concerns that the window trough dust lead loading in other rooms was too 

intercorrelated with the treatments of interest. Because grantees frequently treated all windows 

throughout a dwelling with a similar treatment, the trough dust lead loadings in other rooms 

would be expected to be as reflective of the effects of the common window treatment as they 

would be of the effects of exterior dust lead. As a result, the Evaluation teamís attempt to control 

for exterior dust may have inadvertently led to overcontrolling for the effects of the window 

treatments. In response to the concerns, the bare floor and window sill models were reanalyzed 

removing outside window trough dust lead leadings as a variable from the final equation. 

The remaining variables in the models continued to be significant after the removal of the 

window trough dust lead loading. However, in both the bare floor model and the window sill 

model, the contrasts between the window treatments changed. In the revised bare floor model, 

rooms with no window treatments had significantly different (higher) floor dust lead loadings 

than rooms treated with either window replacement or paint stabilization. In the revised window 

sill model, rooms treated with jamb liners had significantly different (higher) window sill dust 

lead loadings than rooms with any of the other window treatment categories. This latter finding 

was unanticipated, since jamb liners were expected to perform as well if not better than either 

paint stabilization or no window treatment. However, these findings match the results of the 

trough dust lead model. With 42 rooms treated with jamb liners in the sill model, these results 

offer further evidence that jamb liners, as installed in this Evaluation, did not result in window 

dust lead loadings as low as other window treatments one year after clearance, after controlling 

for all other variables. 

8.7.3.1.4 Impact of Window Treatments Three Years After Intervention 

The number of rooms available for analysis at three-years post-intervention was greatly reduced 

from the one-year post-intervention. In the analyses of bare floor dust lead loadings, the effects 

of all four categories could be compared but with 71 percent less rooms, resulting in 470 rooms 

in the model. The effects of window treatments were only marginally significantly different from 

each other (p=0.07). While differences were not statistically significant, floor dust lead loadings 

in rooms treated with window replacement tended to be lower than in rooms treated with jamb 

liners or no window treatments. 

The reduction in available rooms resulted in fewer categories of treatments being available for 

comparison in the analyses of the impact of window treatment on window sill and window 

trough dust lead loadings. For these analyses, enough data were available to compare the effects 

of window replacement versus no window treatments. Surprisingly, window sill dust lead 

loadings were not significantly different for window replacement versus no window replacement, 

even though the sill dust lead loadings were lower in rooms treated with window replacement 

(p=0.13). However, when the effect of trough lead loadings in another room was removed from 

the model, window replacement did have a significantly different effect on window sill dust lead 

loadings than rooms without a window treatment (p<0.03). 

There was no significant difference between the effect of window replacement and no window 

treatment on window trough dust lead loadings at three-years post-intervention unless preintervention trough dust lead loadings were over 1,750 μg/ft2

. These results may have been 

influenced by a second treatment that was a significant factor in the model: the presence or 

absence of exterior lead hazard control work. The ability of the model to separate the effects of 

window replacement from that of exterior lead hazard control work was inhibited because 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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dwellings receiving window replacement treatments were more likely to receive exterior 

treatments (p<0.01). Ninety-six (96) percent of rooms with window replacement were in 

buildings with exterior lead treatments, as opposed to 52 percent of rooms with no window 

treatments. The effect of exterior treatments may have diluted some of the positive effects 

attributable to window replacement. Taken together, modeling results suggest that dwellings 

treated with both treatments had window trough dust lead loadings that were significantly lower 

than dwellings without either exterior or window replacement treatments, regardless of the preintervention trough dust lead loading. 

8.7.3.1.5 Summary of Effects of Window Treatments on Dust Lead Loadings

The statistical models found a number of significant relationships between different types of 

window treatments and post-intervention dust lead loadings. The challenge for the Evaluation 

team was to postulate whether the descriptive statistics and the statistical models offer enough 

evidence to suggest that specific window treatments caused the lower dust lead loadings. On 

windows, it was easier to create a causal argument because any window treatments would have 

directly affected the clearance window sill and trough dust lead loadings. The same argument 

could not be made for floor dust lead loadings. Furthermore, there were fewer sources of lead 

that were expected to influence longitudinal window dust lead loadings than floor dust lead 

loadings; therefore the post-intervention condition of windows would have been expected to 

have a greater impact on the window dust lead loadings than on floors. 

At one year post-intervention, window sill and window trough dust lead loadings in rooms with 

window replacement were significantly different from those in rooms treated with all other 

treatments. A theoretical causal relationship between the window treatments and the window 

dust lead loadings is also supported by the descriptive statistics. It was expected that window 

replacement would create window surfaces with no lead-based paint in the immediate vicinity, 

while the other treatments would leave leaded paint on the windows that could deteriorate with 

time. The descriptive statistics for the one-year post-intervention window sill model suggest that 

window replacement performed better at clearance; rooms treated with window replacement had 

the lowest final clearance window sill dust lead loadings (15 μg/ft2

) and the largest percentage 

declines from pre-intervention (94%) compared to rooms with other window treatments. The 

rooms treated with window replacement also had the smallest increase in dust lead loadings from 

clearance until one-year post-intervention (27 μg/ft2

). The descriptive statistics for the one-year 

window trough model offered similar findings: rooms treated with window replacement had the 

lowest final clearance window trough dust lead loadings (22 μg/ft2

) and a percentage decline 

from pre-intervention (99.6%) that was the same or larger compared to those in rooms with other 

window treatments. The rooms treated with window replacement also had the second smallest 

increase in trough dust lead loadings from clearance until one-year post-intervention (178 μg/ft2

) 

after window paint stabilization (56 μg/ft2

). 

Both the modeling results and the descriptive statistics suggest that window replacement resulted 

in lower window dust lead loadings than other window treatments. It must be recognized, 

however, that one-year post-intervention geometric mean sill dust lead loadings remained below 

the window sill dust lead clearance standard of the time (500 μg/ft2

) for each of the window 

treatment categories. Only windows treated with jamb liners had one-year post-intervention 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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geometric mean trough dust lead loadings that were above the window trough dust lead clearance 

standard of the time (800 μg/ft2

).19

On floors, the models generally supported a finding that rooms treated with window replacement 

had lower bare floor dust lead loadings than rooms that received no window treatments. Looking 

further, the one-year models identified window treatments as a better predictor of the bare floor 

dust lead loadings than treatments to other components in the room, while the three-year model 

identified trim treatments as the better predictor of those loadings. Further exploration of the data 

in the three-year model found that 78 percent of rooms with window replacement also had trim 

treatments, while just 32 percent of rooms with no window treatments had trim treatments. 

Because grantees tended to treat many components in a room when window replacement was 

conducted, attributing lower floor dust lead loadings to the window replacement alone must be 

made with caution. 

At one-year and three-years post-intervention, the geometric mean dust lead loadings on bare 

floors were the same or similar for rooms treated with window replacement and no window 

treatment (both 12 μg/ft2

 at one-year; 8 and 6 μg/ft2, respectively, at three-years). These levels 

are well below the current EPA floor dust lead standard of 40 μg/ft2

 and could arguably be 

considered well below a level of concern. However, Lanphear et. al (Lanphear1998) identified a 

correlation between floor dust lead loadings and blood lead levels at loadings below the standard

and that more than five percent of the blood lead levels are likely to be greater than 10 ug/dl. 

This study would suggest that differences at these lower levels may well be of practical 

significance. 

The descriptive statistics could also raise questions about how post-intervention results that 

appear quite similar can be significantly different. This finding was largely attributable to the 

fact that rooms treated with window replacement had higher baseline paint and dust lead levels. 

For example, rooms treated with window replacement had pre-intervention geometric mean bare 

floor dust lead loadings that were approximately 50 percent higher than rooms treated with no 

window treatments in the one-year model (31 v. 20 μg/ft2

). Only after considering all other 

factors did a room treated with window replacement have a post-intervention bare floor dust lead 

loading that was at least marginally significantly different (lower) than that in a room with no 

window treatments. Although the results of the statistical modeling met expectations, it must be 

recognized that the findings are partially based on projections that could benefit from further 

analysis in a more controlled study. 

The one-year post-intervention model also identified a difference in effects of window paint 

stabilization and no window treatment on bare floor dust lead loadings. This finding appears to 

go in an expected direction, but a comparison of dust lead loadings at clearance and at one-year 

post-intervention raises questions about causality. In the one-year model, geometric mean floor 

dust lead loadings in rooms treated with window paint stabilization did not change from preintervention to clearance (20 μg/ft2

 at both phases), but then declined 55 percent to a one-year 

post-intervention loading of 9 μg/ft2

. Floor dust lead levels in rooms treated with no window 

treatments declined 35 percent from pre-intervention to clearance (20 to 13 μg/ft2

), but then 

 

19 Although clearance is based on the maximum dust lead loading for all samples in a dwelling, we use the standard 

as a measure for comparison against the geometric mean of the arithmetic mean for a dwelling. Even when the 

geometric mean is below the standard, a percentage of dwellings are expected to exceed the standard. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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remained essentially the same to one-year post-intervention (12 μg/ft2

). Arguably, window paint 

stabilization contributed to the declines in floor dust lead loadings since a smaller amount of 

leaded dust reaccumulating on window sills after windows were stabilized compared to any other 

treatment including window replacement (as reported above). However, it is hard to assert this 

position conclusively given the findings reported in Section 8.7 that almost one in eight rooms 

with window stabilization had a failure to this treatment by one-year post-intervention. 

8.7.3.2 Effects of Paint Removal. A model was developed to explore whether paint removal in a 

room resulted in increased floor dust lead loading due to contamination from the paint removal. 

Work by Farfel and Chisholm in the 1980s demonstrated that if traditional methods of lead 

hazard control including paint removal were conducted without cleaning (other than dry 

sweeping), post-intervention dust lead loadings increased from pre-intervention (Farfel 1990). 

The Evaluation designers theorized that even when final cleaning was required, clearance dust 

lead loadings after paint removal would be higher than those for other treatments because paint 

removal introduces more lead particles into a room, and those particles may be difficult to clean 

up. 

For dwellings in the one-year room level analysis, 16 percent of bare floors in rooms treated with 

paint removal failed initial clearance compared with eight percent of bare floors in rooms 

without such treatments, based on a clearance level of 100 μg/ft2

. After final clearance was 

achieved, the geometric mean bare floor dust lead loading (16 μg/ft2

) in rooms treated with paint 

removal was 60 percent higher than that in rooms without paint removal (10 μg/ft2

). 

Even if dwellings treated with paint removal were more likely to have higher dust lead loadings, 

it was not apparent what the long-term effects of paint removal would be. Paint removal has the 

advantage of creating surfaces that are lead-free. If the dust lead generated at intervention can be 

removed following initial clearance failure or through routine cleaning post-intervention, then 

paint removal may be more successful than other treatments in the long run. However, if the 

newly generated dust lead is not or cannot be removed, then the positive effects of paint removal 

may not be apparent for a long period of time and at least in the near term, an increased risk of 

exposure may result. 

One year after intervention, the geometric mean bare floor dust lead loadings were 11 μg/ft2

 in 

the rooms with paint removal and 12 μg/ft2

 in the rooms without paint removal. The preintervention dust lead loadings in rooms with paint removal treatments were 17 percent higher 

(27 vs. 23 μg/ft2

) than rooms without these treatments. After controlling for other variables 

including the pre-intervention levels, the models determined that rooms where some components 

had paint removed on site did not have significantly different one-year post-intervention bare 

floor dust lead loadings than rooms that did not have paint removal treatments (p=0.08). 

Three years after intervention, the geometric mean bare floor dust lead loading was 6 μg/ft2 in 

rooms with paint removal and 8 μg/ft2

 in rooms without paint removal. For this set of dwellings, 

the geometric mean pre-intervention dust lead loadings were 20 percent higher in rooms with 

paint removal (30 μg/ft2

) than in rooms without paint removal (24 μg/ft2). As at one year, rooms 

where some components had paint removed on site did not have significantly different bare floor 

dust lead loadings at three-years post-intervention than rooms that did not have paint removal 

treatments. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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These findings suggest that by one year post-intervention, rooms treated with paint removal no 

longer had higher dust lead loadings than rooms not treated with paint removal. This remained 

true at three years after clearance. At both periods, rooms treated with paint removal were 

estimated to have dust lead loadings roughly 5 to 14 percent lower than those in rooms treated 

with no paint removal, a difference that was not statistically significant. The results support the 

conclusion that while paint removal is more likely to increase floor dust lead loadings at 

clearance, there does not appear to be a long-term detrimental effect on dust lead loadings. The 

geometric mean bare floor dust lead loading declined 5 μg/ft2

 between clearance and one-year 

post-intervention in rooms treated with paint removal, while bare floor dust lead loadings 

increased 2 μg/ft2

 between clearance and one-year post-intervention in rooms without paint 

removal. 

