montreal lead study: association between cumulative lead exposure index and blood lead levels in 1-5...

Montreal Lead Study: Association between

Cumulative Lead exposure index and Blood lead levels in

1-5 Years-old ChildrenGerard Ngueta, (PhD Candidate in Epidemiology)

Research Advisor: Dr. Patrick Levallois

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Relevance of Montreal Lead StudyDifference from earlier association studies

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INTRODUCTIONOBJECTIVES

METHODOLOGYRESULTS

CONCLUSIONS AND PERSPECTIVES

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Montreal Lead Study

Undertaken in 2009 and firstly designed to assess lead exposure in 1-5 years old children living in Montreal city

US E.P.A reports indicating the global decrease of environmental lead exposure and huge reduction of BLL in young children.

Montreal Study remains relevant because of poor data published in Canadian children (aged under 6).

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METHODOLOGYRESULTS


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Strong association between environmental lead and BLL

Reported in several previous studies and reports

In most cases, they were cross-sectional association studies

Most of children included were those with high risk of lead exposure [Black and Hispanic origin > 50% population study]

The present study differs from earlier: 1) Caucasian children ≈ 67% of population study2) Cumulative lead exposure index (CLEI) in addition to cross-

sectional measures of exposure

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METHODOLOGYRESULTS


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Motivation for using CLEI ? Previous studies indicated that lead has a half-life of approximately

30 days in the blood

Greenbalt reported that the time required to find steady-state is approximately four-to-five times the elimination half-life after a single exposure [Annual review of medicine 36, 421-427]

There is a scientific reason to believe that BLL at a given time is more related to lead exposure experienced during 3-5 months before that time.

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METHODOLOGYRESULTS


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Motivation for using CLEI ?

Days Environmental lead Blood lead

149 X149

148 X148

…. ….

3 X3

2 X2

1 X1

Day of visit X0 Y

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METHODOLOGYRESULTS


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Motivation for using CLEI ?

Days Environmental lead Blood lead

149 X149

148 X148

…. ….

3 X3

2 X2

1 X1

Day of visit X0 Y

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METHODOLOGYRESULTS


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Motivation for using CLEI ? Previous studies indicated that lead has a half-life of approximately

30 days in the blood

Greenbalt reported that the time required to find steady-state is approximately four-to-five times the elimination half-life after a single exposure [Annual review of medicine 36, 421-427]

There is a scientific reason to believe that PbS at a given time is more related to lead exposure experienced during 3-5 months before that time.We hypothesize that cumulative lead exposure would be more suitable to assess the association between Environmental lead and BLL

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METHODOLOGYRESULTS


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Objectives of study To estimate the effects of both CLEI and cross-sectional measures of

water lead and residential dust lead on BLL in children aged 1 to 5.

To assess the association between both measures of exposure and the likelihood of BLL greater or equal to 2 µg/dl.

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Population StudySamples collectionCumulative exposure variablesOverview on Statistical analysis

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METHODOLOGYRESULTS


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Where are children from ? Selected from four large districts:

1) Mercier-Hochelaga-Maisonneuve2) Saint-Laurent3) Verdun4) Villeray-Saint-Michel-Parc-Extension

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METHODOLOGYRESULTS


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Who are they?

306 children aged under 6

Child should drink tap water regularly [1]be born in Canada, [2]live in the residence for at least one year, [3]not live outside home more than 2 days per week [4] no suffer from severe disease [5]

Families should not use a water filtration system [6]Families should live in single-house unit or multi-units apartments with 3 levels or less [7]

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METHODOLOGYRESULTS


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Who are they?

Age (Months)

12-23 50 (16%)

24-35 66 (22%)

36-71 190 (62%)

Girls 153 (50%)

Caucasians 207 (68%)

Day Care attendance 229 (75%)

Mother with university degree

221 (73%)

Hand-to-Mouth behaviour 148 (49%)

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METHODOLOGYRESULTS


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Who are they?

