Pb NAAQS Human Health
Risk Assessment – Overview
of Design and Implementation
November 12th, 2008
Dr. Zachary Pekara and Dr. Jee-Young Kimb
a - Office of Air Quality Planning and Standards (OAQPS), USEPA
b – National Center for Environmental Assessment (NCEA), USEPA
Overview of presentation
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Background – the role of risk assessment in the National
Ambient Air Quality Standards (NAAQS)
Key attributes of Pb from a risk assessment standpoint
Case study approach
Air-quality scenarios
Sensitive populations, sentinel health endpoint and blood Pb
metric
Types of exposure and risk metrics modeled
Conceptual framework for the Pb NAAQS risk assessment
More detailed overview of indoor dust modeling step
Blood Pb results
Concentration-response function(s) for IQ loss
Key IQ loss (risk) results
Areas for refinement of risk assessment approach
ADDITIONAL SLIDES
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Background on NAAQS Process:
Statutory Considerations and Role of
Administrator
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NAAQS includes a primary standard (human health
focus) and secondary standard (welfare and
ecosystem)
Primary standard (for public health protection) –
judged by the Administrator to protect public health
with an adequate margin of safety
 Includes consideration for sensitive subpopulations
Administrator considers risk and evidence-based
information (provided by staff) along with peer-review
and public comments in making decision regarding
appropriate NAAQS
Background on NAAQS Process:
Risk Assessment and EvidenceBased Analysis
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Risk assessment – application of more complex step-wise
analysis of exposure and resulting risk for residential
populations associated with selected case studies
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Mechanistic and empirical modeling elements:
• Exposure modeling framework
• Health impact (risk) modeling framework
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Estimate distribution of exposure and risk for populations
within specific study areas (e.g., area surrounding smelter
facility)
Evidence-based analysis – use data obtained directly from
the literature (empirical) to estimate risk estimates using
simple analysis framework
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For Pb, have air-to-blood ratio to estimate exposure and
simple CR function slope to translate that into IQ loss
• IQ loss = Pb-air * AB ratio * IQ loss slope
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Generate simple estimate of risk (no characterization of risk
distribution across population)
Background on NAAQS Process:
Indicator, Level, Averaging Time and Form
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Indicator: chemical species or mixture that is to be
measured (Pb NAAQS is TSP)
Level: amount of Pb that can be in ambient air
Averaging time: period over which air measurements are
averaged to arrive at a level to compare to the level
Form: air quality statistics (e.g., max, or second max) that is
to be compared with the level (works with averaging time)
EXAMPLE: Current NAAQS: 0.15 µg/m3 max rolling 3 month
average
• Level: 0.15 ug/m3
• Averaging time: rolling 3 month average
• Form: maximum
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Risk Assessment informs: level and to a certain extent
averaging time
Key Attributes of Pb-Related Risk with
Implication for the NAAQS Review –
Multi-pathway and persistent nature of Pb
Simplified representation
Pb in ambient air
penetrates
indoors
Pb
paint
deposition
to indoor dust
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deposition
outdoor
soil
Food
(crops)
Drinking
water
Auto
Pb
ingestion of
indoor dust
inhalation
Re-entrainment
ingestion of
outdoor soil
dietary and drinking
water ingestion
Key Attributes of Pb-Related Risk with
Implication for the NAAQS Review –
Air-related and background pathways
Non-air related (background)
Air-related (policy-relevant)
Pb in ambient air
penetrates
indoors
deposition
to indoor dust
ingestion of
indoor dust
inhalation
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deposition
outdoor
soil
ingestion of
outdoor soil
Food
(crops)
Drinking
water
dietary and drinking
water ingestion
Key Attributes of Pb-Related Risk with
Implication for the NAAQS Review –
Non-linearity of Exposure and Risk Modeling
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Non-linearity in Pb exposure modeling and IQ concentrationresponse requires consideration of total Pb exposure (not
just air-related) in order to representatively “place” a modeled
child on the CR function curve