A limitation of the analysis is that paint removal treatments were often only a portion of a broad 

set of treatments applied to a room. On average, 19 linear feet of paint was removed from rooms 

analyzed with one-year dust lead data and 14 linear feet of paint was removed from rooms 

analyzed with three-year dust lead data. These treatments were accompanied in some rooms with 

similar quantities of trim or other components being replaced and/or stabilized. The findings 

presented may not be representative of the outcomes that might be expected from the grantee that 

on average removed 64 linear feet of paint per room using on-site paint removal. 

While these room level analyses could assess differences over time between rooms treated with 

paint removal and rooms not treated with paint removal, they could not assess the effects of paint 

removal against other specific treatment categories. The comparison groups included rooms 

treated with the complete range of treatments from abatement by component replacement to no 

treatment other than cleaning. The mixture of treatments both in rooms treated with paint 

removal and in rooms without paint removal made it impossible to determine how paint removal 

compared with other abatement treatments that were less likely to generate leaded dust during 

the intervention or to interim controls that left lead-based paint in the room. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

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Exhibit 8-1: List of Variables Used in 

Pre-Intervention and Post-Intervention Dust Lead Models 

Lead Hazards 

Pre-intervention Variables: 

Entryway Dust Lead Loading a

Surface Type of Entry Floor (Hard, Painted or Carpet) a

Surface Condition of Entry Floor a

Average Interior Floor Dust Lead Loading b

Percent of Painted Floors b

Percent of Hard Floors b

Percent of Carpeted Floors b

Percent of Painted Floors * Average Surface Condition b

Percent of Carpeted Floors * Average Surface Condition b

Percent of Hard Floors * Average Surface Condition b

Average Window Sill Dust Lead Loading c

Average Surface Condition of Window Sills c

Percent Painted Window Sills c

Average Window Trough Dust Lead Loading d

Average Surface Condition of Window Troughs d

Percent Painted Window Troughs d

*Percent Dust Collected in Same Room for Each Component 

(Entries, Floors, Window Sills, Window Troughs) 

Average Paint Lead on Interior Doors/Trim (Mean of Log(XRF)) 

Average Paint Lead on Windows (Mean of Log(XRF)) 

Average Paint Lead on Exterior Components (Mean of Log(XRF)) 

Average Paint Condition of Interior Doors/Trim 

Average Paint Condition of Windows 

Average Paint Condition of Exterior Components 

Interaction between Paint Lead Loading and Paint Condition for Each Component 

 (Interior Doors/Trim, Windows, Exterior Components) 

*Interaction between % Dust Collected in Same Room and Dust Lead Loading (Pre-Intervention) for 

Each Component (Entries, Floors, Window Sills, Window Troughs) 

Interaction of Surface Type and Condition of Entry Floor a

*Post-intervention Variables: 

Entryway Dust Lead Loading 

Surface Type of Entry Floor (Hard, Painted or Carpet) 

Surface Condition of Entry Floor 

Average Interior Floor Dust Lead Loading 

Percent of Painted Floors 

Percent of Hard Floors 

Percent of Carpeted Floors 

Percent of Painted Floors *Average Surface Condition 

Percent of Carpeted Floors * Average Surface Condition 

Percent of Hard Floors * Average Surface Condition 

Average Window Sill Dust Lead Loading 

Average Window Trough Dust Lead Loading 

Average Surface Condition of Window Sills

Average Surface Condition of Window Troughs 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-84

Exterior Street Dust Lead (ug/ft2) *** 

Exterior Entry Dust Lead (ug/ft2

) *** 

Soil Lead (ppm) *** 

Pre-Intervention Building/Dwelling Condition 

Number of Interior Elements with Deterioration (0,1,2) 

Roof Leak (Yes/No) 

Plumbing Leak (Yes/No) 

Number of Exterior Elements with Deterioration (0,1,2) 

Living Space of Dwelling at Pre-intervention (sq. ft) 

Entry Height in Stories 

Market Value 

Household Characteristics 

Pre-intervention Variables:

Was Home Renovated (Yes/No) 

Years of Education of Female Parent (< High School, ≥ High School, Vacant, Unknown) 

Presence of Cleaning Equipment (Percentage of five classes of equipment) 

Frequency of Cleaning the House 

Frequency of Washing Exterior Window Sills d 

Cleanliness of the Home 

(1=Appears clean, 2=Some evidence of cleaning, 3=No evidence of cleaning) 

Household Income ($) 

Number of Children Less than 6 Years 

Number of People between 6-18 Years 

Number of People in Home 

Other Characteristics

Season of Dust Sample Collection (Pre-Intervention) 

*Season of Dust Sample Collection (at Post-Intervention) 

Building Type (Single unit, 2-4 units, >4 units) 

House Age 

Occupancy Status (Pre-Intervention) 

Ownership (1=Rented, 2=Owner occupied, 3=Other) 

**Intervention 

Interior LHC Work (by Strategy) 

Exterior LHC Work (Yes/No) 

Site LHC Work (Yes/No) 

Interaction between Interior LHC Work and Exterior LHC Work 

Interaction between Interior LHC Work and Site LHC Work 

Interaction between No. of Exterior Elements with Deterioration and Exterior Strategy 

Interaction between No. of Interior Elements with Deterioration and Interior Strategy 

Interaction between Entry Floor Dust Lead (Pre-Intervention) and Interior Strategy a

Interaction between Floor Dust Lead (Pre-Intervention) and Interior Strategy b

Interaction between Window Sill Dust Lead (Pre-Intervention) and Interior Strategy c

Interaction between Window Trough Dust Lead (Pre-Intervention) and Interior Strategy d

Interaction between Entry Floor Condition (Pre-Intervention) and Interior Strategy a

Interaction of Average Floor Surface Condition (Pre-Intervention) and Interior Strategy b
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 8-85

Interaction between Average Surface Condition of Window Sills and Interior Strategy c

Interaction between Average Surface Condition of Window Troughs and Interior Strategy d

Interaction between Paint Lead on Interior Doors/Trim and Interior Strategy 

Interaction between Paint Lead on Windows and Interior Strategy 

Interaction between Paint Lead on Exterior Components and Exterior LHC Work 

*Dust SEM ñ 1 Yr only 

**Dust SEM- 1 Yr and Multiple Regression models 

***Dust SEM- Exterior Dust/Soil only 

For Multiple Regression Models: a These variables were used only in ìentryî model. 

b These variables were used only in ìfloorî model. c These variables were used only in ìwindow sillî model. 

d These variables were used only in ìwindow troughî model. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

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9-1

9.0 EFFECTS OF INTERVENTIONS ON CHILDRENíS BLOOD LEAD 

9.1 INTRODUCTION

When the Evaluation was designed, it was recognized that there are important limitations to 

using childrenís blood lead levels as a measure of lead hazard control effectiveness. Lead can 

enter a childís blood stream from many sources beyond those affected by the environmental 

interventions funded by HUD. For example, blood lead levels can also be affected by the childís 

nutrition and can vary with the age of child and season of the year. The introduction to the 

Evaluation study design protocols further noted that: 

ìFinally, chronically lead-poisoned children may continue to have elevated blood 

lead levels for months or years after exposure has ceased due to body stores that 

usually decline very slowly. Thus, monitoring changes in blood lead levels after 

environmental intervention may underestimate the primary preventive benefit of 

exposure reduction in a treated dwelling from birth onward. For this reason, the 

most important outcome measure for this evaluation will be changes in dust lead 

loading in dwellings undergoing environmental intervention.î 

Despite these limitations, blood lead data, in conjunction with data on changes in environmental 

conditions in dwellings, are relevant and useful outcome measures. Over the period of one to 

three years after the interventions, reductions in household lead hazards should be reflected in 

blood lead level reductions. Previous studies of lead hazard control interventions identified 

declines in blood lead levels on the order of 18-34 percent from pre-intervention to six to 12 

months post-intervention (EPA 1995b; EPA, 1998). This chapter explores the effects of the 

interventions conducted in the Evaluation on blood lead levels at the four post-intervention 

collection periods (6-months, 1-year, 2-years, and 3-years post-intervention). 

The Evaluation designers were also interested in analyzing the effects of treated dwellings on the 

blood lead levels of children who were enrolled after intervention (Objective 7b). The designers 

were especially interested in children born into the dwellings, because there were (and continue 

to be) few studies that examine the effects of treated homes on children who have not been 

previously exposed to lead in the environment (i.e., effects of primary prevention). However, 

only 23 children were identified who were born into the dwelling after intervention and provided 

at least one blood lead sample. The enrolled cohort was too small to pursue analyses of the 

effects of primary prevention. 

9.2 METHODOLOGY

For parents who agree to participate, blood lead testing of resident children between the ages of 

six months and six years is a requirement of the HUD LHC Grant Program. However, neither the 

presence of a child nor the participation of the child in the Evaluation is a requirement for a 

dwelling unit to be eligible for HUD LHC Grant funds. During the first two funding rounds of 

the HUD LHC Grant Program, blood lead testing was to be conducted prior to intervention, 

immediately after intervention and 6 and 12 months after intervention. Blood lead levels were 

primarily to be used to measure the safety and effectiveness of the lead hazard control activities 

that the grantees selected. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 

9-2

9.2.1 Blood Collection Methodology 

The Evaluation protocols required the collection of the pre-intervention blood lead sample occur 

within six weeks prior to the lead hazard control intervention. This sample would serve as a 

baseline level for each child. Grantees were allowed to substitute a previously collected blood 

lead sample from a child for the pre-intervention sample if the earlier blood sample result was 

verified by the grantee through the release of medical records. 

As described in Section 7.4.1.2, the protocols required the collection of an immediate postintervention blood lead sample to help determine if the child had a blood lead increase that may 

have resulted from any aspect of the intervention or occupant protection activities. The findings 

related to this blood sample are reported in Section 7.4. 

The Evaluation protocols specified that following intervention, blood lead samples would also to 

be collected at 6 and 12 months after the date of clearance. When HUD approved the extension 

of the Evaluation, the protocols were amended to require additional blood lead samples be 

collected at two-years and three-years after the clearance date, for those children living in homes 

participating in the extension. 

Trained phlebotomists obtained blood specimens from participating children, primarily using 

venipuncture methods. On a case-by-case basis, if a venous sample could not be obtained, the 

phlebotomist could collect a capillary sample instead. Three grantees, Milwaukee, Vermont and 

Wisconsin, received approval to use capillary sampling (fingerstick) as their primary blood 

collection method. Phlebotomists at these three sites were trained in proper fingerstick 

techniques. Sixty-six percent of all blood samples were collected by venipuncture. Among 

samples that were collected at both pre-intervention and one-year post-intervention and both preintervention and two-years post-intervention, 93 and 97 percent, respectively, were collected 

using the same sampling methodology. 

Each grantee selected its own laboratory (or laboratories) to analyze the blood specimens. Each 

laboratory was required to meet the proficiency standards set under the Clinical Laboratory 

Improvement Act of 1988. Lead was measured by either graphite furnace atomic absorption 

spectrophotometry or anodic stripping voltametry. The procedures for the quality assurance for 

blood lead samples and the procedures for the substitution of blood lead values below the levels 

of detection are presented in Section 3.2. 

9.2.2 Statistical Methodology 

Of the 1,766 children who were enrolled in the Evaluation prior to intervention and who lived in 

dwellings that were treated and passed clearance, 1,273 children had a valid pre-intervention 

blood lead test reported. Valid blood lead tests included samples collected under the study 

protocols as well as blood lead results reported by the parent that could be verified by medical 

record. Blood lead results were considered invalid when samples were analyzed during a period 

when the blood analysis laboratory did not meet the Evaluation quality control standards. Valid 

blood lead tests came only from children whose age fell between six months and six years at 

enrollment, the acceptable age range for enrollment of a child in the Evaluation. 