Age (Months)

N (%) BLL † BLL ≥ 2 µg/dL

12-23 50 (16.0%) 1.27 (0.91 – 1.76)

7 (14.3%)

24-35 66 (22.0%) 1.40 (1.00 – 1.91)

16 (24.6%)

36-71 190 (62.0%) 1.31 (0.95 – 1.72)

30 (16.3%)

Median (p25-p75): Expressed in µg/dL

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METHODOLOGYRESULTS


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Samples collection

Largely described elsewhere

Water samples

WLLF5 WLLS1

WLLS2

WLLS3

WLLS45 min

flushing30 min of

stagnation

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METHODOLOGYRESULTS


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Sample collection


Water samples

Dust samplesWindowsill dust : Floor dust: sampled in the center of the available floor space 1) Child’s room 2) Home entrance 3) Another room frequently used

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METHODOLOGYRESULTS


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Sample collection


Water samples

Dust samples

Paint samples

1) X-ray fluorescence evaluation2) Collection of paint chips and lab measurement of lead level

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METHODOLOGYRESULTS


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Cumulative lead exposure index

Firstly: Modeling seasonal changes of environmental lead

CLEI for water

CLEI = Qe*0.50*∑ [WLLi*exp(-(Ln 2/30)*(N-i))] (expressed in µg)

Daily amount of water consumed

mean water lead level observed for the day i before

day of visit

Gastrointestinal absorption rate

N from 0 to 149

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METHODOLOGYRESULTS


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CLEI for water


Worst-case exposure scenario: refers to the highest water lead concentration in the samples collected after stagnation time of 30 minutes. Best-case exposure scenario: refers to the sample collected after 5 minutes of flushing

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METHODOLOGYRESULTS


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CLEI for water


CLEI for dust

CLEI = Qe*0.30*DLL*∑ [exp(-(Ln 2/30)*(N-i))] (expressed in µg)

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METHODOLOGYRESULTS


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Statistical analysis

Linear regression Ordinary least square evaluation Effect estimates Standardized partial regression coefficients Independent contribution of each exposure

To estimate the effects of both CLEI and cross-sectional measures of water lead and residential dust lead on BLL in children aged 1 to 5.

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METHODOLOGYRESULTS


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Statistical analysis

Logistic regression Maximum-likelihood estimation Effect estimates

To assess the association between both measures of exposure and the likelihood of BLL greater or equal to 2 µg/dl.

Crude models

Semi-adjusted models

Adjusted models

Each exposure variable alone

Models including all exposure variables

Full model including all covariates

Propensity Score methods

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Unadjusted linear effectsAdjusted CLEI effectsAdjusted Cross-sectional effectsLikelihood of BLL ≥ 2 µg/dL

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METHODOLOGYRESULTS


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Unadjusted linear effects of environmental lead on BLL

Cumulative lead exposure index † Cross-sectional measure of exposure ††

Estimate 95% CI R-Square Estimate 95%CI R-Square

Intercept 0.1459 0.0714; 0.22050.0986

Intercept 0.2116 0.1393; 0.28380.0353

Water (Worst scenario) 0.0665 0.0431; 0.0899 Water (Worst scenario) 0.0170 0.0067; 0.0274

Intercept 0.1587 0.0866; 0.23080.0964

Intercept 0.1786 0.1050; 0.25210.0667

Water (Best scenario) 0.1231 0.0792; 0.1670 Water (Best scenario) 0.0591 0.0338; 0.0844

Intercept 0.2318 0.1650; 0.2987 0.0501 Intercept 0.2295 0.1613; 0.2977

0.0465Windowsill dust loading 0.0003 0.0001; 0.0004 Windowsill dust loading

0.0033 0.0015; 0.0051

Intercept 0.2412 0.1761; 0.30640.0294

Intercept 0.2440 0.1793; 0.30880.0277

Floor dust loading 0.0022 0.0007; 0.0036 Floor dust loading 0.0243 0.0078; 0.0408

1) R-Squares obtained with CLEI were greater than those by modeling cross-sectional exposure.

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Intercept 0.1459 0.0714; 0.22050.0986

Intercept 0.2116 0.1393; 0.28380.0353


Intercept 0.1587 0.0866; 0.23080.0964

Intercept 0.1786 0.1050; 0.25210.0667




0.0033 0.0015; 0.0051

Intercept 0.2412 0.1761; 0.30640.0294

Intercept 0.2440 0.1793; 0.30880.0277


2) Low values of R-squares (<9%) indicate that an exposure source taking alone is not enough to explain the variability observed in the log(BLL).