6pts
IQ loss
1pt
1.0
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Blood Pb level (ug/dL)
10
Design Aspects:
Case study approach
General urban
case study
Location-specific
urban case study
Primary Pb smelter
case study
Comparatively
small area
2km radius
study area
5-20 km
Pb smelter
facility
Small neighborhood
with ambient air levels
at standard
One single exposure zone
(uniform ambient air Pb level
and demographics)
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Larger urban area with varying
ambient air Pb levels and
demographics
2km radius residential area surrounding
large Pb smelter with varying ambient air Pb
levels and demographics
Each US Census block is a separate exposure
zone (varying ambient air Pb levels and
demographics across study area)
Air quality scenarios evaluated
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Current conditions scenario
PREVIOUS – 1978 NAAQS scenario (urban case
studies hypothetically assumed to have ambient air
Pb levels just meeting current NAAQS)
 Assume proportional rollup for location specific
urban case studies based on TSP monitor data
Alternate (lower) standard levels
 0.5, 0.2, 0.05, and 0.02 ug/m3
 Varying averaging times (max monthly and max
quarterly)
Sensitive populations, sentinel health
endpoint and blood Pb metric
selected for risk modeling
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Neurological effects in children (0-7 yrs of age): developing
nervous system in children most sensitive and effects shown to occur
at lower blood Pb levels
 Evidence for neurological effects is well supported by epi and tox
studies
 Available epi studies support derivation of CR functions for IQ
loss
Epi studies investigating neurological effects have focused on
number of blood Pb metrics (concurrent, lifetime average, peak,
and early childhood).
 All 4 metrics have been correlated with IQ, but the concurrent and
lifetime average have been shown to have the strongest
association (in the Lanphear 2005 pooled analysis)
 Concurrent (strongest association of the 4) emphasized in
presenting final results
Risk (Pb-related IQ loss):
 Population-weighted distributions of total
IQ loss
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Population incidence estimates
• Number of children with total Pb related
IQ loss greater than 1 IQ point, 5 IQ
points, 7 IQ points, etc.
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50th %
95th %
Blood Pb levels (ug.dL)
% of pop
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Exposure:
 Population-weighted distributions of
blood Pb levels
50th %
95th %
Points of IQ loss
% of pop
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% of pop
Types of Exposure and Risk Metrics:
population-weighted distributions and
population incidence
1,350 kids with > 4 IQ
points lost
Points of IQ loss
Conceptual framework for risk
assessment - 1
Location-specific urban case study
Single central tendency
blood Pb level for entire
study area
Single population
distribution of blood Pb
levels for entire study area
STEP 1:Multipathway blood
Pb modeling
% of pop
Blood Pb levels (ug.dL)
Blood Pb levels (ug.dL)
% of pop
STEP 2: Application of
geometric standard
deviation (GSD)
Single population
distribution of IQ loss for
entire study area
STEP 3: Application of
IQ loss functions
Points of IQ loss
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Conceptual framework for risk
assessment - 2
Ambient air Pb
levels
MODEL
blood Pb levels (IEUBK) –
central-tendency levels for EACH
exposure zone
MODEL
indoor dust Pb levels
Background Pb
levels
(diet and
drinking water)
Exposure Analysis
(central-tendency level)
% of pop
Soil Pb levels
• multi-pathway intake modeling
• biokinetic BLL modeling
Blood Pb levels (ug.dL)
Demographic data for
exposure zones
Exposure Analysis
(population distribution)
MODEL
Populationdistribution of blood
Pb levels for ENTIRE
study area
% of pop
Inter-individual variability
in residential blood Pb
levels (GSD)
Blood Pb levels (ug.dL)
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Risk Characterization
(IQ loss)
Estimate
policy-relevant IQ
loss for population
percentiles of interest
% of pop
CR functions relating
blood Pb levels and
IQ loss
MODEL
Populationdistribution of IQ
points lost for entire
study area
Points of IQ loss
Modeling Approach:
Characterizing indoor dust Pb levels - 1
General urban and location-specific urban case studies
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Hybrid model: mechanistic-empirical model
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SUB-MODEL 1: Mechanistic compartmental
model to predict indoor Pb loadings given
ambient air Pb levels (recent-air contribution).
