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Environmental Pollution 191 (2014) 38e49

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Environmental Pollution

journal homepage: www.elsevier .com/locate/envpol

Pathways of Pb and Mn observed in a 5-year longitudinal investigationin young children and environmental measures from an urban setting

Brian Gulson a,b,*, Karen Mizon a, Alan Taylor c, Michael Korsch b, J. Michael Davis d,Honway Louie e, Michael Wu e, Laura Gomez b, Luminita Antin e

aGraduate School of the Environment, Macquarie University, Faculty of Science, Sydney, NSW 2109, AustraliabCommonwealth Scientific and Industrial Research Organisation (CSIRO), Earth Science and Resource Engineering, Sydney, AustraliacDepartment of Psychology, Macquarie University, Sydney, AustraliadUS EPA, Research Triangle Park, NC, USAeNational Measurement Institute, Sydney, Australia

a r t i c l e i n f o

Article history:Received 13 February 2014Received in revised form5 April 2014Accepted 7 April 2014Available online xxx

Keywords:PbMnChildrenBloodHandwipesDustSoilDietPathways

* Corresponding author.E-mail address: brian.gulson@mq.edu.au (B. Gulso

http://dx.doi.org/10.1016/j.envpol.2014.04.0090269-7491/� 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

We monitored 108 children �5 years on a 6-month basis for up to 5 years in a major urban setting.Samples (n w 7000) included blood, urine, handwipes (interior, and after exterior playing), 6-dayduplicate diet, drinking water, interior house and day care dust-fall accumulation using petri dishes,exterior dust-fall accumulation, exterior dust sweepings, paint, soil and urban air. The geometric meanblood Pb (PbB) was 2.1 mg/dL and blood Mn (MnB) was 10.0 mg/L. Following a path modelling approach,mixed model analyses for a fully adjusted model showed the strongest associations for PbB were withinterior house dust and soil; for MnB there were no significant associations with any predictors. Predictorvariables only explained 9% of the variance for Pb and 0.7% for Mn. Relationships between environmentalmeasures and PbB in children are not straightforward; soil and dust sweepings contribute only about 1/5th of the amounts to PbB found in other studies.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

The environment and diet are critical factors in thewell-being ofyoung children, especially their potential exposure to toxic metalssuch as Pb andMn. The literature abounds with papers focussing onspecific toxic elements such as Pb but the majority address onlyenvironmental levels and are not specifically related to children oradults; moreover, they provide little if any information on otherelements and are cross-sectional in design (studies summarized inUS EPA, 2013). In contrast to the non-physiological role of Pb, Mn isan essential trace element and several human enzyme systems areeither activated or require Mn, and Mn plays an important role inmetabolism, the nervous system and other key systems and func-tions (Davis, 1998). Studies of young children (up to 6 years of age)have suggested that environmental exposure to Mn in utero could

n).

affect early psychomotor development (Takser et al., 2003). A majorsource of exposure to Pb historically has been tetraethyl Pb (TEL) ingasoline. More recently, the introduction of methyl-cyclopentadienyl manganese tricarbonyl (MMT) to replace TEL ingasoline has raised the possibility of gasoline being a source of Mnexposure (Davis et al., 1998). Although both TEL and MMT areorganometallic compounds, combustion of fuel mixtures contain-ing these additives produces particulate matter comprising inor-ganic compounds of the respective metals. Emission of theseparticles in vehicle exhaust can result in their wide dispersionthrough the environment and exposure of human populations(Davis et al., 1998).

Along with identifying these and other sources of Pb and Mnexposure, knowledge of the environmental pathways leading tohuman exposure is critical. Pathways include aerial deposition insoil/dust from motor vehicle emissions, air particulates and thenaccumulation in external and internal residential dusts and thenvia mouthing/and or inhalation in the children. House dust is asignificant contributor to PbB levels in children (Bornschein et al.,

Fig. 1. Flow chart illustrating the study design. Air Pb can contribute to all variables except paint.

B. Gulson et al. / Environmental Pollution 191 (2014) 38e49 39

1985; Charney et al., 1980; Duggan, 1983; Duggan and Inskip,1985; Gulson et al., 1995a,b 2013; Inskip and Hutton 1988;Lanphear et al., 1995, 1996, 1998a, 1998b; Laxen et al., 1987;Mielke et al., 1997, 2010; review by Paustenbach et al., 1997;Thornton et al., 1990) and its main metric has been via vacuumcleaner dust for elemental concentrations and/or surface wipes(US EPA (2000); US HUD (2001)). For longitudinal studies a morerobust method for dust exposure is dustfall accumulation usingtrays (Angle and McIntire, 1979; Clark et al., 1991; Van Alphen,1999) or petri dishes (Gulson et al., 1995a,b, 2003, 2006, 2009)which provide a measure of dust accumulation over time ratherthan only metal concentrations. Likewise a more direct measure ofexposure is via handwipes of the children (Buchet et al., 1980;Bornschein et al., 1985; Gulson et al., 2006; Manton et al., 2000;Viverette et al., 1996) but this approach has been infrequentlyimplemented possibly because of perceived inconvenience to thechildren and interpretation of the results.

Table 1Descriptive statistics for Mn and Pb in blood.

Gender Percentiles

5 10 25

PbB Male 0.88 1.03 1.50PbB Female 0.89 1.10 1.50MnB Male 4.90 5.93 8.00MnB Female 5.00 6.47 8.70

Age 0.5e2 yr Age 2e3 yr

PbB MnB PbB MnB

Geomean 2.7 13.0 2.4 10.5Median 2.7 12.0 2.4 11.0Standard deviation 2.6 6.4 2.1 4.3Range 18.4 43.2 17.3 26.0Minimum 0.6 1.8 0.7 2.0Maximum 19.0 45.0 18.0 28.0Count 156 146 169 165

PbB in mg/dL; MnB in mg/L.

As part of a 5-year longitudinal study to evaluate potentialchanges to the environment and exposure of young childrenassociated with the introduction of MMT into Australia in 2001 andits cessation of use in 2004 and cessation of use of Pb in gasoline in2002, samples of blood and urine and environmental materialshave been analysed for a suite of 20 elements using inductivelycoupled plasma methods resulting in w7000 samples from 108children. Samples as described in the following section werecollected every 6 months from children in residences located atvarying distances from major traffic thoroughfares in Sydney, NewSouth Wales and in the surrounding suburbs. Earlier papers pre-sented preliminary results for Pb andMn in house dust, handwipes,and blood collected over three 6-month cycles, i.e., an 18-monthperiod (Gulson et al., 2006), the impact of MMT on Sydney air(Cohen et al., 2005; Gulson et al., 2007), and the blood results(Gulson et al., 2008). This paper describes results encompassing the5-year period for Pb and Mn. Because of the limited statistically

50 75 90 95

2.10 3.13 4.38 5.772.00 3.00 4.03 5.30

10.00 13.00 17.00 20.0011.00 13.00 16.30 18.00

Age 3e4 yr Age 4e5 yr Age 5e7 yr

PbB MnB PbB MnB PbB MnB

2.0 9.1 1.9 9.6 1.7 9.62.0 9.6 1.9 10.0 1.7 9.91.3 3.5 2.8 3.6 1.2 3.58.6 19.0 23.8 22.0 6.7 19.00.1 1.0 0.2 1.0 0.4 1.08.7 20.0 24.0 23.0 7.1 20.0

133 133 117 117 134 134

B. Gulson et al. / Environmental Pollution 191 (2014) 38e4940

significant effects observed for Mn and the greater overall interestin Pb, we have focused more strongly in this paper on Pb.