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METHODOLOGYRESULTS


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Intercept 0.1459 0.0714; 0.22050.0986

Intercept 0.2116 0.1393; 0.28380.0353


Intercept 0.1587 0.0866; 0.23080.0964

Intercept 0.1786 0.1050; 0.25210.0667




0.0033 0.0015; 0.0051

Intercept 0.2412 0.1761; 0.30640.0294

Intercept 0.2440 0.1793; 0.30880.0277


3) Significant crude association between Log(BLL) and Water lead, Windowsill dust loading and Floor dust loading

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METHODOLOGYRESULTS


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Adjusted linear effects of CLEI on BLL

1) Water lead and windowsill dust remain markedly associated with Log(BLL) (β=0.0758, p=0.0002 and β=0.0002, p=0.0058 respectively).

Unstandardized estimate

95% CI Standardized estimate

95% CI

Worst scenario

Intercept -0.0482 -0.9391; 0.8427 0.1747 -0.6928; 1.0421

Water 0.0758 -0.0359; 0.1156 0.1819 -0.1483; 0.4565

Windowsill dust loading 0.0002 -0.0001; 0.0004 0.0967 -0.0665; 0.3158

Floor dust loading 0.0007 -0.0014; 0.0028 0.0277 -0.0959; 0.1995

Paint lead

Reference level 0 0

Level-1 exposure 0.0735 -0.0885; 0.2356 0.0735 -0.0885; 0.2356

Level-2 exposure 0.2789 0.0599; 0.4979 0.2789 0.0599; 0.4979

Adjusted R-Square 0.2115

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METHODOLOGYRESULTS


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Adjusted linear effects of CLEI on BLL

2) paint-lead effect was also strongly significant in children exposed to paint chips with high lead level (paint chips ≥ 5000 mg/kg) compared with those living in homes without paint chips and low lead level in painted surface (XRF < 1 mg/cm2).



95% CI

Worst scenario

Intercept -0.0482 -0.9391; 0.8427 0.1747 -0.6928; 1.0421

Water 0.0758 -0.0359; 0.1156 0.1819 -0.1483; 0.4565



Paint lead

Reference level 0 0

Level-1 exposure 0.0735 -0.0885; 0.2356 0.0735 -0.0885; 0.2356

Level-2 exposure 0.2789 0.0599; 0.4979 0.2789 0.0599; 0.4979


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METHODOLOGYRESULTS


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Adjusted linear effects of cross-sectional exposure on BLL

1) Water lead effect was no longer statistically significant (β=0.0106, p=0.0884).



95% CI

Worst scenario

Intercept 0.3656 -0.5196; 1.2508 0.4888 -0.3889; 1.3664

Water 0.0106 -0.0016; 0.0227 0.0598 -0.0091; 0.1288



Paint lead

Reference level 0 0

Level-1 exposure 0.1179 -0.0463; 0.2820 0.1179 -0.0463; 0.2820

Level-2 exposure 0.3008 0.0710; 0.5306 0.3008 0.0710; 0.5306


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METHODOLOGYRESULTS


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Adjusted linear effects of cross-sectional exposure on BLL

2) Adjusted R-square remains low by modeling cross-sectional exposure (0.1557 versus 0.2115 for CELI) .



95% CI

Worst scenario

Intercept 0.3656 -0.5196; 1.2508 0.4888 -0.3889; 1.3664

Water 0.0106 -0.0016; 0.0227 0.0598 -0.0091; 0.1288



Paint lead

Reference level 0 0

Level-1 exposure 0.1179 -0.0463; 0.2820 0.1179 -0.0463; 0.2820

Level-2 exposure 0.3008 0.0710; 0.5306 0.3008 0.0710; 0.5306


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METHODOLOGYRESULTS


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Association between CLEI (worst scenario) and BLL ≥ 2 µg/dl

Crude OR (95% CI) Adjusted OR (95% CI)

Model 1a Model 2b

Water (Worst scenario) (µg/kg of bw) < 1.12 1 1 1

1.12 - 2.92 1.20 (0.65 - 2.21) 0.69 (0.29 - 1.65) 1.11 (0.51-2.41)≥ 2.92 4.00 (2.41 - 6.65) 3.57 (1.74 - 7.32) 3.70 (1.93-7.11)