Considers: air exchange rates, deposition velocity,
cleaning rates and efficiency. Dynamic mass-balance
model which is solved for steady-state.
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Background (non-air) component of indoor
dust Pb loading estimated by subtracting airrelated estimate from total residential Pb
loading estimate. Total estimate of indoor
dust Pb levels obtained from HUD dataset
(median of US residential range).
SUB-MODELS 2 and 3: Empirical-based log-log
regression equations used to (critical non-linearity):
a)
b)
Convert wipe equivalent loadings (from
mechanistic model) to vacuum loadings and
then
Convert
15 vacuum loadings to concentrations
Primary Pb smelter case study
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Log-log regression model based on sitespecific data from the remediation zone. Data
include:
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Indoor dust Pb concentrations from
17 houses in remediation zone (units of
analysis). Temporally-averaged values
were used for each house.
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Annual-average Pb concentrations
from US Census block centroids
located within 200m of each house
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Road dust measurements within
300m of each house
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Post-remediation yard soil Pb levels
for each house
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Model selected relates natural log of
ambient air Pb to natural log of
indoor dust Pb (this model had better
predictive power compared with models
which included soil or road dust
variables).
Modeling Approach:
Characterizing indoor dust Pb levels - 2
Indoor dust Pb (ppm)
Presentation of indoor dust Pb models
used in Pb NAAQS risk assessment
4500.0
4000.0
3500.0
3000.0
2500.0
2000.0
1500.0
1000.0
500.0
0.0
Hybrid (urban) model
Primary Pb smelter
regression model
0
1
2
Ambient air Pb levels (ug/m3)
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3
Modeling Approach:
Estimating blood Pb levels (IEUBK modeling)
Media Pb concentrations (air,
soil, indoor dust, diet, drinking
water)
(single value across all 7 years)
Ingestion and inhalation
rates
(7 values – differentiated by
child age)
IEUBK blood Pb
model
Lifetime average BLL estimate
(average of 6th month to 7th year)
Concurrent BLL estimate
(7th year estimate)
Combined with Geometric Standard
Deviation (GSD) characterizing inter-individual
blood Pb level variability in population
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Modeling Approach:
Blood Pb results (and performance evaluation)
Comparison – Modeled Concurrent BLLs for Case Studies Compared to NHANES-IV Data
(modeled results are for current conditions)
Blood Pb levels (ug/dL)
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NHANES-IV (interpolated 19992002, 7yr old)
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General urban case study (mean
current conditions - higher)
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Primary PB smelter (smaller 1.5km
study area - current NAAQS)
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Location-specific case study
(Chicago)
4
Location-specific case study
(Cleveland)
2
Location-specific case study
(LA)
0
median
75th
90th
Population percentile
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95th
Modeling Approach:
Specification of CR Functions for IQ Loss – 1
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Lanphear et al. (2005) – An international pooled analysis from seven
prospective cohorts
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Development of regression model involved multistep process
• First examined fit of linear model then considered quadratic and cubic terms to
examine non-linearity
• Restrictive cubic spline function indicated that log-linear model provided a good fit to
the data
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Ten potential confounders considered
• Final model adjusted for site, HOME score, birth weight, maternal IQ, and maternal
education
• Addition of child’s sex, tobacco and alcohol exposure during pregnancy, maternal
age at delivery, marital status, and birth order did not alter effect estimate
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Four measures of BLL examined
• Concurrent, peak, early childhood, and lifetime average all highly correlated, but
concurrent BLL exhibited strongest relationship with IQ
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Stability of model evaluated
• Results of random-effects model were similar to fixed-effects model
• Identical log-linear models that were fit with each model omitting data from one of the
sites indicated that the pooled analysis did not depend on data from any single
cohort
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Modeling Approach:
Specification of CR Functions for IQ Loss – 2
Relationship between Blood Pb and Children’s IQ in Lanphear
et al. (2005)
Log-linear model (95% CI shaded) for
concurrent blood lead concentration
adjusted for HOME score, maternal
education, maternal IQ, and birth weight.