2. Materials and methods

2.1. Study design

The approach we adopted was to investigate the relationship between envi-ronmental sources and PbB and MnB, and also the pathways between the potentialenvironmental contributors to blood shown in Fig. 1. The approach is comparablewith path or structural equation modelling as outlined by Bornschein et al. (1985)although our statistical analyses were based on the linear mixed model asdescribed below.

2.2. Participants

One hundred and eighteen children were enlisted for the study and 12 dis-continued, usually because of change of location. The cohort consisted of 51 femalesand 57 males whose ages ranged at the first data collection from 0.29 to 2.4 yearswith a mean of 1.3. There were 3 sets of twins and 3 sets of siblings (Table 1,Supplementary notes). Recruitment of participants was opportunistic by approachesto parents with assistance for introduction from the Play Group Association of NSW,the LEAD Group, Early Childhood Centres of NSW, Long Day Childcare Centres, andadvertising and an article about the study in the widely-distributed free magazine“Sydney’s Child.” Selection criteria were that the children: 1. were approximately 6monthse18 months of age, 2. lived within varying distances from major trafficthoroughfares with the main focus on those that lived within 100 m, 3. resided in ahome distant from any known Mn and Pb source such as a ferro-alloy industry orrailways, and 4. had parents who were not engaged in such industries. Each subjectwas assigned a “traffic proximity” rating from 1 (low) to 5 (high) based on residencedistance from the roads and traffic density on the respective roads. Daily traffic flowinformation was obtained from the NSW Roads and Traffic Authority database andflows range up to 80,000 vehicles per day.

Some details of the children are provided in Table 1, Supplementary notes.This study has been approved by the human ethics committee at Macquarie

University.

2.3. Collection of environmental samples

Sampling has been undertaken on 6-month cycles from July 2001 to July 2006.Soil samples and exterior dust sweepings on hard surfaces such as concrete or

brick or tile paving (using dust pan and soft haired kitchen hand broom overw1m2,both wiped with baby wipes after each use) from front and back areas around thehouses were collected in zip-lock plastic bags at 6-month intervals to provide in-formation on current deposition of Pb and Mn.

The children’s dietary intakes for six days were obtained using a 6-day duplicatediet protocol during the same time periods as the environmental sampling.

Drinkingwater samples, as part of the dietary intake, were collected on the sameoccasions after running the tap for about 30 s. The protocols for sample collectionand preparation are described in Gulson et al. (1997).

Handwipes for each hand of the children were collected into cleaned poly-ethylene centrifuge test tubes prior to, and after, the child played outdoors. Bothhands front and back and each finger were wiped individually using a “Johnson &Johnson” baby wipe. Wipe 1 refers to handwipes of children prior to playing out-doors and Wipe 2 to wipes taken after playing outdoors for varying periods of time,usually about 1 h. The second wipe protocol was not instigated until the secondsampling period. Additional wipes were obtained after the child attended childcare(wipe type 3) and of surfaces such as the top of clothes driers exposed to externalconditions (wipe type 4).

Dustfall accumulation in two frequented areas of the house (child’s bedroom,living/play room) were collected over 6-month periods by the petri-dish method(Gulson et al., 1995a,b) to provide ongoing monitoring of dust Mn and Pb and othermetal loadings (expressed as amount of metal/area/time). When the child spenttime at a childcare centre, dust accumulation was monitored at that centre for thesame duration as the home. To obtain more information about the possible transferof exterior dust to the house interior, petri dishes were also placed on covered patiosand front porches facing traffic thoroughfares.

If peeling paint was observed, and the house was built prior to 1970, the pres-ence of Pb was checked with a spot test kit (Lead Check swabs) and if positive,samples were taken for analysis. From 1 to 5 samples were collected from eachhousehold. Individual samples were analysed separately and the data aggregated forthe statistical analyses.

2.4. Collection of blood samples

Venous blood samples were collected by a trained phlebotomist into ultra-tracemetal free Vacutainer tubes using a 23G 3/4 Vacutainer blood collection set con-sisting of 1200 tubing with multiple sample Luer adapter (“butterfly”). The child’sweight at each visit was measured using portable electronic scales.

More details of the sampling procedures can be obtained from the first author.

A questionnaire was administered at the time of the first sampling and updatedthroughout the study. Information was obtained about the location of the residencewith respect to traffic, age and condition of the residence, metal exposure, and morepersonal details relevant to the parents and child. A copy of the questionnaire isgiven in the Supplementary notes.

2.5. Sample preparation, analysis and QA/QC

Details of these procedures are given in Gulson et al. (2006) and more details ofQA/QC are described in Gulson et al. (2008).

2.6. Statistical analysis

The data consisted of observations collected over varying periods for 108 par-ticipants. The number of observation-occasions ranged from2 to 13 per subject, witha mean of 9.

Descriptive statistics were estimated from untransformed data, and Pearsoncorrelation coefficients were determined on non-imputed data aggregated for eachsubject using IBM/SPSS version 21.

For the purposes of analysis and because of the major interest in potentialchanges in PbB and MnB over time associated with the cessation of Pb in gasoline in2002 and then MMT in 2004, the observations for each subject were organised intothree-month periods; the periods (e.g., JulyeSeptember, OctobereDecember) werethe same for each subject. Despite this aggregation of the observations, the practi-calities of data collection meant that data from different sources (e.g., blood, food)did not always occur in the same period. While this had no implications for analysesbased on data from a particular source (e.g., blood), it caused difficulties for cross-source analyses (e.g., relating PbB level to the level of Pb in food). The main prob-lem was that a large number of observations were lost to the analysis because ameasurement in a given period from one sourcewas notmatched by ameasurementfrom another source in the same period. Coarser aggregation, into six-month pe-riods, did not substantially reduce the data loss.

The solution we adopted was to treat the periods which, for each subject, con-tained at least five of the seven possible blood measurements as the units foranalysis and to obtain values for other sources which were not measured in thatperiod by linear interpolation, based on the observations from that source in otherperiods. Once the observations for periods which did not contain the minimumnumber of blood measurements had been used in the interpolation, they weredropped from the analysis.

As interpolation is subject to error, it was carried out with Amelia II (Honakeret al., 2007; King et al., 2001), a multiple imputation program which creates mul-tiple datasets, with the variations in imputed values over datasets reflecting theuncertainty in the imputed values. Amelia II was especially appropriate because itallows imputation within time-series (in this case, observations over time for eachsubject) as well as within cross-sections. The process is referred to here as linearimputation because the imputations were based on linear fits to the time-series dataon the grounds that there were too few observations per person to support higher-order fits. Priors were set for each variable by specifying the standard deviation ofthe observed measurements. Inspection showed that the interpolated values fellinto the ranges which could be expected given the observed values, and reflected thetrends evident in individual data over time. Inspection also suggested that inter-polation based on the whole set of points for an individual produced more satis-factory estimates than would have been obtained by carrying forward (or back)single values from neighbouring periods.