Windowsill dust loading (µg/kg of bw)

< 87.03 1 1 187.03 - 239.67 0.92 (0.49 - 1.73) 0.42 (0.16 - 1.10) 0.76 (0.35-1.72)

≥ 239.67 2.53 (1.55 - 4.15) 1.03 (0.45 - 2.37) 1.98 (1.03-3.82)Floor dust loading (µg/kg of bw)

< 8.12 1 1 18.12 - 20.47 2.09 (1.22-3.59) 3.64 (1.58 - 8.39) 1.97 (1.01-3.87)

≥ 20.47 2.44 (1.42-4.21) 3.44 (1.46 - 8.07) 2.25 (1.13-4.48)

Paint lead c

Reference level 1 1 1

Level-1 exposure 1.16 (0.68-1.97) 1.48 (0.65 - 3.37) 1.10 (0.56-2.14)Level-2 exposure 3.23 (1.78-5.84) 6.08 (2.21 - 16.71) 3.04 (1.44-6.42)

-2Log(Likelihood) 516.85 343.82

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METHODOLOGYRESULTS


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Model 1a Model 2b


1.12 - 2.92 1.20 (0.65 - 2.21) 0.69 (0.29 - 1.65) 1.11 (0.51-2.41)≥ 2.92 4.00 (2.41 - 6.65) 3.57 (1.74 - 7.32) 3.70 (1.93-7.11)


< 87.03 1 1 187.03 - 239.67 0.92 (0.49 - 1.73) 0.42 (0.16 - 1.10) 0.76 (0.35-1.72)


< 8.12 1 1 18.12 - 20.47 2.09 (1.22-3.59) 3.64 (1.58 - 8.39) 1.97 (1.01-3.87)

≥ 20.47 2.44 (1.42-4.21) 3.44 (1.46 - 8.07) 2.25 (1.13-4.48)

Paint lead c




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METHODOLOGYRESULTS


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Model 1a Model 2b


1.12 - 2.92 1.20 (0.65 - 2.21) 0.69 (0.29 - 1.65) 1.11 (0.51-2.41)≥ 2.92 4.00 (2.41 - 6.65) 3.57 (1.74 - 7.32) 3.70 (1.93-7.11)


< 87.03 1 1 187.03 - 239.67 0.92 (0.49 - 1.73) 0.42 (0.16 - 1.10) 0.76 (0.35-1.72)


< 8.12 1 1 18.12 - 20.47 2.09 (1.22-3.59) 3.64 (1.58 - 8.39) 1.97 (1.01-3.87)

≥ 20.47 2.44 (1.42-4.21) 3.44 (1.46 - 8.07) 2.25 (1.13-4.48)

Paint lead c




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METHODOLOGYRESULTS


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Model 1a Model 2b


1.12 - 2.92 1.20 (0.65 - 2.21) 0.69 (0.29 - 1.65) 1.11 (0.51-2.41)≥ 2.92 4.00 (2.41 - 6.65) 3.57 (1.74 - 7.32) 3.70 (1.93-7.11)


< 87.03 1 1 187.03 - 239.67 0.92 (0.49 - 1.73) 0.42 (0.16 - 1.10) 0.76 (0.35-1.72)


< 8.12 1 1 18.12 - 20.47 2.09 (1.22-3.59) 3.64 (1.58 - 8.39) 1.97 (1.01-3.87)

≥ 20.47 2.44 (1.42-4.21) 3.44 (1.46 - 8.07) 2.25 (1.13-4.48)

Paint lead c




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METHODOLOGYRESULTS


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Association between CS (worst scenario) and BLL ≥ 2 µg/dl


Model 1a Model 2b

Water (Worst scenario) (µg/L)

< 2.16 1 1 1

2.16 - 4.96 1.51 (0.82 - 2.76) 1.48 (0.64 - 3.44) 1.40 (0.64 - 3.03)≥ 4.96 4.47 (2.64 - 7.57) 3.17 (1.50 - 6.71) 4.21 (2.16 - 8.19)

Windowsill dust loading (µg/ft2)

< 7.15 1 1 17.15 – 20.69 1.19 (0.65 - 2.17) 0.96 (0.41 - 2.26) 1.23 (0.53 - 2.38)