The availability of a valid pre-intervention blood lead result was a requirement for all 

longitudinal analyses of blood lead levels in this report. Thus, the 1,273 children described above 

form the starting point of any longitudinal analysis of childrenís blood lead levels up to one-year 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 

9-3

post-intervention. Of these children, 367 lived in grantee sites that did not participate in the 

extension of the Evaluation, so a maximum of 906 children were eligible for the longitudinal 

analysis of childrenís blood lead levels between two and three-years post-intervention. 

Longitudinal blood lead findings are presented at two levels: descriptive statistics of the blood 

lead levels across time and statistical model analyses of the effect of treatment strategies on 

blood lead results over time. The Evaluation team had originally planned to examine blood lead 

results at two points in time: one-year after the intervention and three-years after the 

intervention. However, the number of children with both pre-intervention and three-years postintervention blood lead results was too limited1

 to draw firm conclusions about three-year results. 

Three-year blood lead data were considered in only one statistical model. Descriptive statistics 

are presented at one-year and two-years post-intervention. 

Two methods of statistical modeling were employed to examine variables influencing postintervention blood lead. Repeated measures and structural equations models were fit to the 

longitudinal blood lead data to determine predictors of blood lead levels. Exhibit 9-1 presents the 

possible predictors examined in the models. 

All lead variables (i.e., blood, dust and paint) were transformed to their natural logarithm to 

normalize their statistical distributions. An individual blood lead result was only included in a 

model when data for the set of predictors under consideration for that result were present. The 

blood lead data of children, who according to their caregiver received medical chelation 

treatments prior to enrollment, were included in the statistical models. Because only four 

children meeting the criteria were chelated, the inclusion of their blood lead results should not 

affect the outcomes. 

Blood lead results were analyzed statistically when post-intervention blood and dust lead 

samples were collected eight weeks before or after the six-month target date, and ten weeks 

before or after the one-, two- and three-year post-intervention dates. The original study protocols 

called for samples to be collected within two weeks of the target dates to limit the variation in the 

passage of time from intervention. Grantees were not always successful in obtaining a sample 

within the collection window because of the practical difficulties when scheduling appointments 

with families. After data had been submitted to the Evaluation, the acceptable collection 

windows were revised in order to balance the goals of the original protocols with the need to 

retain data. On average, blood lead samples were collected one week after the target dates at each 

of the four post-intervention data collection phases. 

The SAS procedures PROC GLM and PROC SYSLIN were used to run the repeated measures 

(RM) and structural equations (SEM) models, respectively. Volume I of the Compendium 

presents a detailed explanation of how each model was developed and run. 

 

1

 Ninety-five children who were between 6 months and 6 years at enrollment and lived in dwellings that passed 

clearance had both a pre-intervention and three-year blood lead sample. This number would be further reduced for 

statistical modeling purposes because of factors such as missing variables, samples collected outside of protocol 

specified collection window, and other model specific restrictions. For the 78 children who met the age and 

clearance criteria, and whose three-year post-intervention blood lead test was collected within the +/-10 week 

collection window, geometric mean blood lead loadings declined 40% from pre-intervention to three year postintervention. There was no significant difference between the geometric mean blood lead levels at 2 years and 3 

years post-intervention while controlling for pre-intervention blood lead. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 

9-4

9.2.2.1 Repeated Measures Model. A RM model used the blood lead results of each child in a 

dwelling at each phase as the outcome. The model is referred to as a ìrepeated measures modelî 

due to the fact that multiple children per dwelling and multiple phases of blood results per child 

are included and accounted for in the model. This report presents the results of an analysis of 

blood outcomes at six-months, one-, two- and three-years post-intervention for dwellings in the 

extended Evaluation (Blood RM-Extended Evaluation). Backward elimination of the possible 

predictors in the model (see Exhibit 9-1) was performed. The variable interior lead hazard 

control strategy was forced into the model to allow for a test of its potential effects in the final, 

reduced models. 

 

9.2.2.2 Post-Intervention Structural Equations Model. A Structural Equations Model (SEM) is a 

means of estimating direct and indirect effects within or on a set of interrelated variables. To 

examine longitudinal effects of the treatments on blood lead levels, an SEM was created that 

included blood lead as a primary outcome at one-year post-intervention (Blood SEM-1 Yr). The 

analysis explored the relationships between the pre-intervention and post-intervention 

environmental and blood lead measurements, as mediated by the intervention itself. 

Under the constraints of the SEM methodology, variables associated with only one child per 

dwelling can be analyzed. The Evaluation team chose the youngest child who had lived in the 

dwelling for at least three months prior to enrollment. 

A SEM developed for the pre-intervention data (pre-intervention Blood SEM) was used as a 

starting point for the model that utilized the post-intervention data. The predictors of the preintervention outcomes established in the pre-intervention model (see Section 9.2.2.3) were 

included as predictors of pre-intervention outcomes in the post-intervention model. No step-wise 

inclusion or elimination of pathways was performed for pre-intervention outcomes. All variables 

specified in Exhibit 9-1 were included as possible predictors of post-intervention outcomes. 

Backward elimination of insignificant predictors of the post-intervention outcomes was 

performed, followed by forward inclusion steps to re-enter, as needed, previously excluded 

pathways. The variable interior lead hazard control strategy was forced into the Blood SEM-1 

Yr model. However, if interior strategy was not a significant variable, it was not included in the 

final output figures. 

9.2.2.3 Pre-intervention Structural Equations Model. The use of a cross-sectional SEM is well 

suited for analysis of lead exposure data because it is capable of showing the direct and indirect 

pathways that occur in the movement of lead in the environment. While the Blood SEM-1 Yr 

described above examined effects only at one-year post-intervention, this model also involved 

longitudinal linkages to the pre-intervention data and therefore could be used to test hypotheses 

regarding the stability or change in lead levels from those observed pre-intervention. In order to 

explore the possible changes in pathways, the pre-intervention Blood SEM had to be developed 

to establish the baseline pathways of lead through the home environment to a childís 

bloodstream. 

Pre-intervention environmental, family, demographic, and child data were used to develop the 

pre-intervention Blood SEM. Blood lead level was an endogenous variable, meaning that the 

sources of variation in pre-intervention blood lead levels were determined by other variables in 

the model. These other variables included exogenous variables (e.g., paint lead levels, childís 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 

9-5

age) that were not controlled for by the model and four other endogenous2

 variables (e.g., preintervention window sill dust lead). Over 70 potential variables were identified (Exhibit 9-1). 

Complete data were available to run the pre-intervention Blood SEM for 459 children. Like the 

Blood SEM-1 Yr, the output of this model was a list of factors considered to have a direct or 

indirect statistically significant influence on blood lead levels. ìSignificant influenceî was 

defined as a 95-percent probability that the factor had an effect on blood lead levels. 

The model accounted for 44 percent of the variance in blood lead. As shown in Figure 9-1, ten 

factors were determined to have a direct and significant influence on childrenís blood lead levels 

at pre-intervention (presented in order of percent variance explained): 

• Parental report of the child previously being lead poisoning (15.6%), 

• Childís age (cubic function)3 (3.6%), 

• Childís race (3.1%), 

• Education of the principal female caregiver (2.0%), 

• Paint lead levels on windows (1.8%), 

• Market value of dwelling unit (1.4%) 

• Season of blood sample collection (1.1%), 

• Percent of sampled window troughs that were painted (1.0%), 

• Surface condition of entry floor (0.6%), and 

• Interior floor dust lead loadings (0.6%). 

Of the explained variance, 13 percent could not be attributed independently to any single 

variable. Of the ten significant variables, four environmental factors ó lead paint loading on 

windows, percent of sampled window troughs that were painted, surface condition of entry floor, 

and interior floor dust lead loading --- were found to directly and significantly affect childrenís 

pre-intervention blood lead levels. 

Several additional environmental factors indirectly influenced blood lead levels (Figure 9-1). 

Through their direct or indirect influence on interior floor dust lead loadings, the entry floor, 

window sill and window trough dust lead loadings had an indirect bearing on blood lead levels. 

The paint lead loading on interior doors/trim, windows and exterior components; the condition of 

paint on the interior doors/trim; and exterior building condition indirectly affected blood lead by 

directly affecting dust lead loadings. The condition of the sampled surface also indirectly 

influenced blood lead levels by directly influencing dust lead loadings at all dust sampling 

locations. 

These direct and indirect pathways of lead in the childís home to the child formed the baseline 

for further analysis. These effects and changes to these effects post-intervention are discussed in 

further detail in Sections 9.4.5 and 9.4.6. 

2

 Dust lead loadings at the four locations previously investigated using the Dust SEM (see Chapter 8) were the other 

endogenous variables in the model; however, factors influencing dust lead loadings are discussed in this chapter 

only in terms of their subsequent influence on pre-intervention blood lead levels. With more dwellings available for 

the Dust SEM, that model provides more accurate information concerning factors significantly influencing dust lead 

loadings. 

3

 A cubic function was used because blood lead levels have been shown to rise rapidly until a child is about two to 

three years of age and then decline at a less rapid rate. The ìage effectî is further discussed in Section 9.4.5.3. 
. 

Figure 9-1 

Pre-Intervention Lead Exposure Pathways Including Blood Lead (HUD Evaluation Project) 

(Data as of: June 1, 2000) 

 (N = 459) 

Note: Solid line indicates that a statistically significant coefficient was found.

 All coefficients are significant at P<0.05 

 Entry Dust Lead 

 (ug/ft2) 

Floor Dust Lead 

(ug/ft2) 

Blood Lead 

(ug/dl) 

 Window Sill 

 Lead 

 (ug/ft2) 

 Window Trough

Lead

 (ug/ft2) 

Entry Surface TypeSurface Condition of Entry Floor Living Space of Dwelling Paint Lead on Interior Doors/Trims 

Percent of Hard Floors Condition of Painted Floors Paint Condition of Int. Doors/Trims

Parent Report Previous Lead PoisoningRace Female Education Paint Lead on Interior/Exterior Windows Market Value Child's Age, age2, age3Season of Blood Sample Collection Percent Painted for Window Troughs Surface Condition of Entry Floor 

Surface Condition of Window TroughsBuilding Type Paint Lead on Interior/Exterior Windows Season of Dust Sample Collection 

Paint Lead on Interior Doors/TrimsSurface Condition of Window Sills # of Ext. Elements with Deterioration Paint Lead on Ext. Other Components 

GM=19GSD=4.9 R2=0.33

GM=22 GSD=4.9 R2=0.29

GM=8.3GSD=2.1 R2=0.44

GM=312GSD=6.4 R2=0.19

GM=5310 GSD=12.1 

R2=0.36 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

9-6 
. 

 

9-7

9.3 DESCRIPTIVE STATISTICS OF LONGITUDINAL BLOOD LEAD LEVELS

This section presents information on the overall effectiveness of the HUD LHC Grant Program 

on childrenís blood lead levels post-intervention as measured by unadjusted results. One set of 

descriptive statistics is presented for the children who had valid blood lead results available in 

each of the first four sampling phases of the Evaluation (pre-intervention, immediate postintervention, 6-months and one-year post-intervention). A second set of descriptive statistics is 

presented for the children who had valid blood lead results available in each of the first five 

sampling phases of the Evaluation (the four previously described plus two-years postintervention). The Evaluation team required a child to have blood lead results in all sampling 

phases in order to observe trends across the phases, yet avoid the possible bias introduced by 

mixing in results from children who later dropped out of the study.4 

9.3.1 One-Year Post-Intervention 

Twenty-five percent (321) of children with valid blood lead tests at pre-intervention had four 

consecutive phases of valid blood lead tests reported. There was a wide variation in the retention 

rates of children by grantee. Wisconsin and Boston retained 62 and 47 percent of their children, 

respectively. Vermont, California, Alameda County and Chicago had more difficulty retaining 

children: retention rates ranged from two to seven percent. While some of the variation in 

retention rates is the result of varying local mobility patterns and other factors outside of the 

control of the grantee (e.g., percentage of owner-occupied dwellings), local grant programs 

managed by health programs had a higher retention rate (30%) than programs managed by 

housing departments or housing and health department collaborations (14%). 

For the 321 children, there was an overall reduction of 2.7 μg/dL (27%) in geometric mean 

blood lead levels from pre-intervention levels (9.9 μg/dL) to one-year post-intervention (Figure 

9-2). Blood lead levels slightly decreased between pre-intervention and immediate postintervention (on average 4 months later) and then declined at a fairly steady rate over the 

following two consecutive six-month sample collection periods. The declines in blood lead 

levels from pre-intervention to immediate post-intervention were not significant, while declines 

during each successive sampling phase were statistically significant (p< 0.01). Between 

immediate post-intervention and one-year post-intervention, geometric mean blood lead levels 

declined 25 percent. 