Amelia II was used to produce 10 imputed datasets and separate analyses werecarried on each dataset, using a mixed model with subject as a random factor. Theresults from the separate analyses were combined using the formulae originallyprovided by Rubin (1987). These formulae combine information about within- andbetween-dataset variation which is used to form the standard errors for parameterestimates.

A mixed model analysis (IBM/SPSS version 21) was used in order to study therelationship between the concentration of each metal and each of the following:time inmonths since the first collection; category of traffic proximity, (centred at themean) gender; age (at first collection, centred at the mean); age of housing (builtbefore 1970 and after 1970), type of housing (brick, cement sheeting (fibro),weatherboard), and location within the house (for petri dusts). Participants weretreated as a random factor. Time, which was coded zero for the first collection, wastreated as a continuous rather than a categorical variable because the interval be-tween collections was not uniform. The use of the mixed model made it possible totake account of, and assess, the dependencies between themultiple observations foreach subject, and to obtain efficient estimates of the parameters despite the un-balanced nature of the data (unequal numbers of observations for different partic-ipants). The variables were coded in such a way that the intercept in the reportedresults shows the mean of the transformed metal level for a male with wipe type 1(collected prior to playing outside) at the mean age of first collection and the meantraffic exposure level. That is, gender and wipe type were indicator- or dummy-coded, with males and wipe type 1 as the reference or zero-coded category, andage of first collection and traffic proximity level were centred at their means. Re-lationships were established for variables adjusted for other variables at the samelevel and for unadjusted variables (but adjusted for season, gender, traffic proximity,

B. Gulson et al. / Environmental Pollution 191 (2014) 38e49 41

age and type of housing). Results for the different samples of soil (front and back-yard), dustfall from various locations within the residence, dust sweepings (frontand backyard) and paint were aggregated for the statistical analyses.

A p value less than 0.05 was taken to be significant.

3. Results

Elemental analyses for w7000 samples have been obtained for108 participants. As previously noted, the number of observation-occasions (“periods”) ranged from 2 to 13 per subject, with amean of 9.

As paint with concentrations above 1% Pb was only found in 28of the 102 houses, paint has not been included in the analyses asmuch data would be discarded in the mixed model analyses if doneso. Paint Pb concentrations ranged from 1.0 to 34% in 44 samplesand all but one house with peeling paint was built prior to 1970.Twenty five houses were built after 1970 when the amount of Pbused in paint was lowered to 1%. Nine houses were of timberconstruction, 6 built with fibrous cement and the remainder wereof brick construction.

Tests of associations between Mn and Pb in 479 urine sampleswere not feasible as more than half the samples had Pb valuesbelow the detection limits and over 90% for Mn.

As water was a component of the 6-day duplicate diet, data ontap water were not incorporated into the statistical analyses.Drinking water levels for Pb ranged from 0.01 to 27 mg/L with ageometric mean of 1.2 mg/L (n ¼ 573) and for Mn the range was0.01e101 mg/L and geometric mean 1.6 mg/L (n ¼ 573). Apart fromthe few elevated Pb values, the levels of Pb in drinking water overall

Fig. 2. Flow chart showing bivariate relationships between blood Pb and environmental meadjusted for other variables at the same level showing the strongest association was betweeinterior house dust as the dependent variable and adjusted for exterior dust sweepings andproximity, and age and type of housing. Separate analyses were also undertaken with inteinterior house dust and soil, and the other variables of time, first period, age collected, seascoefficients are noted at the top and p values at the bottom. The dashed lines representsignificant relationships. The significant relationships between soil and PbB and dust sweepinterior house dust, diet) but are adjusted for time, first period, age collected, season, gend

contribute minimally to PbB when incorporated into the US EPAIEUBK pharmacokinetic model for children.

Relationships established for variables either adjusted for allother independent variables (i.e., other forms ofmeasurement of Pbor Mn, as well as time, season, gender, traffic proximity, age andtype of housing) or unadjusted, i.e. not adjusted for other mea-surements of Pb orMn (but adjusted for time, season, gender, trafficproximity, age and type of housing), are presented in tabular andgraphical forms, including path modelling (Figs. 2 and 3 foradjusted variables; Figs. 1 and 2 for unadjusted variables in theSupplementary notes) and box plots (Figs. 3e7 in theSupplementary notes).

A series of analyses were conducted in order to investigate, first,the association between the environmental variables and bloodlevels, and then the association between the environmental vari-ables themselves, in accordance with the model shown in Fig. 1.Thus, in the first set of analyses PbB and MnB were the dependentvariables, while in subsequent analyses handwipes, house dustaccumulation and dust sweepings respectively were the dependentvariables.

The results of each analysis are described in the following sec-tions, and are summarised in figures diagrammatically (Figs. 1 and2; Figs. 1 and 2 in the Supplementary notes) in a framework basedon the model shown in Fig. 1.

3.1. Blood

For blood sampling, the number of observations per subjectranged from 1 to 9 with a mean of 5.3 and median of 6. Descriptive

asures (diet, interior handwipes, interior house dust, exterior dust sweepings, and soil)n blood and interior house dust accumulation. Separate analyses were undertaken withsoil, and the other variables of time, first period, age collected, season, gender, trafficrior handwipes as the dependent variable and adjusted for exterior dust sweepings,on, gender, traffic proximity and age and type of housing. In the boxes, unstandardisedrelationships tested but found to be non-significant and the other arrows designateings and PbB are not adjusted for other environmental measures (interior handwipes,er, traffic proximity, and age and type of housing.

Fig. 3. Flow chart showing bivariate relationships between Mn in blood and environmental measures (diet, interior handwipes, interior house dust, exterior dust sweepings, andsoil) adjusted for other variables at the same level showing marginal associations between blood and interior house dust accumulation and blood and diet. Separate analyses werealso carried out as for Pb as described in Fig. 2 caption.

B. Gulson et al. / Environmental Pollution 191 (2014) 38e4942

statistics for the non-imputed data are listed in Table 1. There wasno significant difference between males and females (p 0.55 forPbB, 0.40 for MnB). The PbB data have been grouped according toage ranges from 0 to 7 years as many studies have shown that thehighest PbB in children are in those aged about 2e3 years, probablyassociated with crawling and hand-to-mouth activity (e.g., US EPA,2013). Our results are consistent with these observations as there isno statistically significant difference in arithmetic mean PbB for theage groups 0.5e2 years and 2e3 years (Table 1).

We observed a gradual decrease in PbB over the 5 yearsconsistent with the removal of Pb from gasoline in 2002 (Gulsonet al., 2008) and consistent with many other studies focused onthe impact on PbB following removal of Pb from gasoline (e.g.Thomas et al., 1999). The geometric mean PbB level of 2.1 mg/dL (orhighest geometric mean for the 0.5e2 year age group of 2.7 mg/dL)is less than half the reference level of 5 mg/dL recently

Table 2Pearson Correlations for Pb in blood and environmental samples.