≥ 20.69 2.65 (1.61 - 4.36) 1.89 (0.88 - 4.04) 2.47 (1.30 - 4.69)Floor dust loading (µg/ft2)

< 0.70 1 1 1

0.70 - 1.62 2.20 (1.28 - 3.78) 1.60 (0.74 - 3.44) 1.95 (0.99 - 3.85)≥ 1.62 2.26 (1.31 - 3.88) 1.60 (0.73 - 3.51) 1.92 (0.96 - 3.84)

Paint lead c


Level-1 exposure 1.14 (0.68 - 1.97) 0.93 (0.42 - 2.08) 1.08 (0.56 - 2.01)Level-2 exposure 3.23 (1.78 - 5.84) 4.48 (1.73 – 11.60) 3.04 (1.45 - 6.37)


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METHODOLOGYRESULTS

CONCLUSIONS & PERSPECTIVES

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In the absence of cohort studies or Bone lead measures, cumulative lead exposure index is more appropriate than cross-sectional measures to estimate the association between lead exposure and Blood lead

In young children (aged under 6) included in this study:

If all other factors are kept stables, then for each additional increase in water cumulative exposure, BLL is expected to increase 1.08 µg/dl (p=0.0002).

If all other factors are kept stables, then for each additional increase in cumulative exposure of windowsill dust loading, BLL is expected to increase 1.00 µg/dl (p=0.0058).

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METHODOLOGYRESULTS


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In the absence of cohort studies or Bone lead measures, cumulative lead exposure index is more appropriate than croiss-sectional measures to estimate the association between lead exposure and Blood lead


The mean BLL in children exposed to paint chips with high lead level (paint chips ≥ 5000 mg/kg) is 1.32 µg/dl higher than mean BLL observed in those living in homes without paint chips and low lead level in painted surface (XRF < 1 mg/cm2)

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METHODOLOGYRESULTS


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1 unit of change in Cumulative floor dust loading does not markedly influence the BLL…However, floor dust loading is significantly associated with the odds of BLL ≥ 2 µg/dl from 8.12 µg/kg of body weight

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METHODOLOGYRESULTS


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The odds of BLL ≥ 2 µg/dl is 4 times higher in children with water cumulative lead ≥ 2.92 µg/kg of bw when compared with those with water cumulative lead < 1.12 µg/kg of bw In the children under the present study, water lead is the first largest contributor to BLL, followed by paint-lead and windowsill dust loading.

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METHODOLOGYRESULTS


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Future challenges :

Compare results obtained from cross-sectional measures of exposure with those reported in previous studies

Assess the departure from odds-ratio multiplicativity (and additivity) that may be due to nutritional factors , children’s characteristics and/or guardian’s socioeconomic position.

Translate cumulative lead exposure index in terms of public health languages (recommendations)

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Acknowledgment:

Canadian Water Network

Ministry of Environment and sustainable development (MDDEP)

Canada Health

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Research Team:Patrick LevalloisJulie St-LaurentDenis GauvinMarilène CourteauMichèle PrévostSchokoufeh NourFrance LemieuxMonique D’ArmourPat Rasmussen

Celine CampagnaElise DeshommesSuzanne GingrasAlain LeBlancAnnick Trudelle

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THANK YOU !

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In the database we received, Paint lead was a categorical variable :

Reference level XRF < 1 mg/cm2

Level-1 exposure

XRF ≥ 1 mg/cm2 OR Paint chips < 5000 mg/kg

Level-2 exposure

Paint chip ≥ 5000 mg/kg

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Descriptive analysis of Environmental Exposure

Median (p25 – p75)

Water Lead (µg/dL)

WLLF5 1.24 (0.26 – 2.68)

WLLS1 2.33 (0.76 – 4.25)

WLLS2 2.24 (0.62 – 4.05)

WLLS3 1.99 (0.46 – 4.49)

WLLS4 1.90 (0.41 – 4.83)

Dust Lead (µg/ft2)

Floor dust 0.70 (0.35 – 1.62)

Windowsill dust 7.15 (2.56 – 20.70)

montreal lead study: association between cumulative lead exposure index and blood lead levels in 1-5...

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