Because of the higher retention rates at certain sites and because these same sites generally 

enrolled more children per dwellings, the blood lead findings tend to reflect a subset of grantees 

and a subset of their Evaluation dwellings. Just six of the grantees had at least 20 children with 

valid blood lead samples for the four phases through one-year post-intervention. Eighty-five 

percent of the children lived in Milwaukee (23%), Wisconsin (23%), Minnesota (14%), 

Cleveland (9%), Baltimore (8%), and Boston (7%). The geometric mean blood lead levels for 

these grantees are presented on Figure 9-2. While children at these grantee sites began with 

4 The total number of children that had blood lead collected at both pre-intervention and the post-intervention phases 

were: 647 at six months post-intervention, 471 at one-year post-intervention, 143 at two-years post-intervention, and 

95 at three-years post-intervention. 
. 

Figure 9-2: Geometric Mean Blood Lead Levels (μg/dL) from Pre-Intervention to One-Year PostIntervention by Sampling Phase and Grantee

50

201510

Pre- Immediate Post- Six Months Post- One-Year PostSampling Phase

Geometric Mean Blood Lead Level (μg/dL) CLMN BOML ALL BAWI

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

9-8
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 

9-9

varying levels of lead in their blood, the patterns for blood lead reduction are similar across 

grantees. Geometric mean blood lead levels declined between 17 and 31 percent between 

immediate post-intervention and one-year post-intervention across the grantees. 

It is of great interest that there were substantial declines in blood lead levels (20%) for grantees 

where the geometric mean pre-intervention blood lead levels were less than 10 μg/dL. Earlier 

studies had not demonstrated positive effects of interventions on blood lead levels for children 

with initial levels less than 20 μg/dL (Swindell 1994; EPA 1997a; Aschengrau 1998). The 

effects of interventions on lower pre-intervention blood lead levels is examined in Section 9.4.5. 

Dwellings treated with Interior Strategies 04 and 05 heavily influenced the findings (see Table 9-

1 for strategy definitions)5

. The 264 children living in these homes accounted for 78 percent of 

these data. 

9.3.2 Two-Years Post-intervention 

Two-years post-intervention, there was an overall reduction of 3.8 μg/dL (37%) in geometric 

mean blood lead levels from pre-intervention levels (10.2 μg/dL) for the 89 children with all five 

phases of blood lead available (Figure 9-3). Among this population, blood lead levels were more 

likely to decline between pre-intervention and immediate post-intervention (on average 4 

months) than in the population of children in the one-year post-intervention analysis. The decline 

in blood lead levels between pre-intervention and immediate post-intervention was significantly 

different (p=0.02). In this population, blood lead levels appeared to decline at a faster rate during 

the first 6 months (2.0 μg/dL per year) than in the following next 6 months (1.4 μg/dL per year) 

and the period between one and two-years post-intervention (0.6 μg/dL per year). The declines 

in blood lead levels during each successive post-intervention sampling phase were statistically 

significant (p< 0.01 through one-year; p=0.02 between one-year and two-years postintervention). Between immediate post-intervention and one-year post-intervention, geometric 

mean blood lead levels declined 25 percent. Between one-year and two-years post-intervention, 

geometric mean blood lead levels declined an additional 9 percent. 

The 89 children who made up this population represented 10 percent of the children with preintervention blood lead tests that were potentially eligible for the two and three year extension of 

the Evaluation. This value somewhat underestimates the actual retention rate because not all of 

the 906 children from grantees participating in the extension of the Evaluation lived in homes 

that were eligible for the extended study. Seventy-nine percent of the children lived in three 

grantee sites (Milwaukee (37%), Minnesota (26%), and Boston (16%)). The geometric mean 

blood lead levels for the three grantees were similar, as were the trends across phases (Figure 9-

3). Geometric mean blood lead levels declined 38 percent between immediate post-intervention 

and two-years post-intervention in both Boston and Milwaukee, while they declined 23 percent 

in Minnesota during the same period. 

Two-years post-intervention, dwellings treated with Interior Strategies 04 and 05 continued to 

heavily influence the findings. Children living in these homes accounted for three quarters of the 

blood lead data collected in all five phases. 

5

 See Section 5.2 for a more detailed description of dwelling unit interventions. Effects of Interior Strategies 01, 06-

07 are not presented in this chapter because less than 20 children with serial blood lead tests lived in dwellings 

treated with these interventions. 
. 

Figure 9-3: Geometric Mean Blood Lead Levels (μg/dL) from Pre-Intervention to TwoYears Post-Intervention by Sampling Phase and Grantee

50

1510

Pre- Immediate Post- Six Months Post- One-Year Post- Two-Year PostSampling Phase

Geometric Mean Blood Lead Level (μg/dL) ALL

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

9-10
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-11 

 

Table 9-1: Interior Strategy Code Definitions 

Strategy Definition 

Interior 01 No Action 

02 Cleaning, Spot Paint Stabilization Only 

03 Level 02 plus 

Complete Paint Stabilization, Floor Treatments

04 Level 03 plus 

Window Treatments

05 Level 04 plus 

Window Replacement, Wall Enclosure/Encapsulation

06 All Lead-Based Paint Enclosed, Encapsulated, or Removed 

(Meets Public Housing Abatement Standards)

07 All Lead-Based Paint Removed

Glossary of Treatments

Encapsulation - The application of a covering or coating that acts as a barrier between lead-based paint and the 

environment, the durability of which relies on adhesion and which has an expected life of at least 20 years. 

Enclosure - The application of rigid, durable construction materials that are mechanically fastened to the substrate to 

act as a barrier between lead-based paint and the environment. 

Paint Stabilization - The process of repainting surfaces coated with lead-based paint, which includes the proper 

removal of deteriorated paint and priming. 

Paint Removal - The complete removal of lead-based paint by wet scraping, chemical stripping, or contained 

abrasives. 

Removal/Replacement - The removal/replacement of a building component that was coated with lead-based paint. 

Window Treatments - The process of eliminating lead-containing surfaces on windows that are subject to friction or 

impact through the removal of paint or enclosure of certain window components. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-12 

 

9.4 TREATMENT EFFECTIVENESS

A principal goal of the Evaluation (Objectives 7 & 9) was to measure the effects of the 

intervention strategies on blood lead levels at each post-intervention phase of the study. Study 

protocols called for the use of statistical models to assess potential modifiers and confounders of 

the relationship between intervention strategy and blood lead levels. In particular, the effects of 

baseline blood lead levels, childís age and season of blood testing were to be examined. Two 

multivariate statistical analyses were performed to explore the factors that significantly affected 

longitudinal blood lead levels: the Blood SEM-1 Yr and the Blood RM-Extended Evaluation. 

9.4.1 General Characteristics of the Children and Their Homes 

Table 9-2 presents the general characteristics of the children and their homes for the children 

included in the models compared with the general Evaluation population. The post-intervention 

models retained 155 and 296 of the 1,273 children with pre-intervention blood lead tests. Certain 

characteristics of these children differed from the general Evaluation population. Children in the 

models were more likely to be White and less likely to be Black or Hispanic. Children in the 

models were more likely to live in single-family homes and owner-occupied homes. The 

geometric mean floor dust lead loading in the homes in the models was 17-18 μg/ft2

 compared 

with 24 μg/ft2

 for the general Evaluation population. 

The pre-intervention geometric mean blood lead levels of the children in the post-intervention 

models (8.5 and 8.9 μg/dL) were similar to those levels of children in the general Evaluation 

population. However, the pre-intervention geometric mean blood lead levels of the children in 

the model populations were lower than the pre-intervention geometric mean blood lead levels of 

children with complete data through one-year (9.9 μg/dL) and two-years post-intervention (10.2 

μg/dL)(see Sections 9.3.1 and 9.3.2). 

The changes in blood lead levels over time observed across the analytical models generally 

corresponded to the 18-34 percent declines observed in previous lead intervention studies (EPA 

1995b, EPA 1998). Geometric mean blood lead levels declined 1.8 μg/dL (20%) from preintervention (9.0 μg/dL) to one-year post-intervention for the 155 children in the Blood SEM1Yr. Blood lead levels for children in the Blood SEM-1Yr declined less between preintervention and one-year post-intervention than in the general descriptive statistics (20% v. 

27%, respectively). The difference may be attributable to the SEM eligibility requirement that 

limited the analysis to the youngest child in each dwelling. As explained in more detail in 

Section 9.4.5, a population of younger children who tend to have lower pre-intervention blood 

lead levels would be more likely to exhibit lower declines in blood lead levels than a population 

of older children with higher pre-intervention blood lead levels. In the Blood RM-Extended 

Evaluation, geometric mean blood lead levels declined an estimated 1.9 μg/dL (23%) from preintervention to one-year post-intervention. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-13 

 

Table 9-2: Characteristics of Children in the Blood Models 

Factors Children 

w/initial Blood 

Tests 

Blood SEMPre-Intervention

Blood SEMOne-Year PostIntervention Blood RMExtended 

Evaluation 

N (children) 1,273 459 155 296 

Age (mean) 

(months) SD 

40.1 

17.9 

34.4 

16.7 

32.0 

16.1 

42.0 

17.6 

Gender-Female 

 

628 

(49%) 

233 

(51%) 

75 

(48%) 

151 

(51%) 

Race Asian 

 Black 

 Hispanic 

 White 

 Other 

9% 

48% 

15% 

24% 

4% 

7% 

40% 

14% 

34% 

5% 

5% 

36% 

11% 

41% 

6% 

10% 

34% 

9% 

41% 

6% 

Pre-Int. (GM) 

Blood Lead GSD 

(μg/dL)

8.7 

2.1 

8.2 

2.1 

9.0 

2.2 

8.5 

2.1 

Previous Report of Lead 

Poisoning 

32% 29% 32% 25% 

Owner-Occupied 38% 47% 60% 57% 

Single-Family Building 43% 42% 54% 60% 

Pre-Int. Floor GM 

Dust Lead GSD 

(μg/ft2) 

23.5 

5.0 

18.9 

4.9 

17.6 

4.3 

16.7 

4.2 

Interior 02 

Strategy 03 

 04 

 05 

 Other 

10% 

15% 

27% 

46% 

2% 

9% 

11% 

19% 

60% 

1% 

8% 

10% 

21% 

60% 

10% 

10% 

26% 

54% 

Data from: Forms 1, 5, 9, 19, 23 

Data as of: June 1, 2000 

Source of Data: Descriptive Statistics of Models and NCHH Table of Pre-Intervention Results 

9.4.2 Effect of Interventions on Post-Intervention Blood Lead Levels Without 

Consideration of Other Factors 

Table 9-3 presents the geometric mean blood lead levels by phase and interior strategy for all 

children who had all four phases of blood testing conducted from pre-intervention to one-year 

post-intervention6

. Geometric mean blood lead levels for children living in homes treated with 

Interior Strategies 04 and 05 declined 22 and 28 percent, respectively, from pre-intervention to 

one-year post-intervention. The 43 children (13%) living in homes treated with Interior Strategy 

 

6

 No children eligible for the post-intervention blood lead analyses lived in dwellings treated with Interior Strategy 

06/07. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-14 

 

Table 9.3: Geometric Mean Blood Lead Levels (μg/dL) from 

Pre-Intervention to One-Year Post-Intervention by Sampling Phase 

and Interior Strategy 

 Interior Strategy 

Sampling Phase 02 03 04 05 

 

Pre-Intervention GM 9.8 10.9 13.9 7.8

 GSD 2.0 1.7 2.0 2.0

 

Immediate GM 9.6 9.5 13.3 7.9

Post-Intervention GSD 1.9 1.9 2.0 1.9

Six Months GM 8.3 8.1 12.1 6.8

Post-Intervention GSD 1.9 1.8 1.8 1.8

One-Year GM 7.9 6.9 10.0 6.1

Post-Intervention GSD 1.9 2.0 1.9 1.8

 

Number of Children 33 43 90 174

 

 

GM= Geometric Mean 

GSD= Geometric Standard Deviation 

 

Data From: Forms 5, 9 and 23 

Data as of: June 1, 2000 

Source of Data: UT Table 420-I 

03 had greater percent declines in geometric mean blood lead levels from pre-intervention to 

one-year post-intervention (37%). The 33 children (10%) living in homes treated with Interior 

Strategy 02 had smaller declines in geometric mean blood lead levels from pre-intervention to 

one-year post-intervention (19%). 