Blood Diet Interior house dust Dust s

Blood Correlation 1 0.261 0.516 0.313Sig. (2-tailed) 0.006 <0.001 0.001

Diet Correlation 0.261 1 0.153 0.009Sig. (2-tailed) 0.006 0.113 0.925

Interior house dust Correlation 0.516 0.153 1 0.664Sig. (2-tailed) <0.001 0.113 <0.001

Dust sweepings Correlation 0.313 0.009 0.664 1Sig. (2-tailed) 0.001 0.925 <0.001

Soil Correlation 0.333 0.010 0.765 0.786Sig. (2-tailed) <0.001 0.922 <0.001 <0.001

Interior handwipes Correlation 0.458 0.057 0.535 0.366Sig. (2-tailed) <0.001 0.560 <0.001 <0.001

Exterior handwipes Correlation 0.430 0.185 0.448 0.459Sig. (2-tailed) <0.001 0.119 <0.001 <0.001

Childcare dust Correlation 0.356 0.255 0.369 0.407Sig. (2-tailed) 0.015 0.087 0.012 0.005

N ¼ 108; Exterior handWipes N ¼ 72; Childcare dust N ¼ 46.

recommended by the US Centers for Disease Control and Preven-tion (US CDC, 2012a,b). Eight of the 108 children (8%) had aPbB> 10 mg/dL, the current Australian National Health and MedicalResearch Council guideline. Four of these children had aPbB � 15 mg/dL, requiring notification to the New South WalesHealth department.

There is no recognized reference level for Mn in blood but thevalues in Table 1 are consistent with those in the literature for “non-exposed” adults and children, the mean values for which rangefrom 6 to 12 mg/L, summarized in Gulson et al. (2006). There was asmall decrease of Mn in blood over the 5 years (Gulson et al., 2006);MMT was discontinued in Pb-replacement gasoline in 2004. Sincewe published the blood metal results in 2008, there have beenseveral other papers published providing results for Pb and Mn(e.g., Ferré-Huguet et al., 2009; Röllin et al., 2007; Ngueta andNdjaboue, 2013).

weepings Soil Interior handwipes Exterior handwipes Childcare dust

0.333 0.458 0.430 0.356<0.001 <0.001 <0.001 0.0150.010 0.057 0.185 0.2550.922 0.560 0.119 0.0870.765 0.535 0.448 0.369

<0.001 <0.001 <0.001 0.0120.786 0.366 0.459 0.407

<0.001 <0.001 <0.001 0.0051 0.390 0.467 0.450

<0.001 <0.001 0.0020.390 1 0.580 0.125

<0.001 <0.001 0.4080.467 0.580 1 0.364

<0.001 <0.001 0.0190.450 0.125 0.364 10.002 0.408 0.019

Table 3Pearson Correlations for Mn in blood and environmental samples.

Blood Diet Interior house dust Dust sweepings Soil Interior handwipes Exterior handwipes Childcare dust

Blood Correlation 1 0.190 0.071 0.007 0.142 0.262 �0.175 0.092Sig. (2-tailed) 0.049 0.467 0.947 0.142 0.006 0.142 0.546

Diet Correlation 0.190 1 �0.076 0.035 �0.005 �0.058 0.122 �0.118Sig. (2-tailed) 0.049 0.435 0.717 0.959 0.549 0.308 0.439

Interior house dust Correlation 0.071 �0.076 1 0.084 0.037 0.102 0.245 �0.006Sig. (2-tailed) 0.467 0.435 0.385 0.706 0.293 0.038 0.967

Dust sweepings Correlation 0.007 0.035 0.084 1 0.363 �0.122 0.201 0.152Sig. (2-tailed) 0.947 0.717 0.385 <0.001 0.209 0.090 0.319

Soil Correlation 0.142 �0.005 0.037 0.363 1 0.130 0.029 0.068Sig. (2-tailed) 0.142 0.959 0.706 <0.001 0.178 0.810 0.657

Interior handwipes Correlation 0.262 �0.058 0.102 �0.122 0.130 1 0.299 0.132Sig. (2-tailed) 0.006 0.549 0.293 0.209 0.178 0.011 0.389

Exterior handwipes Correlation �0.175 0.122 0.245 0.201 0.029 0.299 1 �0.049Sig. (2-tailed) 0.142 0.308 0.038 0.090 0.810 0.011 0.766

Childcare dust Correlation 0.092 �0.118 �0.006 0.152 0.068 0.132 �0.049 1Sig. (2-tailed) 0.546 0.439 0.967 0.319 0.657 0.389 0.766

N ¼ 108; Exterior handWipes N ¼ 72; Childcare dust N ¼ 46.

B. Gulson et al. / Environmental Pollution 191 (2014) 38e49 43

3.2. Blood and environmental samples

Correlation coefficients (based on data aggregated over partic-ipants) for Pb showed that, apart from diet, the variables werehighly correlated, indicating they have a common source (Table 2).Correlations for Mn in blood and other variables (Table 3) were lessthan those for Pb with the main correlations being MnB-diet, MnB-interior handwipes, Mn interior house dust-exterior handwipes(after playing outside), Mn sweepings-soil, and Mn interiorhandwipes-exterior handwipes.

The results for the mixed model analyses with blood levels asthe dependent variable and environmental predictor variables ofhouse dust accumulation, dust sweepings, handwipes, diet and soil,which could influence PbB and MnB abundances are summarizedin Table 4 and in Table 2 of the Supplementary notes.

Compared with winter, Mn was higher in autumn and PbB washigher in spring. The higher value for PbB in spring contrasts withour previous studies of different cohorts where no or minimalseasonal effect was obvious (Gulson et al., 2000).

Therewere no significant results for MnB and PbB and proximityto traffic and there was no difference between males and females.For the same time period as in this paper, PbB and MnB decreasedover time and increasing age as outlined in more detail in Gulsonet al. (2008).

In an analysis with PbB as the dependent variable and with theadjusted predictors, none was individually statistically significant(Fig. 2; Table 2 Supplementary notes) which was as expected, giventhe strong correlations among the predictors. There was amarginally significant association of PbB and interior house dustand soil. Moreover, individually (unadjusted) the predictorsshowed some significant associations with PbB (Fig. 1Supplementary notes). Even though the robustness of the

Table 4Summary of statistically significant results for adjusted relationships between blood and

Sample Traffic Season Interior house dust

Pb Mn Pb Mn Pb Mn

Blood ☺ U U

Interior handwipes U ☺

Exterior handwipes U ☺ ☺

Interior dust U ☺

☺

NA NA

Dust sweepings ☺ U NA NA

☺Significance p < 0.05; USignificance p < 0.1; NA Not Applicable; blank space not signi

analysis is reduced by the smaller numbers, if handwipes collectedafter playing outside (exterior handwipes) and dust accumulationfrom childcare centers are included in the analyses, the only sig-nificant relationship for PbB is with interior house dust (p 0.023)(data not shown).

