Paper III
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International Journal of Hygiene and Environmental Health
j o ur na l h o me pa g e : w w w . e l s e v i e r . c o m / l o c a t e / i j h e h
The Northern Norway Mother-and-Child Contaminant Cohort (MISA) Study: PCA analyses of environmental contaminants in maternal sera and dietary intake in early pregnancy 夽
Anna Sofía Veyhe
a,∗, Dag Hofoss
a,b, Solrunn Hansen
a, Yngvar Thomassen
c, Torkjel M. Sandanger
a,d, Jon Øyvind Odland
a, Evert Nieboer
a,eaDepartmentofCommunityMedicine,FacultyofHealthScience,TheArcticUniversityofNorway,Norway
bInstituteofHealthandSociety,UniversityofOslo,Norway
cNationalInstituteofOccupationalHealth(NIOH),Oslo,Norway
dNorwegianInstituteforAirResearch(NILU),FramCentre,Tromsø,Norway
eDepartmentofBiochemistryandBiomedicalSciences,McMasterUniversity,Hamilton,Ontario,Canada
a r t i c l e i n f o
Articlehistory:
Received26August2014 Receivedinrevisedform 17November2014 Accepted1December2014
Keywords:
Pregnantwomen
PersistentOrganicPollutants(POPs) Toxicandessentialelements FoodFrequencyQuestionnaire(FFQ) PrincipalComponentAnalysis(PCA) TheNorthernNorwayMother-and-Child ContaminantCohortStudy(MISA)
a b s t r a c t
Background:Althoughpredictorsofcontaminantsinserumorwholebloodareusuallyexaminedbychem- icalgroups(e.g.,POPs,toxicand/oressentialelements;dietarysources),principalcomponentanalysis (PCA)permitsconsiderationofbothindividualsubstancesandcombinedvariables.
Objectives:Ourstudyhadtwoprimaryobjectives:(i)Characterizethesourcesandpredictorsofasuite ofeightPCBs,fourorganochlorine(OC)pesticides,fiveessentialandfivetoxicelementsinserumand/or wholebloodofpregnantwomenrecruitedaspartoftheMother-and-ChildContaminantCohortStudy conductedinNorthernNorway(TheMISAstudy);and(ii)determinetheinfluenceofpersonalandsocial characteristicsonbothdietaryandcontaminantfactors.
Methods:RecruitmentandsamplingstartedinMay2007andcontinuedforthenext31monthsuntil December2009.Blood/serumsampleswerecollectedduringthe2ndtrimester(mean:18.2weeks,range 9.0–36.0).Avalidatedquestionnairewasadministeredtoobtainpersonalinformation.Thesampleswere analysedbyestablishedlaboratoriesemployingverifiedmethodsandreferencestandards.PCAinvolved Varimaxrotation,andsignificantpredictors(p≤0.05)inlinearregressionmodelswereincludedinthe multivariablelinearregressionanalysis.
Results:Whenconsideringallthecontaminants,threeprominentPCAaxesstoodoutwithprominent loadingsof:allPOPs;arsenic,seleniumandmercury;andcadmiumandlead.Respectively,inthemulti- variatemodelsthefollowingwerepredictors:maternalage,parityandconsumptionoffreshwaterfish andland-basedwildanimals;marinefish;cigarettesmoking,dietaryPCAaxesreflectingconsumption ofgrainsandcereals,andfooditemsinvolvinghunting.PCAofonlythePOPsseparatedthemintotwo axesthat,intermsofrecentlypublishedfindings,couldbeunderstoodtoreflectlongitudinaltrendsand theirrelativecontributionstosummedPOPs.
Conclusions:ThelinearcombinationsofvariablesgeneratedbyPCAidentifiedprominentdietarysources ofOCgroupsandofprominenttoxicelementsandhighlightedtheimportanceofmaternalcharacteristics.
©2014ElsevierGmbH.Allrightsreserved.
夽TheNorwegiantitleoftheprojectis:Miljøgifterisvangerskapetogiammepe- rioden(MISA).
∗Correspondingauthorat:DepartmentofCommunityMedicine,UiT,TheArctic UniversityofNorway,Tromsø,Norway.Tel.:+298276631.
E-mailaddress:anna.sofi[email protected](A.S.Veyhe).
Introduction
Contaminantsoccurorarereleasedintonatureandwilleven- tuallyenterthefoodchainmakingthisaprimaryrouteforhuman exposure(AMAP,2009).Prominentenvironmentalpollutantsin thehumanbodyincludepersistentorganicpollutants(POPs)and toxicelementsandaredetectedinbiologicalsamplesinvarying quantities(AMAP,2009).Althoughpredictors of concentrations of contaminants in serum or wholeblood of pregnant women http://dx.doi.org/10.1016/j.ijheh.2014.12.001
1438-4639/©2014ElsevierGmbH.Allrightsreserved.