Associations existed between the pre-intervention blood lead levels, the interior strategies and 

post-intervention blood lead levels. For example, children living in dwellings treated with 

Interior Strategy 04 had the highest blood lead levels at all four phases, while children living in 

dwellings treated with Interior Strategy 05 had the lowest blood lead levels at all four phases. 

This association is addressed in further detail in Section 9.4.3. 

The geometric mean blood lead levels by phase and interior strategy were also examined for the 

89 children who had all five phases of blood testing conducted from pre-intervention to twoyears post-intervention. Geometric mean blood lead levels for children living in homes treated 

with Interior Strategies 04 and 05 declined 42 and 31 percent, respectively, from pre-intervention 

to two-years post-intervention. Blood lead levels in homes treated with Interior Strategy 04 fell 

from 12.5 μg/dL to 7.3 μg/dL, while levels in homes treated with Interior Strategy 05 declined 

from 8.5 μg/dL to 5.9 μg/dL. Only 11 and 9 children living in dwellings treated with Interior 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-15 

 

Strategies 02 and 03, respectively, had blood lead available in the first five phases. Given these 

small sample sizes, the descriptive statistics for these strategies are not presented here. 

9.4.3 Effect of Interventions on Post-Intervention Blood Lead Levels When Considering 

Other Factors 

The multivariate models described in Section 9.4.1 were used to explore the influence of lead 

hazard control interventions on post-intervention blood lead levels when controlling for other 

factors. The Blood SEM- 1Yr was used to examine effects of the interventions on blood lead 

levels at one-year post-intervention. The Blood RM ñ Extended Evaluation was used to examine 

the influence of interventions on the changes in blood lead levels over the three years of 

Evaluation. 

9.4.3.1 Effects of Interventions on One-Year Post-Intervention Blood Lead 

Factors that influenced one-year post-intervention blood lead levels (based on the Blood SEM1Yr) were: 

• Pre-intervention blood lead levels (log-transformed); 

• Childís Age (cubic function); 

• Childís Race 

• Parental Report of Previous Lead Poisoning of the Child; 

• Cleanliness of the Home (pre-intervention); 

• Exterior Building Condition (pre-intervention); and 

• Interaction between Exterior Paint Lead Level and Exterior LHC Work 

Children with higher pre-intervention blood lead levels had higher post-intervention blood lead 

levels. Details concerning the effect of the childís race and age on post-intervention blood lead 

levels are provided in Section 9.4.5. Children with a parental report of being previously lead 

poisoning had significantly higher post-intervention blood lead levels, even after controlling for 

the pre-intervention blood lead level. Children living in homes with more deteriorated exterior 

components prior to intervention also had significantly higher post-intervention blood lead 

levels. Surprisingly, children living in homes judged by interviewers to be less clean prior to 

intervention had lower post-intervention blood lead concentrations. 

Of interest, the variation in interior lead hazard control treatments as measured by Interior 

Strategy was not a significant predictor of post-intervention blood lead levels. However, postintervention blood lead levels were associated with dwellings where exterior lead hazard control 

work was conducted, as long as the average pre-intervention exterior paint lead loading was 

taken into consideration. Figure 9-4 presents the estimated one-year post-intervention blood lead 

levels by Exterior Work (Yes/No) and pre-intervention exterior paint lead loadings when setting 

all variables to their mean values. The variation in exterior paint lead levels had a significant 

effect on the blood lead levels when no exterior work was conducted. Higher exterior paint lead 

loadings in dwellings without exterior work were associated with higher post-intervention blood 

lead levels. Children living in dwellings where exterior lead hazard control interventions were 

done had lower blood lead levels at one-year post-intervention than in dwellings without the 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-16 

 

treatments (all other factors being equal), but those differences were only significant when the 

mean exterior paint lead loading at pre-intervention was about the 90 percentile (7.0 mg/cm2

). 

Also of interest, none of the concurrent dust lead loadings in the dwellings were significantly 

associated with post-intervention blood lead levels. The pathways from environmental sources 

that had been found to be significant predictors of the childrenís pre-intervention blood lead 

levels were not significant predictors of the childrenís blood lead levels measured twelve months 

after the interventions were performed. Further discussion of the effect of interventions on the 

lead exposure pathways is found in Section 9.4.6. 

9.4.3.2 Effects of Interventions on Changes in Post-Intervention Blood Lead. 

Factors that influenced changes in post-intervention blood lead levels (based on the Blood RMExtended Evaluation) were: 

• Pre-intervention blood lead levels (log-transformed); 

• Childís Age (cubic function); 

• Parental Report of Previous Lead Poisoning;

• Season (considered as a sinusoidal effect); and

• Phase

Blood lead levels significantly declined with time. A seasonal effect that was observed prior to 

intervention continued to be observed post-intervention. Children had higher blood lead levels in 

the late summer and lower levels in the late winter. 

As observed in the one-year post-intervention model, Interior Strategy was not a significant 

predictor of post-intervention blood lead levels. In addition, the use of exterior and/or site 

treatments was not significantly related to those blood lead levels. 

Figure 9-4: Predicted One-Year Post-Intervention Blood Lead by 

Exterior Paint Lead Loading and Exterior Work (Yes/No) 

6

6.5

7

7.5

8

8.5

9

9.5

012345678

Exterior Paint Lead Loading (mg/cm2

)

One-Year Post-Intervention 

Blood Lead (ug/dL)

NO

YES
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-17 

 

9.4.4 Discussion of Intervention Findings 

The Evaluation team hypothesized that, given the statistically significant differences observed in 

dust lead loadings by Interior Strategy (see Chapter 8), different Interior Strategies would yield 

differences in post-intervention blood lead levels. Such a finding was not observed. No 

individual interior strategy was related to significant differences in blood lead level. 

For the four interior strategies that were examined in the blood lead models (Interior Strategies 

02-05), window sill and window trough dust lead loadings were dramatically lower in dwellings 

treated with Interior Strategy 05. However, interior floor dust lead loadings were not 

significantly lower in these same dwellings. Assuming interior floor dust lead is the primary 

exposure pathway of dust lead to a child, as established by the pre-intervention model, this 

finding may suggest a reason why Interior Strategy 05 did not prove to be more effective than 

the other interior strategies. At the same time, the lack of significant differences between Interior 

Strategy 05 and the other strategies remains somewhat surprising, given the fact that this strategy 

would have removed the environmental factor most predictive of pre-intervention blood lead - 

lead-based paint on windows. 

The observation in the Blood SEM- 1Yr that children living in dwellings where the exterior paint 

lead levels were above 7 mg/cm2

 and the exteriors were treated had lower post-intervention 

blood lead levels suggests that exterior lead hazard control is an important component of a lead 

hazard control plan. The fact that this finding was not also observed in the repeated measures 

model limits the strength of the conclusion, but it highlights an area where further research 

should take place. 

9.4.5 Factors Modifying Treatment Effects 

9.4.5.1 Pre-intervention Blood Lead Levels and Parental Report of Previous Lead Poisoning. 

Previous studies of the effects of lead hazard control interventions on childrenís blood lead levels 

reported that post-intervention blood lead levels are significantly related to the pre-intervention 

blood lead levels (EPA 1995b). Childrenís blood lead levels are affected by both the lead in the 

external environment and by lead that previously entered and became stored in the body (i.e., the 

body burden) (Nordberg 1991; Rabinowitz 1991). Lead present in the tissues of the body, 

especially the bones, can be released into the blood stream during periods of reduced exposure to 

external lead sources. As a result, it is expected that the blood lead levels of children who have 

previously been exposed to lead will have higher blood lead levels than children who had not 

been previously exposed even if they were living in the same home environment. 

Pre-intervention blood lead levels of children were significantly associated with the postintervention blood lead levels. Furthermore, a child whose caregiver reported that the child was 

lead poisoned prior to intervention had significantly different post-intervention blood lead levels 

than a child whose caregiver did not report that the child had been lead- poisoned. The children 

who had been lead-poisoned, as reported by their caregivers, had higher post-intervention blood 

lead levels after controlling other variables, including pre-intervention blood lead levels. 

In the Blood SEM- 1Yr, a ten percent increase in pre-intervention blood lead levels resulted in a 

predicted increase in one-year post-intervention blood lead of five percent. A child whose initial 

blood lead level was higher than another childís level would continue to have a higher blood lead 

level post-intervention. For example, consider two identical children with all factors being equal 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-18 

 

to the model means except that one child has an initial blood lead level of 9.1 μg/dL and the 

other has an original blood lead level of 10.0 μg/dL. The predicted blood lead level of the first 

child fell to 7.2 μg/dL one-year post-intervention, while the predicted blood lead level of the 

second child was 7.6 μg/dL. 

While controlling for all other factors including pre-intervention blood lead levels, children who 

were reported to be lead poisoned prior to enrollment had higher post-intervention blood lead 

levels. Children whose caregivers reported that they were previously lead poisoned were 

predicted to have post-intervention blood lead levels 31 percent higher than children whose 

caregivers did not report that the they were previously lead poisoned. For example, using the 

Blood SEM-1Yr results, a child whose initial blood lead level was 9.0 μg/dL was predicted to 

have a blood lead level at one-year post-intervention of 8.6 μg/dL if previously lead poisoned 

and 6.6 μg/dL if not previously lead poisoned. 

Discussion 

Two possible limitations must be noted when attempting to quantify the effects of previous lead 

poisoning and initial blood lead levels. First, the pre-intervention blood lead levels and a report 

of previous lead poisoning are not truly independent factors especially at the extremes. Just 5 

percent of children with an initial blood lead level of 5 μg/dL or less were reported to be 

previously lead poisoned, while over 70 percent of children with an initial blood lead level of 15 

μg/dL or more were known by the caregiver to be lead poisoned prior to the intervention. 

A second limitation that may underestimate the effect of pre-intervention blood lead levels on 

post-intervention blood lead levels is the influence of laboratory detection limits. Approximately 

one-quarter of the children with post-intervention blood lead levels had initial blood lead levels 

of 5 μg/dL or less and one-half of those children lived in Wisconsin where the laboratory could 

not detect levels below 5 μg/dL. Any actual declines in blood lead levels would not have been 

reported by the laboratory for half of the children at the extreme end of the distribution of data, 

thereby possibly diminishing the predicted effect of pre-intervention blood lead. 

Although previous studies had found that children with initial blood lead levels below 20 μg/dL 

did not have substantial declines post-intervention (Swindell 1994; EPA 1997a; Aschengrau 

1998), children in the Evaluation with pre-intervention blood lead levels between 10-19 μg/dL 

exhibited blood lead declines of 34 percent at one-year post-intervention (Table 9-4). Table 9-4 

presents unadjusted data for all children who had a blood lead result reported at both preintervention and one-year post-intervention as well as an associated floor dust lead result at each 

sample phase. Changes in blood lead levels were organized by categories of pre-intervention 

blood lead. Across all categories, floor dust lead loadings declined by a similar percentage 

(p=0.34), but blood lead levels varied by pre-intervention levels (p<0.001). For categories with 

pre-intervention blood lead levels at or above 10 μg/dL, changes were similar (p=0.46); the 

geometric mean blood lead levels declined an average of 36 percent or more one-year postintervention. 

9.4.5.2 Childís Race/Ethnicity. At both pre-intervention and one-year post-intervention, the 

childís race/ethnicity was significantly associated with the childís blood lead levels. At both of 

the phases, there were more than 15 children in each of three racial/ethnic groups: non-Hispanic 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 9-19 

 

White, non-Hispanic Black and Hispanic.7

 Children whose parents reported that they were 

Black had significantly higher blood lead levels than children who were reported to be White or 

Hispanic. Controlling for all other significant variables in the models, Black children had blood 

lead levels that were approximately 25 percent higher than White or Hispanic children at both 

phases. 

The relationship between race/ethnicity and childrenís blood lead levels has previously been 

identified in earlier surveys of health (Mahaffey 1982; Pirkle 1998) as well as other 

epidemiologic studies (Charney 1980; Clark 1985; Lanphear 1998). The findings of this 

Evaluation are consistent with earlier findings that Black children had higher blood lead levels 

than White children. Possible reasons for the disparity in blood lead levels by race were 

discussed in Lanphear, 1996b. 