For the relationships of MnB with all adjusted predictors (Fig. 3;Table 2, Supplementary notes) there were no significant individualpredictors although dietary Mn and interior house dusts weremarginally significant.

Therewere no significant relationships for PbB and diet, PbB andage of housing, PbB and type of housing, or PbB and paint.

An evaluation of the impact of the predictor variables on theblood results showed that the percentage of the variance explainedby the predictors (calculated using the method described bySnijders and Bosker, 2012) was lowand varied from0.7% forMn and9% for Pb. Compared with the full model, the variance explainedwithout diet, wipes 1 and dust 1 is 4.6%, indicating a substantialcontribution of the variance arising from these variables. Comparedwith the full model, the variance without dust sweepings and soilwas 1.6%, indicating their lower contribution to the overall variance.

3.3. Environmental samples e handwipes

3.3.1. Interior handwipesAs hand-to-mouth activity is a principal route contributing to

metal exposure of young children, an estimate of metal exposurecan be gained from handwipes. The dataset comprised 1227 ob-servations for 108 participants, with a mean of 5.6 observations persubject (median 6) and a range of 1e9 for the home locations andmean of 2.4 (median 2) and range of 0e7 for the childcare locations.Samples within the residence (interior handwipes) and afterplaying outside (exterior handwipes) were supplemented by

environmental samples and between environmental samples.

Dust sweepings Soil Diet Interior handwipes

Pb Mn Pb Mn Pb Mn Pb Mn

U U

☺ NA NAU

☺

NA NA ☺ ☺

ficant.

Table 5Descriptive statistics for handwipes (mg/handwipe).

Pb W1 Mn W1 Pb W2 Mn W2 Pb W3 Mn W3 Pb W4 Mn W4

Mean 4.8 4.8 7.9 5.1 83.7 22.1 123.6 52.6Std. deviation 32.2 6.4 22.6 5.9 184.9 41.7 113.7 40.9Geometric Mean 2.4 2.2 3.7 2.8 13.0 5.1 72.2 34.5Minimum 0.09 0.03 0.15 0.06 0.22 0.16 9.20 6.20Maximum 840 25 330 53 830 150 300 94N 697 697 504 504 21 21 5 5

Wipe type Percentiles

5 10 25 50 75 90 95

Pb W1 0.7 1.0 1.5 2.3 4.0 6.3 9.2Pb W2 0.8 1.1 1.8 3.3 6.8 16.0 27.0Pb W3 0.3 1.2 3.3 5.1 115.0 242.0 773.0Pb W4 9.2 9.2 16.6 89.5 260.0Mn W1 0.4 0.6 1.0 1.6 5.3 17.0 20.1Mn W2 0.5 0.7 1.2 2.5 7.6 14.0 17.0Mn W3 0.2 0.7 1.3 5.8 32.5 122.8 148.0Mn W4 6.2 6.2 8.9 35.5 82.5

\W1 interior handwipes; W2 after playing outside; W3 extra play outside.W4 tops of hard surfaces exposed to exterior conditions.

B. Gulson et al. / Environmental Pollution 191 (2014) 38e4944

occasional sampling of the handwipes from other locations such asafter playing in the front and back yards, especially in the highertrafficked areas, and after the child had been at childcare (type 3;n¼ 25). Wipe type 4 (n¼ 5) were from surfaces exposed to exteriorconditions such as on the top of clothes driers.

Table 6(a). Descriptive statistics for Pb in dustfall accumulation (mg/m2/30 days) from petri dishedishes.

Pb PD1 male Pb PD1 female Pb PD2

(a)Mean 93.0 57.8 208Std. deviation 637 111 1746Geometric mean 21.7 27.6 28.7Median 18.4 25.1 29.1Minimum 0.2 1.3 0.4Maximum 11,390 1075 21,650N 376 330 154

Petri dust type Percentiles

5 10 25

Pb PD1 male 4.7 6.7 10.2Pb PD1 female 5.6 7.1 11.2Pb PD2 male 3.5 5.6 13.3Pb PD2 female 1.2 3.7 7.7Pb PD3 male 23.9 45.3 155Pb PD3 female 47.1 63.2 194

Mn PD1 male Mn PD1 female Mn PD2

(b)Mean 19.0 19.2 46.3Std. deviation 23 19 173Geometric mean 13.5 13.9 19.6Median 13.1 12.7 22.2Minimum 0.2 2.3 0.2Maximum 196 177 2055N 376 330 154

Petri dust type Percentiles

5 10 25

Mn PD1 male 4.7 5.6 8.3Mn PD1 female 4.1 5.4 7.9Mn PD2 male 2.2 4.8 12.0Mn PD2 female 1.9 3.4 8.1Mn PD3 male 54.5 123 216Mn PD3 female 48.4 132 211

PD1 interior house dust; PD 2 childcare centre dust; PD3house exterior dust.

Descriptive statistics for the handwipes are provided in Table 5and Figs. 3 and 4 in the Supplementary notes. There were signifi-cantly higher concentrations of Mn and Pb in wipes 1 to 4. Therewere no significant differences in either Mn or Pb for males andfemales.

s. (b). Descriptive statistics for Mn dustfall accumulation (mg/m2/30 days) from petri

male Pb PD2 female Pb PD3 male Pb PD3 female

30.2 2100 100031 8247 169117.2 390 43521.9 363 4400.2 9.6 11.2

152 80,760 10,81096 117 90

50 75 90 95

18.4 42.7 87.2 15325.1 64.7 127.0 17229.1 55.9 131.5 29921.9 37.0 68.9 104

363 1123 3138 8809440 1079 2139 4605

male Mn PD2 female Mn PD3 male Mn PD3 female

23.9 575 38729 841 33213.7 344 29114.9 333 2820.1 7.9 14.8

200 7540 258596 117 90

50 75 90 95

13.1 21.0 33.5 49.112.7 24.3 38.6 53.722.2 39.2 65.4 10814.9 27.1 50.7 75.9

333 608 1214 2203282 517 727 962

B. Gulson et al. / Environmental Pollution 191 (2014) 38e49 45

In the analysis of a possible association of interior handwipeswith interior house dust accumulation, soil and dust sweepings,interior dust Pb and soil Pb predicted the Pb in interior handwipes(Table 3 Supplementary notes; Fig. 2). Unadjusted interior housedust, dust sweepings and soils predicted the Pb in handwipes (Fig.1Supplementary notes) but all three measures were highlycorrelated.

There were no significant relationships between the Pb and Mnin wipes and traffic proximity.

With respect to season, levels of Mn in handwipes were lower inautumn compared with winter but there were no seasonal effectsfor Pb (Table 3 Supplementary notes).

As with blood, an evaluation of the impact of the predictorvariables on the interior handwipe results shows the percentage ofthe variance explained by the predictors to be very low for Mn at0.3% and only 10% for Pb.