The mean IQ (95% CI) for the intervals <5,
5-10, 10-15, 15-20, and >20 µg/dL are
shown. (Lanphear et al., 2005)
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Log-linear model for concurrent blood lead
concentration along with linear models for
concurrent blood lead levels among
children with peak blood lead levels above
and below 10 µg/dL. (Lanphear et al.,
2005)
Modeling Approach:
Specification of CR Functions for IQ Loss - 3
Plot of four CR functions specified for the risk assessment
(based on Lanphear et al., (2005) pooled analysis results)
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Stratified at 7.5 peak BLL
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10
IQ loss
log-linear with cutpoint
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dual linear - stratified
at 10 ug/dL, peak
dual linear - stratified
at 7.5 ug/dL, peak
log-linear with lowexposure linearization
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4
2
Stratified at 10 peak BLL
0
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0
1
2
3
4
5
6
7
Concurrent blood Pb (ug/dL)
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9
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Modeling Approach:
Risk Estimation – Prediction of IQ Loss
four CR functions
relating blood Pb
levels to IQ loss
Results of exposure modeling
Results of risk modeling
% of pop
% of pop
LLL function
Blood Pb levels (ug.dL)
Points of IQ loss
General urban case study (current conditions, LLL CR function)
TOTAL
IQ loss
Blood Pb
Level
(concurrent:
ug/dL)
50th%
-4.5
1.9
95th%
-7.7
6.5
Population
percentile
Pathway contribution (based on fraction of total UPTAKE)
Diet
Drinking
Water
18%
10%
Background
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Inhalation
Indoor dust
(air)
Indoor
dust
(other)
Outdoor
soil/dust
0.5%
28%
6%
28%
Recent Air
Past Air
Modeling Approach:
Risk Estimation – Risk Results
Median population percentile risk (IQ loss) results (LLL CR function)
General Urban Case Study
Points IQ Loss
Air Quality Scenario
µg/m3,
Current NAAQS (1.5
max quarterly)
Alternative NAAQS (0.5 µg/m3, max monthly)
Alternative NAAQS (0.2 µg/m3, max quarterly)
Current conditions - mean (0.14 µg/m3 max quarterly)
Alternative NAAQS (0.2 µg/m3, max monthly)
Alternative NAAQS (0.05 µg/m3, max monthly)
Alternative NAAQS (0.02 µg/m3, max monthly)
RECENT AIR:
Inhalation + indoor
dust ingestion (air)
3.5
1.9
1.5
1.3
1.2
0.5
0.3
LOW BOUND
RECENT + PAST AIR:
Inhalation + indoor
dust ingestion (total)
+ soil
4.8
3.6
3.4
3.2
3.2
2.8
2.6
HIGH BOUND
Air-related (policy-relevant) risk
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TOTAL Pb Exposure
5.8
4.8
4.6
4.5
4.4
4.1
4.0
Areas for Potential Refinement of the Pb NAAQS
Risk Assessment Approach
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Exposure modeling:
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Further refine indoor dust modeling (provide coverage for foot
tracking mechanism that links ambient air to indoor dust Pb)
Develop probabilistic approach for modeling inter-individual
variability in multi-pathway exposure to Pb (with emphasis on
ambient-air related pathways) – alternate to GSD approach
Refine ability to pathway-apportion exposure (and risk) particularly
for higher population percentiles
Enhance ability to relate shorter-term changes in Pb exposure to
blood Pb levels (enhance shorter-term blood Pb modeling)
Refine our ability to model the impact of ambient air-Pb changes
on adult blood Pb levels
Risk modeling:
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Further refine our understanding of low-exposure (low-blood Pb)
IQ loss with the goal of enhancing our CR functions
Refine our ability to model other low-exposure related health endpoints
ADDITIONAL SLIDES
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Policy-relevant apportionment of risk
estimates (policy-relevant versus
background)
Background
sources
Policy-relevant sources
Ambient air
“Recent air”
Indoor dust
• newly emitted lead
• resuspension of historically
emitted and deposited lead
Indoor dust
“Past air”
Outdoor soil
• historically emitted and
deposited lead
• paint
• Diet
• Drinking water
paint
Total risk = recent air pathways + past air pathways + background pathways
• The risk assessment simulates attainment of alternate NAAQS by reducing
recent air exposures.