 

Table 9-4: Geometric Mean Pre-Intervention and One-Year Post-Intervention Blood Lead 

Levels and Blood Lead Changes by Pre-Intervention Blood Lead Levels 

PreIntervention 

Blood Lead 

(μg/dL) 

Number 

and 

Percent of 

Children 

Geometric 

Mean PreIntervention 

Blood Lead 

(μg/dL) 

Geometric 

Mean OneYear PostIntervention 

Blood Lead 

(μg/dL) 

Percent Change from 

GM Pre-Intervention 

Blood Lead to GM 

One-Year PostIntervention Blood 

Lead 

Percent Change from 

GM Pre-Intervention 

Floor Dust Leada

 to GM 

One-Year PostIntervention Floor Dust 

Leada

<6b 105 

(25%) 

3.5 3.7 6% -43% 

6-9 98 

(23%) 

7.2 5.6 -22% -64% 

10-14 76 

(18%) 

11.7 7.7 -34% -48% 

15-19 62 

(15%) 

16.5 11.2 -32% -59% 

20-25 38 

( 9%) 

22.4 14.2 -37% -52% 

>25 39 

( 9%) 

31.5 18.1 -43% -51% 

All 418 9.4 7.2 -23% -53% 

a

Floor dust lead levels are represented by the arithmetic mean dust lead loadings for all floors in a dwelling. 

b

For pre-intervention blood lead levels below 6 μg/dL, the increases may be due in part to laboratory detection limitations that

restricted the number of test results that could exhibit observable declines, but did not restrict the number that could increase. 

Data from: Forms 05, 09 and 19 

Data as of: June 1, 2000 

Source of Data: NCHH Table

 

7

 Other racial groups included: Asian, Native American and Other. 
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9.4.5.3 Childís Age. Previous studies have identified a relationship between the age of a child 

and their blood lead levels (Clark 1985; EPA 1996a). For children between the ages of six 

months and six years, blood lead levels tend to rise until a child is 18 to 36 months old and then 

decline. A similar pattern was identified among children in the Evaluation. 

At pre-intervention, the blood lead levels of children in the Evaluation were significantly 

associated with the age of the child. Controlling for all other variables, children six months of 

age (the youngest children enrolled in the study) had the lowest blood lead levels. Blood lead 

levels increased until a child was two years of age and then declined until a child was about four 

and half years old. The effect of childís age was predicted in the statistical models using a cubic 

function that better matched the observed trends. The predicted effect at pre-intervention is 

displayed in Figure 9-5. 

Childís age remained a significant variable in the post-intervention model, with trends following 

a similar pattern as displayed prior to intervention. At one-year post-intervention, two year-old8

children were likely to have higher blood lead levels than they did at enrollment, all other factors 

being equal (Figure 9-6). While the ultimate goal of any intervention is to avoid any increases in 

the blood lead levels, the results of the modeling suggest that these increases were attributable to 

an age effect and not to any increased environmental exposure. The predicted one-year postintervention blood lead levels for children over 10 months of age at enrollment all declined from 

pre-intervention, with the greatest declines for children who were between two and two and a 

half years of age at enrollment. Again these trends match the expected age effects, as these 

children on average would experience a decline from their peak blood lead levels even without 

the intervention. 

Figure 9-7 presents the actual geometric mean blood lead levels at pre-intervention and one-year 

post-intervention by age of the child at enrollment. The graph displays the influence of the age 

effect described above. The graph also offers visual support for the finding that actual blood lead 

levels at one-year post-intervention could not be explained by the age effect alone. No age 

category had a one-year geometric mean blood lead level that was as high as the pre-intervention 

blood lead level in the succeeding category.

 

8

 On average, children were 14 months older one-year post-intervention than at enrollment, so children who were 

approximately two years of age at one-year post-intervention were generally 9-12 months old at enrollment. 
. 

Figure 9-5: Geometric Mean Blood Lead Levels (μg/dL) at Pre-Intervention by Child's Age 

Predicted from Pre-Intervention SEM

9876543210

10

0 12 24 36 48 60 72

Child's Age at Enrollment (months)

Geometric Mean Blood Lead Level (μg/dL)

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9-21
. 

Figure 9-6: Actual and Predicted Percent Change in Blood Lead Levels from PreIntervention to One Year Post-Intervention by Age of Child at Enrollment: Predicted 

from the One Year SEM

62

-32 -28 -33 -27 -29

-20-40

0

604020

0 12 24 36 48 60 72

Child's Age at Enrollment (months)

Percent Change

ActualPredicted

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9-22
. 

Figure 9-7: Predicted Geometric Mean Blood Lead (μg/dL) at Pre-Intervention and One-Year 

Post-Intervention by Age of Child at Enrollment: Predicted from the One Year SEM

4.1

9.6

11.4

9.8

8.8

9.6

6.7 7.1

8.0 7.6

6.6 6.9 8

6420

1210

6-11 12-23 24-35 36-47 48-59 60-71

Child's Age at Enrollment (months)

Geometric Mean Blood Lead Level (μg/dL) Pre-Interv. One-Year Post-Interv.

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. 

 9-24 

9.4.5.4 Sampling Phase. Blood lead levels continued to decline with time after clearance. The 

phase of the blood lead tests was a variable that was tested in only the RM model. In the Blood 

RM-Extended Evaluation model, blood lead levels were significantly different between all 

phases of blood lead sampling except between two-years and three-years post-intervention. For 

the set of children in the Blood RM-Extended Evaluation model, the decline between six months 

and one-year post-intervention was 7 percent. Blood lead levels declined eight percent between 

one-year and two-years post-intervention, and then declined an additional three percent between 

two-years and three-years post-intervention. As noted above, the latter decline was not 

significantly different from no change. The model estimates based on least squared means are 

presented in Figure 9-8. 

With approximately 25 percent of the children reportedly lead poisoned prior to intervention and 

almost one-third of the children having a pre-intervention blood lead level over 15 μg/dL in the 

Blood RM-Extended Evaluation model, it was expected that it would take a long time to detect 

the effects of the interventions on blood lead levels. Following the interventions and the 

reductions of lead in the childís home environment, lead that had been stored in skeletal tissues 

would be transferred into the blood over a period of time. According to one published study, 

children who had prolonged exposure to lead over the first two years of life had an apparent halflife of lead in blood between 20 and 38 months (Manton 2000). The same study found that 

children who were only briefly exposed had an apparent half-life of 8 to 11 months. The latter 

values corresponded to modeled estimates by Rust et al. (Rust 1999) for children older than two 

years. Half-lives of lead in the bone of children 3, 4, and 5 years of age were estimated to be 8, 

10, and 12 months, respectively. Rust et al. estimated that because of bone-lead stores, an 

intervention that reduces a 5 year-old childís external lead exposure by 50 percent might produce 

only a 25 percent decline in the childís blood lead level 12 months following intervention. 

The findings from the Blood RM-Extended Evaluation model support expectations that for many 

of the children in the Evaluation, blood lead levels began to approach equilibrium with their 

environment about two-years post-intervention. Even so, blood lead levels of children who had 

been exposed for prolonged periods continued to decline through three-years post-intervention. 

The Evaluation team recognizes that a portion of the blood lead declines over time may have 

occurred independently of intervention (i.e., because of declines in the lead in the general 

environment). Over the period of data collection (1994-1999) there were small declines in air 

lead levels and air emissions nationally (EPA 2001b). Other sources of lead outside the home 

such as lead in water and lead in food may also have continued to decline during the period 

(Bolger 1996). With neither a control group nor testing of dietary intakes, the Evaluation was 

unable to determine the magnitude or the possible effects of declines of other external lead 

sources on Evaluation children. However, the declines in external lead sources do not appear 

large enough to explain the 18 to 27 percent declines in blood lead levels from pre-intervention 

to one-year post-intervention.
. 

Figure 9-8: Estimated Post-Intervention Geometric Mean Blood Lead Levels (μg/dL) 

by Sampling Phase: 

Predicted from the RM-Extended Evaluation Model 

8.4

7.4

6.5

5.6 5.3

9876543210

Pre-* Six Months Post- One-Year Post- Two-Years Post- Three-Years PostSampling Phase

Geometric Mean Blood Lead Level (μg/dL)

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9-26 

 

9.4.5.5 Date of Testing (Seasonality). The Evaluation team was able to control for the time of the 

year when the blood lead was collected. Previous studies have demonstrated that blood lead 

levels in children tend to peak in the late summer and remain low in the winter (Hunter 1977; 

Rabinowitz 1985; EPA 1996a; Rothenberg 1996). Seasonal variation can be substantial: children 

tested by the Milwaukee Health Department between 1990-93 had blood lead levels 40 percent 

higher in the summer than in the winter (EPA 1996a). Failure to account for the effect of 

seasonal variation could either overstate or understate the impact of the interventions on the postintervention blood lead levels. 

A sinusoidal function was used to predict the effect of season. This function, which assumes 

seasonality is symmetric, can identify the size and timing of seasonal fluctuations. At preintervention, the blood lead levels in the Evaluation were predicted to be 23 percent higher at 

their peak in July than in January. The model-predicted values were somewhat lower postintervention with blood lead levels 14 percent higher in late summer than in late winter. Even 

with the lower predicted seasonal effects at post-intervention, the magnitude of the seasonal 

effect was greater than the magnitude of the change in blood lead levels from six-months postintervention to one-year post-intervention. The relative size of the effect of season compared 

with the effects of the treatment underscores the necessity of controlling for season in these 

analyses. 

9.4.6 Changes in Pathways from Pre-Intervention to Post-Intervention 

As expected from previous studies (Sayre 1974; Bornschein 1985; Davies 1990; Lanphear 1997), 

very strong pathways from dust lead to blood lead were found at pre-intervention (Figure 9-1). In 

the pre-intervention Blood SEM, pre-intervention blood lead levels were directly predicted by 

dust lead loadings on interior floors and indirectly predicted by dust lead loadings on interior 

entry floors, window sills and window troughs. Pre-intervention blood lead levels were also 

directly influenced by paint lead levels on windows and indirectly influenced by the surface 

condition of dust-sampled surfaces. 

Those pathways from environmental sources of lead that were significant predictors of childrenís 

pre-intervention blood lead levels in the pre-intervention Blood SEM were not significant 

predictors of childrenís blood lead at one-year after the intervention (Figure 9-9). Specifically, 

although the relationships among post-intervention dust lead variables were similar to those 

among pre-intervention dust lead variables, the pathway from dust lead to blood lead could no 

longer be detected, suggesting that the interventions were successful in arresting residential lead 

exposure. 

Although the link between concurrent dust lead and blood lead was no longer observable postintervention, it was hypothesized that declines in residential dust lead loadings (as well as the 

correction of deteriorated lead-based paint) resulted in lower blood lead levels. It is likely that 

the relationship could not be observed because the childrenís body burden of lead became a 

better predictor of blood lead level post-intervention than post-intervention dust lead loadings. 

This hypothesis was tested using bivariate analyses of the youngest childís blood lead levels and 

the interior floor dust lead loadings in their dwellings. Only children with both blood lead results 

and floor dust lead results in both phases were included (119 children). An analysis of the pre-
. 

Figure 9-9 

 Twelve-Month Post-Intervention Lead Exposure Pathways Including Blood Lead 

(Data as of: June 1, 2000) 

 (N = 155) 

Percent of Hard Floors (Phase 01) Interior Floor Dust Lead (Phase 01)

Note: Solid line indicates that a statistically significant coefficient was found. 

 Dash line indicates that no statistically significant coefficient was found.  All coefficients are significant at P<0.05

Entry Dust Lead 

(ug/ft2) 

Phase 04 

Floor Dust Lead

(ug/ft2) 

Phase 04

Blood Lead 

(ug/dl) 

Phase 04

Window 

Trough Lead 

(ug/ft2) 

Phase 04

Window Sill 

Lead 

(ug/ft2) 

 Phase 04

Childís Blood Lead Level (Phase 01)Childís Age, Age2, Age3

Race Parent Report Previous Lead Poisoning # of Ext. Elements with Deterioration Cleanliness of the Home (Phase 01) Paint Lead on Ext. Other Components*ext. strategy

Window Trough Dust Lead (Phase 01) Trough Dust Lead * Interior Strategy Paint Lead on Interior Doors/Trims Interior Strategy

Paint Lead on Interior/Exterior Windows Interior Strategy Ownership Window Sill Dust Lead (Phase 01) 

Surface Condition of Entry Floor (Phase 04) Entry Surface Type* Condition (Phase 01) Entry Surface Type Entryway Dust Lead (Phase 01) Interior Strategy Window Sill Dust Lead (Phase 01) Percent Painted for Window Sills (Phase 01)

Surface Condition of Entry Floor (Phase 01) 

GM=15 GSD=5.2 R2=0.37 

GM=67 GSD=4.1 R2=0.37

GM=8 GSD=3.3R2=0.30 

GM=366 GSD=7.5 R2=0.36

GM=7.2 GSD=1.9 R2=0.66 

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. 