3.3.2. Exterior handwipesAs with interior handwipes, there were significant associations

for exterior handwipes, after playing outside, with Pb in interiorhouse dust and marginally with soil but unexpectedly not withexterior dust sweepings (Table 4 Supplementary notes). There wereno significant relationships between Mn and Pb and traffic prox-imity. There were significantly higher levels of Mn and marginallyhigher levels of Pb in summer compared with winter. If the analysisincludes interior handwipe data as an additional possible contrib-utor prior to playing outside, the only significant associations for Pband Mn are with exterior handwipes is with interior handwipes(p < 0.001; data not shown).

As with blood and interior handwipes, an evaluation of theimpact of the predictor variables on the exterior handwipes resultsshowed the percentage of the variance explained by the predictorsto be negligible for Mn and 10% for Pb.

3.4. Dust accumulation with petri dishes

The advantages of dust accumulation over time as a metric forenvironmental exposure and comparisons with other studies werediscussed in Gulson et al. (2006).

The dataset consisted of 1163 analyses for 108 participants. Thenumber of observations per subject for petri dishes collecting dustover 6-month periods fromwithin the residence (n ¼ 706; PD type1) ranged from 0 to 8 with a mean of 5.2 (median 6) and from thechildcare centres there was similar range with a mean of 1.2(n¼ 250; PD type 2). To obtainmore information about the possibletransfer of exterior dust to the house interior, petri dishes were alsoplaced on covered patios and front porches facing the traffic thor-oughfares (n ¼ 207; PD type 3).

Table 7Descriptive statistics for dust sweepings and soil (mg/g).

Sweepings Pb Soil Pb Sweepings Mn Soil Mn

Mean 566 381 222 220Std. deviation 1484 536 245 190Geometric mean 174 168 156 179Minimum 1.2 11.8 8.3 17.0Maximum 19,200 4260 2850 1635N 660 329 661 329

Percentiles

5 10 25 50 75 90 95

Sweepings Pb 16.0 25.0 59.0 180 498 1239 2050Sweepings Mn 35.0 55.2 93.3 160 270 419 559Soil Pb 19.1 26.5 61.0 173 498 967 1419Soil Mn 67.0 83.5 122 180 253 370 465

There were significantly higher levels of Pb and Mn (Table 6;Figs. 5 and 6 in the Supplementary notes) in the exterior dishes(type 3) compared with both the house interior (type 1) and petridishes placed in the childcare centres (type 2). There were signifi-cantly higher levels of Mn (p 0.001) in dishes placed in the childcarecentres (type 2) compared with the house interior (type 1) petridishes but not for Pb (p 0.29).

Mixed model analysis (Table 5 Supplementary notes) showedthat the concentrations of Mn in interior house dust were higher insummer and autumn thanwinter but no such seasonal effects wereobserved for Pb. Lead concentrations in interior house dust werelower for males than females. There was a significant associationbetween the interior house dust and dust sweepings for Pb but notfor Mn.

An evaluation of the impact of the predictor variables on theinterior house dust results shows the percentage of the varianceexplained by the predictors was 0.2% for Mn and 18% for Pb.

As petri dish type 3 was for sampling outside the residence andusually facing the main traffic thoroughfare, it was expected thereshould be some association between exterior handwipes, collectedafter playing outside, and interior house dust and exterior housedust (petri dishes 1 and 3), dust sweepings and soil. Mixed modelanalyses with exterior handwipes as the dependent variableshowed there to be no significant associations with interior housedust and exterior house dust, dust sweepings and soil for either Pbor Mn (data not shown).

3.5. Dust sweepings and soil

Descriptive statistics for Mn and Pb in dust swept from aroundthe residences are listed in Table 7 and compared with Pb and Mnconcentrations in soil. There was no difference in the geometricmean concentrations for Mn and Pb in the dust sweepings versussoil.

Mixed model analyses (Table 6 Supplementary notes) showedthat therewas a significant association of the sweepings and soil forboth Pb and Mn and there was a significant association for Pb andtraffic proximity. There were no seasonal effects for Mn or Pb. Anevaluation of the impact of the predictor variables on the dustsweeping results shows the percentage of the variance explainedby the predictors was 9% for Mn and 26% for Pb.

4. Discussion

4.1. Blood relationships

In the current study the geometric mean blood Pb of 2.1 mg/dL(or 2.7 mg/dL for the maximumvalue at age 0.5e2 years) is less thanhalf the reference level of 5 mg/dL recommended by the US Centersfor Disease Control and Prevention (US CDC, 2012a,b). It is lowerthan the geometric mean value of w3.5 mg/dL in children up to 5years of age (n ¼ 75) from Esperance, Western Australia (L. Gillam,written communication, 2013) measured in 2008, and slightlyhigher than blood samples from pre-schoolers (age 0e5 years;n ¼ 100) measured in 2005 from Fremantle, Western Australiawhere the geometric mean Pb valuewas 1.83 mg/dL (Guttinger et al.,2008). The elevated PbB levels of >10 mg/dL for 8 children in ourstudy arose from renovations involving Pb paint and ceiling (attic)dust and, with assistance from the cohort coordinator (K.J.M.),these values were rapidly lowered below 10 mg/dL, except in 1 case.

Relationships between blood and environmental media for Pband Mn showed minimal associations. When all predictor variableswere incorporated into the mixed model analysis for Pb, only Pb inblood exhibited a marginally significant association with interiorhouse dust and soil Pb. There were no significant relationships for

B. Gulson et al. / Environmental Pollution 191 (2014) 38e4946

diet and blood. Apart from Pb in exterior dust sweepings andmarginally for interior house dust there were no significant asso-ciations with respect to traffic in contrast to the study of Joselowet al. (1978) from Newark USA, although this was a time of exten-sive use of Pb and Mn in gasoline.

4.2. Environmental relationships

We have attempted to define the pathways of the metals to thechildren by focussing particularly on dust because of its importanceas an exposure medium via inhalation and ingestion, the latterespecially through mouthing behaviour.

Handwipes provide information relevant to ingestion, anddustfall accumulation is relevant to both inhalation and ingestion.Handwipes obtained from the children’s exposure indoors (type 1)lie on potential pathways of soil-dust sweepings-exterior dustfallaccumulation-interior house dust (Fig. 1). Elements in these sam-pling media could come from lithogenic sources (soil), legaciesfrom industrial and/or motor vehicle emissions, and from theresidence itself, especially from material such as leaded paint.When adjusted for interior house dust accumulation (petri dust 1),sweepings and soil there was a significant association for interiorhandwipes with interior house dust and soil, as was the case for theassociation of PbB. There were no significant relationships for Pband Mn in interior handwipes and proximity to traffic.

As might be expected, handwipes obtained after the childrenhad played outside (type 2) had higher levels of metals comparedwith the handwipes obtained from interior exposure but the levelswere only marginally significant for Pb (p 0.06). The differencebetween the two sampling media may be due to the shorterexposure time of the children outdoors. As with interior hand-wipes, Pb in exterior handwipes was significantly associated withinterior house dust (petri dish 1) and marginally with soil. Therewere no significant relationships between Pb and Mn in exteriorhandwipes and proximity to traffic.