• In fact, attaining alternate NAAQS could also involve reduction of past air
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exposures (e.g., historically emitted and deposited lead).
Conceptual framework for
risk assessment - Extra
Location-specific urban
case study
Census block #1
% of pop
% of pop
Census block #n
Blood Pb levels (ug.dL)
% of pop
% of pop
Blood Pb levels (ug.dL)
Points of IQ loss
Points of IQ loss
Populationweighted
aggregation
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% of pop
100
children
Points of IQ loss
900
children
Modeling Approach:
Characterizing ambient air Pb levels, inhalation
exposure air concentrations, and background (diet
and drinking water) concentrations
Media category
General urban case study
single ambient air Pb level
assumed across entire study
area (mean values from urban
areas with > 1 million people).
Location-specific urban
case study
US Census block
groups within study
areas assigned to
nearest TSP monitor
(point source and nonpoint source monitors
handled differently).
 6 to 11 exposure zones
depending on location.
Primary Pb smelter case study
Ambient air Pb
levels
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Inhalation
exposure air
concentrations
National Air Toxics Assessment (NATA) – derived ratios
of modeled Pb air exposure levels to ambient air Pb
levels. The average ratio for the overall NATA analysis was
used.
NATA-derived ratios estimated for
set of relevant US Census tracts
Outdoor soil Pb
levels
Arithmetic mean from HUD data set intended to
characterize residential soil Pb levels across houses
constructed between 1940 and 1998.
Site-specific post-remediation soil
Pb measurement data (for
subarea)
Dietary Pb levels
Based on (a) Pb food residue data from US FDA Total Diet Study (2001) and (b) food
consumption data from NHANES III (CDC, 1997)
Drinking water Pb
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levels
Geometric mean of values reported in studies of US and Canadian populations (residential
water).
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ISC-PRIME dispersion modeling
(NAAQS attainment scenario) used
to estimate centroid levels for US
census blocks and block groups.
 22 US Census block groups and
115 blocks.
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Modeling Approach:
Specification of CR Functions for IQ Loss - Extra
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Log-linear function
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•
•
•
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n = 1,333
Median concurrent BLL 9.7 μg/dL
β = -2.70 (95% CI: -3.74, -1.66)
Estimate IQ point decrement: 3.9 points for BLL 2.4 to 10 μg/dL; 1.9 for
BLL 10 to 20 μg/dL
Dual linear stratified at peak BLL 10 μg/dL
• n = 244
• GM concurrent BLL 4.3 μg/dL
• β = -0.80 (95% CI: -1.74, 0.14) for <10 μg/dL
β = -0.13 (95% CI: -0.23, -0.03) for ≥10 μg/dL
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Dual linear stratified at peak BLL 7.5 μg/dL
• n = 103
• GM concurrent BLL 3.2 μg/dL
• β = -2.94 (95% CI: -5.16, -0.71) for <7.5 μg/dL
β = -0.16 (95% CI: -0.23, -0.08) for ≥7.5 μg/dL
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