 9-28 

intervention blood lead levels and concurrent interior floor dust lead loadings (both logtransformed) identified a correlation of 0.29 (p<0.01). An analysis of blood lead and interior 

floor dust lead for these same children one-year post-intervention identified a very similar 

relationship, with a correlation of 0.32 (p<0.01). 

A simple RM model was run with the same data to test the hypothesis that the relationship 

between blood lead levels and interior floor dust lead loadings (both log-transformed) was the 

same at pre-intervention and one-year post-intervention. The slope of the relationship between 

blood lead and floor dust lead was the same for the two groups (p=0.94), so the interaction term 

was dropped from the model. In the resulting model, the intercepts for the two groups were 

significantly different (p<0.01). Blood lead levels were 20 percent higher at the same interior 

floor dust lead loading at pre-intervention than at one-year post-intervention. 

These analyses support the interpretation put forth above: floor dust lead loadings continued to 

affect blood lead levels post-intervention, but the childís previous exposure as measured by 

baseline blood lead had a stronger relationship to later blood lead levels, which tended to mask 

the effects of dust. The analyses suggest that a similar relationship between blood lead levels and 

interior floor dust lead loadings likely existed at one-year post-intervention as at pre-intervention 

in the two blood SEMs. However, the addition of a previous blood lead result into the one-year 

post-intervention model introduced a factor that was more predictive of later blood lead levels 

than were the concurrent dust lead loadings. The blood lead-dust lead relationship was not 

apparent post-intervention because of the significant correlations between pre-intervention blood 

lead and post-intervention blood lead (r=0.73; p<0.01) and between pre-intervention floor dust 

lead and post-intervention floor dust lead (r=0.34; p<0.01). As displayed in Figure 9-10, homes 

with higher floor dust lead loadings housed children with higher blood lead levels and homes 

with higher floor dust lead loadings continued to have higher floor dust lead loadings postintervention (though overall lower). 

9.5 CONCLUSIONS

Overall, interventions selected by grantees in the LHC Grant Program were successful in 

reducing blood lead levels 18 to 30 percent one-year post-intervention. These levels correspond 

to declines in blood lead levels observed in previous studies of lead hazard control interventions 

(18-34%) (EPA 1995b, EPA, 1998), although this current study is the first to demonstrate 

significant reductions from relatively low pre-intervention blood lead levels. Blood lead levels 

were significantly lower at each successive phase of testing until three-years post-intervention, at 

which time blood lead levels were not significantly different than at two-years post-intervention. 

At two-years post-intervention, geometric mean blood lead levels were approximately 37 percent 

lower than at pre-intervention. 

Children with pre-intervention blood lead levels as low as 10 μg/dL experienced substantial 

declines in blood lead levels following interventions. Previous studies had not observed 

substantial declines unless a childís pre-intervention blood lead level was above 20 μg/dL. These 

results suggest that the interventions of the HUD LHC Grant Program not only had a positive 

overall impact on childrenís blood lead levels but also positively affected children at preintervention blood lead levels around the CDC level of concern (10 μg/dL). 
Data from: Forms 05, 09, and 23 

Data as of: June 1, 2000 Source of Data: NCHH Table . 

Figure 9-10: Geometric Mean Blood Lead Levels and Interior Floor Dust Lead Loadings at PreIntervention and One-Year Post-Intervention by Interior Strategy

50

40353025201510

02 03 04 05

Interior Strategy

Dust Lead: (μg/ft2);

Blood Lead (μg/dL)Dust-pre Blood-pre Dust-1Yr Blood-1Yr

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. 

 9-30 

For at least three-years post-intervention, no interior lead intervention strategy that was 

examined performed substantially better or substantially worse than the other interior strategies 

(after controlling for other factors). Children living in buildings with higher exterior paint lead 

levels (> 7 mg/cm2

) that were treated with exterior lead hazard control work had significantly 

different (lower) blood lead levels than those living in buildings where the exterior was not 

treated. 

The Evaluation designers acknowledged at the beginning of the study that the lack of a control 

population or random selection of treatments would limit the strength of these conclusions. 

Relationships between the interventions and childhood lead exposure will require confirmation 

by more controlled investigations. While the Evaluation could not statistically separate the 

influence of post-intervention lead exposure sources from the influence of pre-intervention blood 

lead (i.e., because these factors were intercorrelated), evidence suggests that the reduction in 

paint lead and dust lead hazards resulted in declines in blood lead levels. 

Although the Evaluation did not have the advantages of a control group or random selection, it 

did have the advantage of a large sample size to help explore the effects of a range of factors on 

blood lead outcomes. Evaluation findings supported previous studies that found a need to control 

for childís age and season of blood lead testing. Age is especially important to consider for 

children less than 12 months prior to intervention because their blood lead levels would be 

predicted to increase in the absence of action and for children between 24 and 30 months of age 

prior to intervention because their blood lead levels would be predicted to decline in the absence 

of action. Likewise, with a 14 to 23 percent difference in blood lead levels in winter compared to 

summer, the season of blood lead testing needs to be taken into account. 

The Evaluation designers recognized that the activities in the HUD LHC Grant Program were 

often a secondary prevention effort for the children who resided in the treated dwellings. 

Children who were reported to be previously lead poisoned experienced smaller blood lead 

declines post-intervention than children who were not reported to be previously lead poisoned. 

This finding emphasizes the need for primary prevention. Unfortunately, the Evaluation was not 

able to recruit enough newborn children into the study to test the primary prevention benefits of 

the interventions. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 9-31 

Exhibit 9-1: List of Variables Used in 

Pre-Intervention and Post-Intervention Blood Lead Models 

Lead Hazards 

Pre-intervention Variables: 

Entryway Dust Lead Loading 

Surface Type of Entry Floor (Hard, Painted or Carpet) 

Surface Condition of Entry Floor 

Average Interior Floor Dust Lead Loading 

Percent of Painted Floors 

Percent of Hard Floors 

Percent of Carpeted Floors 

Percent of Painted Floors * Average Surface Condition 

Percent of Carpeted Floors * Average Surface Condition 

Percent of Hard Floors * Average Surface Condition 

Average Window Sill Dust Lead Loading 

Average Surface Condition of Window Sills 

Percent Painted Window Sills 

Average Window Trough Dust Lead Loading 

Average Surface Condition of Window Troughs 

Percent Painted Window Troughs 

Percent Dust Collected in Same Room for Each Component 

(Entries, Floors, Window Sills, Window Troughs) 

Average Paint Lead on Interior Doors/Trim (Mean of Log(XRF)) 

Average Paint Lead on Windows (Mean of Log(XRF)) 

Average Paint Lead on Exterior Components (Mean of Log(XRF)) 

Average Paint Condition of Interior Doors/Trim 

Average Paint Condition of Windows 

Average Paint Condition of Exterior Components 

Interaction between Paint Lead Loading and Paint Condition for Each Component 

 (Interior Doors/Trim, Windows, Exterior Components) 

*Interaction between % Dust Collected in Same Room and Dust Lead Loading (Pre-Intervention) for 

Each Component (Entries, Floors, Window Sills, Window Troughs) 

Interaction of Surface Type and Condition of Entry Floor 

*Post-intervention Variables: 

Entryway Dust Lead Loading 

Surface Condition of Entry Floor 

Average Interior Floor Dust Lead Loading 

Average Surface Condition of Interior Floors 

Average Window Sill Dust Lead Loading 

Average Surface Condition of Window Sills 

Average Window Trough Dust Lead Loading 

Average Surface Condition of Window Troughs

Pre-Intervention Building/Dwelling Condition 

Number of Interior Elements with Deterioration 

Roof Leak (Yes/No) 

Plumbing Leak (Yes/No) 

Number of Exterior Elements with Deterioration 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 9-32 

Living Space of Dwelling at Pre-intervention (sq. ft) 

Entry Height in Stories 

Market Value 

Household Characteristics 

Pre-intervention Variables:

Was Home Renovated (Yes/No) 

Years of Education of Female Parent 

Presence of Cleaning Equipment (Percent) 

Frequency of Cleaning the House 

Frequency of Washing Exterior Window Sills 

Cleanliness of the Home 

(1=Appears clean, 2=Some evidence of cleaning, 3=No evidence of cleaning) 

Household Income ($) 

Number of Children Less than 6 Years 

Number of People between 6-18 Years 

Number of People in Home 

Child Characteristics (Pre-Intervention unless noted) 

Childís Blood Lead Level (Pre-Intervention) 

*Childís Blood Lead Level (Post-Intervention) 

*Indicator of Pre-Intervention Blood Samples Collected after Start of Intervention 

(Yes = after start of intervention, No = Up to 16 wks prior to start of intervention) 

Childís Age, Age Square, Age Cubic 

Race of Child 

Sex of Child 

Frequency of Putting Fingers into Mouth 

Frequency of Putting Toys into Mouth

Number of Hours Awake per Week 

Number of Hours Away from Home per Week 

Number of Hours Inside the House per Week

Number of Hours Outside the House per Week 

Parent Report Previous Child Lead Poisoning (Yes/No) 

Child Received WIC Benefit (Yes/No)

*Fully Relocated during Intervention (Yes/No) 

Interaction between Entry Dust Lead and Mouthing Behavior 

Interaction between Interior Floor Dust Lead and Mouthing Behavior 

Interaction between Mouthing Behavior and Age, Age2

, Age3 

*Interaction between Blood Lead and Age, Age2

, Age3

Other Characteristics

Season of Blood Sample Collection (Pre-Intervention) 

*Season of Blood Sample Collection (at Post-Intervention) 

Season of Dust Sample Collection (Pre-Intervention) 

*Season of Dust Sample Collection (at Post-Intervention) 

Building Type (Single unit, 2-4 units, >4 units) 

House Age (by decade) 

Occupancy Status (Pre-Intervention) 

Ownership (1=Rented, 2=Owner occupied, 3=Other) 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004 

. 

 9-33 

*Intervention 

Interior LHC Work (by Strategy) 

Exterior LHC Work (Yes/No) 

Site LHC Work (Yes/No) 

Interaction between Interior LHC Work and Exterior LHC Work 

Interaction between Interior LHC Work and Site LHC Work 

Interaction between Blood Lead and Interior Strategy 

Interaction between No. of Exterior Elements with Deterioration and Interior Strategy 

Interaction between No. of Interior Elements with Deterioration and Interior Strategy 

Interaction between Floor Dust Lead (Pre-Intervention) and Interior Strategy 

Interaction between Entry Dust Lead (Pre-Intervention) and Interior Strategy 

Interaction between Window Sill Dust Lead (Pre-Intervention) and Interior Strategy

Interaction between Window Trough Dust Lead (Pre-Intervention) and Interior Strategy 

Interaction of Average Floor Surface Condition (Pre-Intervention) and Interior Strategy 

Interaction between Average Surface Condition of Window Sills and Interior Strategy 

Interaction between Average Surface Condition of Window Troughs and Interior Strategy 

Interaction between Paint Lead on Interior Doors/Trim and Interior Strategy 

Interaction between Paint Lead on Windows and Interior Strategy 

Interaction between Paint Lead on Exterior Components and Exterior Strategy 

*Post-Intervention Models only
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 10-1

10.0 CONCLUSIONS 

10.1 OVERALL FINDINGS 

The Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program is the largest and 

most comprehensive study of lead hazard control in housing ever undertaken in the United 

States. It examined over 3,000 houses located in over a dozen jurisdictions across the country 

where HUD provided funding to address lead-based paint in privately owned low-income 

housing where the risks are greatest. The study looked at virtually all of the modern ways of 

controlling lead-based paint hazards and their relative effectiveness. 

The study provides evidence that the programís lead hazard control activities substantially 

reduced dust lead levels on floors, window sills and troughs and generally, the dust lead 

remained well below pre-treatment levels for at least three years. On floors, three-year postintervention geometric mean dust lead loadings were roughly 80% below pre-intervention levels, 

while on windows (sills and troughs, separately), the three-year levels were at least 89% below 

pre-intervention. Neither lead-based paint that remained in the dwellings nor exterior leadcontaminated dust or soil appear to have had a significant impact on dust lead levels during the 

three year period of post-intervention observation. 