Along with handwipes, interior house dust accumulation mightbe expected to provide a critical indicator of exposure for childrenthrough inhalation and ingestion. Interior house dust Pb and soil Pbprovided the strongest associations with PbB and there was astrong association between exterior dust sweepings and interiorhouse dust (Fig. 2; Fig. 1 Supplementary notes).

There is a strong association between Pb in soil and Pb in dustsweepings, and Pb in handwipes and Pb in soil (Tables 3 and 6Supplementary notes; Fig. 2; Fig. 1 Supplementary notes).

The lack of statistical associations for Mn compared with Pb isprobably due to the limited volume of MMT used in only TEL-replacement gasoline and the limited period of its use from 2001to 2004, as well as high background levels of Mn found in soils. Thisinformation has been discussed in detail in Gulson et al. (2006).

4.3. Comparison with other studies

Although there have been numerous published studies on Pb insoil and dust there have been none to our knowledge thatencompassed the several pathways outlined in this paper includingthe association with blood, multi-element analyses, and the lon-gitudinal approach over 5 years apart from those of the Universityof Cincinnati (Bornschein et al., 1985; Buncher et al., 1991; Clarket al., 1991; Que Hee et al., 1985; Succop et al., 1998). In theircomprehensive investigations employing structural equationmodelling, Succop et al. (1998) found that. handwipe Pb and inte-rior floor dust Pb were the most important direct contributors tothe PbB at <6 years of age. These outcomes are similar to those wehave obtained in the current study.

Some of the most comprehensive studies of recent years onhouse dust are those by Rasmussen and colleagues for 1025 urbanhomes from 13 cities in Canada under the aegis of the CanadianHouse Dust Study. In an earlier study of 50 residences in OttawaCanada, Rasmussen et al. (2001) found that house dust samplescollected from vacuum cleaner bags contained significantly higherPb, Cd, Sb and Hg compared with street dust sweepings and gardensoil samples. There were no significant correlations in comparisonsof elemental concentrations in house dust versus street dust, orhouse dust versus garden soil. In their major study of 1025 homes,Rasmussen et al. (2013) found the levels of metals (As, Cd, Cr, Cu, Ni,Pb, Zn) in vacuum cleaner dust (<80 mm) were an order ofmagnitude higher than natural geochemical background concen-trations and were attributed to anthropogenic sources. Unfortu-nately, the final step in the puzzle, that is the contribution of theelements especially Pb to the children residing in these houses wasnot undertaken and sampling was only carried out on one occasion.Furthermore, the study design or purpose of this major study wasnot to determine source-receptor relationships (Rasmussen et al.,2013) nor was it longitudinal.

In awell-constructed cross-sectional study of 2 year old children(n ¼ 97) in Birmingham (U.K.), Davies et al. (1990) measuredsamples of air, vacuum cleaner dust (owners vacuum cleaner),pavement and road dust, soil, handwipes and diet. Blood Pb con-centrations were significantly related to house dust Pb loading, rateof touching objects, water Pb concentration and parents smokinghabits. The house dust Pb “loading” was 60 mg/m2 but it is notpossible to compare this value with our measurements which wereobtained over a fixed time interval. The geometric mean handwipevalue was 5.7 mg/hand (n ¼ 704) more than double that wemeasured in our study but the U.K. study was undertaken in 1984e85 when leaded gasoline was still in use.

In a longitudinal investigation from the Pb contaminated envi-ronment of the smelting community of Port Pirie, South Australia,13 infants were followed approximately monthly from birth untilthey were about 36 months old (Simon et al., 2007). Handwipes forchildren aged >15 months were 8.6 mg Pb/hand (3.8e8.6) for fe-males and 13.0 (8.9e13.1) mg Pb/hand for males (D. Simon, writtencommunication, 2013). As expected, these values are considerablyhigher than we observed in Sydney (Table 3) and the gender dif-ference was marked whereas this was not the case in Sydney. Therewas a strong correlation between PbB and handwipe Pb for theinfants (r2 0.72, p < 0.01). Approximately 46% of the variance of theinfants PbB could be explained by the geometric mean hand-Pbloading of the infant, considerably higher than the 10% weobserved but given the contaminated environment of Port Pirie, notunexpected.

Mielke and colleagues in the US have been investigating soil-dust-blood Pb relations in urban areas over the past 2 decadeswithmost work focused on NewOrleans USA. Their recent researchon 8 Californian urbanized areas has pointed to the legacy of Pbfrom former gasoline additives and resuspension of dust as sig-nificant contributors to blood Pb of children (Mielke et al., 2010;Zahran et al., 2013a, b) as was suggested by earlier studies (e.g.De Miguel et al., 1997; Chiaradia et al., 1997; other references inZahran et al., 2013a, b). In a study in New Orleans to determine ifsoil samples from 4 sampling locations could predict PbB values,Zahran et al. (2013b) found that residential and busy street soilsamples collected within 1 m from the street could account foralmost 40% of the variation in PbB. This was higher than for soilsfrom house foundations, busy streets and open spaces. Further-more, soil Pb concentration explained 75.4% of the betweenneighbourhood variation in PbB levels in this dataset of 55,551children and 5467 surface soil samples (Laidlaw et al., writtencommunication, 2014). We observed that only 4.8% of the variance

B. Gulson et al. / Environmental Pollution 191 (2014) 38e49 47

in PbB could be explained by soil and dust sweepings and only 3.9%for soils alone and our soils had a geometric mean similar to themedian levels reported for New Orleans. Furthermore, the authorscould not decide whether the accumulated Pb in residential andbusy streets arose from the legacy of gasoline Pb or demolition/renovation of buildings with Pb paint, as was also the case forDetroit (Zahran et al., 2013a). With respect to the impact of de-molition on the environment, Farfel et al. (2005) have shown thatzones up to 100 m (and possibly more) in Baltimore USA can becontaminated during unsafe demolition, an outcome Gulson et al.(1995b) also observed in Sydney.

In the major longitudinal investigation of Biokinetics of Lead inPregnancy undertaken over a 10 year period in Australia (Gulsonet al., 2003), the control group comprised long-time female adultAustralian participants. Isotopic and Pb concentration data wereobtained for samples of duplicate diet, petri dust accumulationcollected on a 3-monthly basis, drinking water, blood, and urine.Mixed model analyses showed the only significant association ofblood to be with drinking water. There were no significant resultsfor bulk Pb concentration, the usual approach in most Pb in-vestigations into sources and pathways of Pb exposure.

In contrast, Hogervorst et al. (2007) in a study around Znsmelters in Belgium found an association between 3-monthly petridust from bedrooms and Pb and Cd in blood and urine. However,given the contamination around the smelters, such outcomes werenot unexpected or inconsistent with the long-term studies in thisarea (references given in Hogervorst et al., 2007).