More importantly, the interventions and the reductions in dust lead loadings were accompanied 

by substantial declines in childrenís blood lead levels over the three years after lead hazard 

control. Based on the blood lead modeling, an average child with a parental report of lead 

poisoning and a baseline blood lead level of 8.4 ug/dl is expected to experience a 37 percent 

decline in blood lead three-years after intervention. Furthermore, unlike findings from earlier 

studies (Farfel 1990; Amitai 1991), average childrenís blood lead concentrations did not display 

an increase immediately after intervention. The requirements placed on the grantees by the Grant 

Program, including local monitoring of occupant and worker safety and verification of 

achievement of clearance standards, proved effective in protecting children. 

Although previous studies had found that children with initial blood lead levels below 20 μg/dL 

did not have substantial declines post-intervention (Swindell 1994; EPA 1997a), children in the 

Evaluation with pre-intervention blood lead levels between 10-19 μg/dL exhibited blood lead 

declines of 34 percent at one-year post-intervention. Children with this range of blood lead leads 

did not experience significantly different declines in blood lead from children with preintervention blood lead levels 20-25 μg/dL and above 25 μg/dL. 

It was originally anticipated that dust lead loadings would increase after treatment as lower 

intensity interventions began to fail. Interestingly, dust lead loadings on window sills and troughs 

and on a subset of dwelling entry floors did increase from clearance to 6 months postintervention, but then those levels stabilized and often declined after that point. This pattern was 

similar to findings in the Baltimore Repair and Maintenance Study (EPA 1997b). In that study, 

samples collected within two months of intervention displayed significant increases from 

clearance levels and then dust lead loadings stabilized. The authors of that study hypothesized 

that the immediate increases in dust lead were associated with move-in. In the Evaluation, the 

locations where six-month dust lead levels increased (entries and windows, but not interior 

floors) suggest that external sources are the likely source of this lead. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 10-2

Both exterior and soil lead hazard control work influenced reductions in post-intervention floor 

dust lead loadings. In the model describing the data, interior floor dust lead loadings in dwellings 

not receiving exterior treatments were predicted to be 32 percent higher than the dwellings 

receiving exterior treatments, while floor dust lead loadings in dwellings not receiving soil work 

were 45 percent higher than dwellings receiving soil treatments. Site treatments (mainly interim 

soil controls) were also associated with lower post-intervention exterior entry dust lead loadings. 

Because exterior entry dust lead levels were found to contribute directly to interior entry floor, 

floor, and window sill dust lead loadings, these treatments were also likely to reduce dust lead 

loadings on these surfaces. 

The lead hazard control treatments themselves tended to hold up for the three-year observation 

period. The median dwelling in the Evaluation had only one treatment failure (7.5% of all 

treatments) two and three years post-intervention. This result actually overstates the number of 

failures that created lead-based paint hazards, because inspectors were required to report all 

treatment failures including failures to abatements (e.g., inoperable replacement windows). As 

expected, paint stabilization on surfaces subject to abrasion, impact or weathering (doors, 

windows, and exteriors) had some of the highest failure rates among the individual treatments: 

23% of these treatments had failed three-years post-intervention. However, as noted above, these 

failures did not correspond with increases in the average dust lead loadings post-intervention. 

10.2 FINDINGS FOR SPECIFIC INTERVENTION STRATEGIES

The strength of the Evaluation is not only its overall findings, but also the availability of a range 

of lead hazard control strategies to make comparisons about the effectiveness those strategies. 

This report presents findings on five intensities of interior interventions that the participating 

grantees conducted as well as assessments of the effects of interventions to the exterior and site 

of a building. In earlier sections of this report, the effects of the different strategies were reported 

by measure of effectiveness (clearance, longitudinal dust lead and longitudinal blood lead). This 

section summarizes those effects by strategy. 

Although not one of the original study objectives, the cost-effectiveness of the various 

interventions was briefly examined, but the evaluators determined that it could not be adequately 

assessed. The Evaluation collected detailed cost information about the interventions that is 

presented in Section 6. However, a critical piece of information that was not part of the 

Evaluation design was the size, frequency and cost of lead hazard control activities undertaken 

by property owners and/or residents after the HUD funded work was complete. Any assessment 

of the short-term cost-effectiveness of interventions would be weakened by the absence of the 

ongoing costs of maintaining interim controls. Tables 10-1 and 10-2 summarizes the costs of 

each intervention strategy, but these costs should be considered with this limitation in mind. 

The primary measures of effectiveness in the Evaluation were interior dust lead loadings and 

childrenís blood lead levels. Although there was a substantial overall decline in childrenís blood 

lead levels following lead hazard control activities, no differential effect was identified between 

the intervention strategies on one-year blood lead levels. For this reason, the comparisons 

between interventions are limited to effects on dust lead loadings. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 10-3

Interventions that abated windows (Interior Strategy 05 and 06/07) had lower dust lead loadings 

on window surfaces during the post-clearance phases1

 than interventions where windows were 

spot painted or just cleaned (Interior Strategy 02) (Table 10-3). For example, when controlling 

for other factors, one-year post-intervention dust lead loadings on window sills and troughs with 

median baseline levels (416 and 5,768 μg/ft2

, respectively) or higher were estimated to be at least 

50 percent lower in homes with abated windows than in homes where windows received only 

spot painting and cleaning and in some cases, well caps. Significant differences were also 

observed between dust lead levels on window sills when window abatement was compared to 

window paint stabilization. Results in homes where windows were only partially abated 

(Strategy 04 ñ sash replacement or jamb liners) fell between the abatement and non-abatement 

groups. These findings match common wisdom that more intensive window interventions will 

more effectively reduce dust lead loadings on window surfaces. 

Interestingly, dwellings where windows were abated but other components were not completed 

abated (Strategy 05) had the highest estimated dust lead loadings on floors post-clearance. Even 

though window dust lead is a source of floor dust lead, the abatement of windows in these homes 

did not result in greater declines on floors. Interventions that also abated all other lead-based 

painted surfaces (Strategies 06/07) had the lowest floor dust lead loadings during the two postclearance phases when these interventions were assessed. Dwellings treated with cleaning only 

or limited paint stabilization (Strategies 02 and 03) had the highest dust lead loadings on window 

surfaces post-clearance. Yet, dust lead loadings on floors in these dwellings were not higher than 

the floor lead loadings in dwellings treated with any of the intervention strategies. 

While window abatement was demonstrated to be the most effective measure to reduce dust lead 

loadings on windows, this treatment must be performed in conjunction with other treatments that 

influence predictors of floor dust lead (e.g., floor surface type and condition, door and trim paint 

lead, and general interior building condition, as well as exterior dust/soil lead). Although 

pathway analysis suggests that window dust lead influences floor dust lead, only treating ìupstreamî hazards would not result in substantial ìdown-streamî dust lead reductions. 

Furthermore, window dust lead loadings increased substantially shortly after clearance without 

influencing the floor dust lead loadings up to three years after treatment. These findings support 

the current requirement to address all interior, exterior and soil lead hazards in an integrated 

manner. 

Final clearance test results were not necessarily predictive of the longer-term post-clearance 

performance of the intervention strategies. For example, floor dust lead loadings in dwellings 

that were fully abated had the highest average levels at clearance, but by six months postintervention, the loadings had declined below all other strategies. This finding suggests that if 

there are no sources to create dust lead in the dwelling, routine cleaning by the residents 

following professional lead hazard control work can reduce dust lead to levels below what was 

achieved through professional cleaning. 

Although differences between intervention strategies were identified, only one of the individual 

strategies may be considered unsuccessful during the three-year observation period. All lead 

hazard control interventions except spot painting and cleaning (Strategy 02) reduced average 

 

1

 The outcomes presented on this page were significant (p<0.05) in the one-year post-intervention multivariate 

regression models and followed the same trends across the three-year post-intervention observation period of the 

Evaluation. Chapter 8 presents the full set of statistical analyses that examined these effects. 
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 10-4

dust lead loadings on all surfaces examined and maintained those levels significantly below the 

pre-intervention loadings throughout the Evaluation. Consideration of a second measure of 

success, whether post-intervention dust lead levels remained below current risk assessment 

standards (40 μg/ft2 on floors and 250 μg/ft2 on window sills), is complicated by the fact that 

grantees did not attempt to achieve these recent (EPA 2001a) standards during the Evaluation. 

However, for each of the intervention strategies, the geometric mean dust lead loadings remained 

below these standards for the three-year period of the Evaluation. 

HUD is sponsoring further research of the Evaluation dwellings to assess the effectiveness of the 

individual strategies six years after intervention. This research will provide additional evidence 

about the longer-term effectiveness of the treatments. For the three-year time period studied here, 

the data show that, with the exception of ìclean-onlyî strategies, the hazard control methods 

employed by the HUD grantees succeeded in protecting children and creating lead-safe housing.
*Pre-intervention levels were set at their median levels (30 μg/ft2 (floors), 416 μg/ft2 (sills) and 5,768 μg/ft2 (troughs) 

Intervention Defining Characteristics Primary Contributing 

Grantees 

Costs 

Interior Strategy 02 

Cleaning-only, or Cleaning-only w/sill & trough caps, or Spot painting w/sill & trough caps, or Spot painting w/replacement of a few components 

Vermont 

Milwaukee 

Alameda Co. 

Minnesota 

Mean: $ 730 Median: $ 430 25th %tile: $ 170 

 75th %tile: $ 1,070 

Interior Strategy 03 

Paint stabilization of most components, or Paint stabilization w/sill & trough caps, or Paint stabilization w/minor window repair 

New York City 

Milwaukee 

Alameda Co. 

California 

Mean: $ 4,730 Median: $ 4,930 25th %tile: $ 3,410 

75th %tile: $ 6,040 

Interior Strategy 04 

Window jamb liners w/sill & trough caps and paint stabilization, or Sash paint removal or replacement w/trough caps and paint stabilization, or Enclosure of walls/ceilings, replacement of trim, but minimal window work 

Milwaukee 

New York City 

Vermont 

Minnesota 

Cleveland 

Mean: $ 6,370 Median: $ 6,120 25th %tile: $ 3,980 

75th %tile: $ 8,570 

Interior Strategy 05 

Window replacement or paint stripping, and combinations of the following: Door/trim replacement, paint removal, encapsulation, or paint stabilization; Wall/ceiling enclosure or stabilization; Floor enclosure 

Baltimore Vermont 

Wisconsin Rhode Island 

Massachusetts Chicago California Cleveland 

Mean: $ 7,150 Median: $ 6,800 25th %tile: $ 4,850 

75th %tile: $ 9,170 

Interior Strategy 06/07 

Removal and enclosure of all LBP Removal only of all LBP 

New York City 

New Jersey 

Boston 

Strat.06/ 07 

Mean: $ 9,510/ 4,410 Median: $ 9,570/ 4,110 25th %tile: $ 8,860/ 910 

75th %tile: $ 9,880/ 5,890 

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

10-5 10-5

Table 10-1: Characteristics and Costs of Interior Lead Hazard Control Intervention
Table 10-2: Characteristics and Costs of Lead Hazard Control Work to Exterior and Site 

Intervention Defining Characteristics Primary Contributing 

Grantees 

Costs 

Exterior Work Treatments (% of all Treated Buildings) 

 Paint Stabilization (84%)  Component Enclosure (29%)  Component Replacement (26%)  Paint Removal (25%)  Encapsulation ( 3%) 

Baltimore Vermont 

Milwaukee Rhode Island 

Alameda Co. Wisconsin 

Massachusetts 

California 

Mean: $ 3,930 Median: $ 1,870 

25th %tile: $ 840 

75th %tile: $ 5,970 

Site Work Treatments (% of all Treated Buildings) 

 Mulch/Seed/Sod/Plant (90%)  Soil Enclosure (22%)  Soil Removal (10%)  Structure Removal ( 3%) 

Rhode Island 

Alameda County 

Cleveland 

Minnesota 

Vermont 

Mean: $ 2,220 Median: $ 1,080 

25th %tile: $ 400 

75th %tile: $ 2,450 

10-6

Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004
Evaluation of the HUD Lead-Based Paint Hazard Control Grant Program May 1, 2004

 11- 1 

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