In a cross-sectional study, Gulson et al. (2013) measured Pbisotopic ratios and Pb concentrations for blood and environmentalsamples from children from 24 dwellings scattered aroundAustralia as part of the only Australia-wide PbB survey ever un-dertaken (Donovan, 1996). PbB levels were �15 mg/dL and isotopeswere used in an attempt to determine the source(s) of theirelevated PbB. Comparisons were made with data for six childrenwith lower PbB levels (<10 mg/dL). Regression analyses indicatedthat the only statistically significant relationship for blood isotopicratios was with dust wipes (p 0.026); there were no significantassociations for Pb concentrations in blood and environmentalsamples. There was a strong isotopic correlation of soils and housedust (p 0.003) indicative of a common source(s) for Pb in soil andhouse dust. In contrast, no such association is present for bulk Pbconcentrations, the most common approach employed in sourceinvestigations.

Several studies have been undertaken in France in recent yearssuch as the cross esectional national survey by Oulhote et al. (2011,2013). In the 2013 study, the authors compared Pb isotopic ratios in125 children whose PbB was >25 mg/dL with those in tap water,household and communal dust, soil and paint. Lead isotope ratiosrevealed a single suspected source of exposure for 32% of thesubjects and were able to eliminate at least one unlikely source ofexposure for 30% of the children.

4.4. Public health implications

In a review and ensuing media publicity Laidlaw and Taylor(2011) expressed the view that Australia was in the grip of a “Pbpoisoning epidemic”. (The use of the term “Pb poisoning” is inap-propriate and these days the term used is “elevated blood Pb” (e.g.,Canfield et al., 2003)). This conclusion was based on a very limitedand incomplete database mostly from cross-sectional studies thatwere undertaken about 20þ years ago. They appealed to the legacyof soil contamination from past gasoline use and resuspension ofdust and exposure of children from minimal data. Our study fromthe largest and most highly trafficked city in Australia showed thegeometric mean PbB in young children to be 2.1 mg/dL (or 2.7 mg/dL

for the maximum at age 0.5e2 years), less than half the recent USCenters for Disease Control and Prevention reference level of 5 mg/dL. Our study has shown that relationships between environmentalmeasures and PbB in children are not straightforward and that soiland dust sweepings contribute only about 1/5th of the amounts toPbB found in other studies such as in the US (Zahran et al., 2013b).

Our data can be compared with the latest figures available fromthe U.S. which show the geometric mean PbB levels in 1e5 year oldsfor 2009e2010 to be 1.17 mg/dL and for the period 2001e2004 to bew1.7 mg/dL (U.S. CDC 2013). Our study was completed in early 2006and if the decline in PbB is similar to that of NHANES, the currentPbB for young children in Sydney would be projected to be about1.5 mg/dL. We suggest that this PbB level is approaching that of a“background” value given the legacy of past gasoline use, industrialactivities in the city (e.g., smelters, brass works, coal-fired powerstations, printing, incineration) and widespread use of leaded paintespecially in older suburbs where the houses were built in the 19thcentury. The PbB value of 1.8 mg/dL for pre-schoolchildren fromFremantle in Western Australia from 2005 would support thisconcept. Although we were unable to employ a more rigoroussampling regime such as using census tracts to enlist volunteers,we consider the randomness in location of our cohort to be suffi-ciently representative of the Sydney metropolitan area. A furtherextrapolation could be that given the demography of Australiawhereby 75% of the population live in urban environments withmore than 100,000 people, our values provide an Australia-widesnapshot, but which should be followed up by further targetedPbB surveys.

We are not demeaning the toxic role of Pb especially in youngchildren where recent studies indicate adverse effects mostly on IQand adverse behaviour at levels below 5 mg/dL, even at levels of 1e2 mg/dL (Bellinger and Dietrich, 1994; Canfield et al., 2003; Juskoet al., 2008; Lanphear et al., 2005). There is, however, a majorconcernwith collection and analysis of blood samples at these verylow levels (Parsons et al., 2001), combined with the problem ofidentification and adjustment of confounding variables (US EPA2013), especially ones which are not measured such as certainchemical toxicants including extensive use of pesticides in resi-dences at the time of the major longitudinal studies (Gulson,2008b), widespread exposure of phthalates (Chopra et al., 2014)and nutritional deficiencies such as iodine (Trumpff et al., 2013). Aswe showed in this study for Pb in blood, an evaluation of the impactof the predictor variables on the blood results shows the percentageof the variance explained by the predictors to be low at 8% for Pb. Incontext, a child’s PbB measurement is estimated to account for 2%e4% of the variance in neurodevelopmental measures (w4%e8% ofthe explained variance) (Binns et al., 2007).

Lead poisoning is still a major issue in some countries whereunsafe practices are undertaken such as artisan gold mining andtreatment in Nigeria (Dooyema et al., 2011) and reprocessing of E-waste and batteries in China and other countries (Chen et al., 2010).However, calls for nationwide blood testing are perhaps, in theviews of the first author, a mis-direction of scarce funds and thereare ongoing monitoring programs in the major mining and smelt-ing communities of Port Pirie, Broken Hill and Mt Isa. In urbancentres where we are now seeing a generational change from theearly 1990’s in young families moving into inner-city suburbs andundertaking renovations, the limited available funds would bebetter directed towards resurrecting the early 1990’s campaignover leaded paint, still a major issue in older cities in Australia andinternationally. Such renovations and other paint surface distur-bances in housing containing Pb paints result in very high expo-sures to Pb dust and are a major focus of Pb exposure reductionactivities in the US through renovation, remodelling and painting(RRP) training programs (www2.epa.gov/lead/renovation-repair-

B. Gulson et al. / Environmental Pollution 191 (2014) 38e4948

and-painting-program, 2013). High concentrations of lead havebeen found in new household paints available in many countriesaround the world (Clark et al., 2009).

5. Conclusions

To our knowledge this is one of the most comprehensive studiesof young children and their environment especially in attemptingto delineate the sources and pathways of selected metals and theiruptake by the children. Because the primary purpose of our studywas to evaluate the impact of the introduction of MMT and cessa-tion of the use of tetra-alkyl Pb in gasoline in Sydney by studyinghouses at different distances from main traffic thoroughfares, weexpected to observe “traffic-related” parameters contributingsignificantly to the environmental media and blood but this wasonly the case for Pb in exterior dust sweepings.

The strongest predictor of PbB is dust-fall accumulation, asimple, non-invasive and inexpensive method using petri dishesinside and outside residences.

Previous and recent studies have drawn inferences for conti-nuity in pathways between soil-dust-blood Pb but potential inter-mediate pathways such as relationships between exterior dust,interior dust, exposures from other locations, handwipes and oftenblood data are missing. Our study indicates that the contribution ofsoil and exterior dust sweepings to PbB is very much lower thanobserved in other studies.

Disclaimer

The sponsoring organizations are not responsible for the viewsexpressed here.

Acknowledgements

Wewish to thank: the parents for allowing participation of theirchildren; Marilyn Morgan for phlebotomy; Becton Dickinson,AstraZeneca, and Johnson & Johnson for consumables for sampling;the NSW Roads and Traffic Authority for allowing access to theirtraffic data; the Australian Research Council, Commonwealth Sci-entific and Industrial Research Organisation, the National Mea-surements Institute, US EPA, and Macquarie University for partialfunding of the research.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.envpol.2014.04.009.

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