A.S.Veyheetal./InternationalJournalofHygieneandEnvironmentalHealth218(2015)254–264 255
areusuallystudiedbychemical groups (e.g.,POPs, toxicand/or essentialelements),principalcomponentanalysis(PCA)permits considerationofbothindividualandcombinedgroups.Thesame strategycanalsobeappliedtodietarysources.Thisapproachis pursuedinthecurrentpaperandinvolvesdietaryinformationand suitesofcontaminantsincluding:eightPCBs,fourOCpesticides, fiveessentialelements—copper(Cu),manganese(Mn),molybde- num(Mo),selenium(Se)andzinc (Zn)—andfivetoxicelements namelyarsenic(As),cadmium(Cd),cobalt(Co),mercury(Hg)and lead(Pb).
Most,butnotall,studiesinvestigatingdietaryintakeinrela- tiontoconcentrationsofenvironmentalcontaminantsinbiological specimenincludeenvironmentalcontaminantsassinglepredic- tors. Birgisdóttir et al. (2013) found that seafood intake was associatedwithaPCA-generatedfactorthatincludediodine(I),Se, AsandHg.Similarly,Kvalemetal.(2009)observedfourdistinct foodfactorslinkingintakeoffishliverandseagulleggstoblood concentrationsofdioxinsandPCBs.PCAwasusedbyOdlandetal.
(2001)togrouphumanplacentalconcentrationsof 11essential and5toxicelements.Factor1explained35.3%ofthetotalvari- ationandfeaturedhighloadingsofphosphorus(P),calcium(Ca), magnesium(Mg),barium(Ba),strontium(Sr),Pb,andnickel(Ni).
Themetalsinthisgroupallforminsolublephosphatesand,based onitsassociationswithsmokingandgestationalage,thisgroup- ingcouldbeinterpretedtoreflectplacentalmineralization.These examplesclearlyillustratethatPCAisapowerfulstatisticaltoolin biomonitoring.
Intakeoffishandmarinemammalsarewellknownpredictors ofthepresence ofPOPs inhumantissues(Kvalemet al.,2012;
Caspersenetal.,2013),asaresociodemographicvariableslikeage, parityand educationalachievement(Hansen etal.,2010).Inor- ganicHgisconvertedbymicroorganismstothemethylHg(Me –Hg)formthat accumulatesin theaquaticfoodchain (Moyer, 2012).Consequently, seafood consumption as well as living in coastalmunicipalitieshavebeenshowntobesignificantpredic- torsofbloodHgconcentrations(Jenssenetal.,2012).Nevertheless, Goldingetal.(2013)foundseafoodexplainedonly8.8%ofthetotal variationinbloodHgconcentrations.
ItiswellknownthatsmokingistheprimarysourceofCd,and lowiron(Fe)-storesareknowntobeinverselyrelatedtoCdblood concentrationsamongnon-smokingwomen(Charaniaetal.,2014;
Gallagheretal.,2011;Meltzer etal.,2010;Vahteretal.,2007).
Cdconcentrationsvaryinfoods,butfibre-richfoodslikecereals (especiallyrice),vegetablesandshellfishcontributetoCdintake (Vahteretal.,2007;Birgisdóttiretal.,2013).Bjermoetal.(2013) havedemonstratedmeatintaketobeinverselyrelatedtoblood Cdconcentrations.SmokingalsocontributestoincreasedbloodPb concentrations(Chelchowskaetal.,2013;Tayloretal.,2013),and itsuptakeisfoundtobeinverselyrelatedtoFe-stores(Mahaffey, 1990).ExposureofthegeneralpopulationtoPbhasbeenlinked tomultiplesourcesincluding:dietary(e.g.,consumptionoffoods grownoncontaminatedsoils,somewines,huntedgameandwater- fowlandtheassociateduseofleadedammunition);leadedpaints;
contaminatedsoilsandair;andcertainhobbiessuchasmakingPb sinkers(Nieboeretal.,2013;Meltzeretal.,2013;Hanningetal., 2003).Cereals(rice,grainsandthusflour)andcertainvegetables andlegumes(especiallycarrotsandpeas)aregoodsourcesofinor- ganicAs(iAs),whichconstitutesthetoxic formof thiselement (Schoofetal.,1999).Non-toxicorganicAsoccursinmeatandcere- alsandespeciallyinseafood,ranging160ng/ginfreshwaterfishto 2360ng/ginsaltwaterfish(Schoofetal.,1999).
ThedietconstitutestheprimarysourceofCoandNi(Shenkin andRoberts,2012;Moyer,2012;Barceloux,1999a,b).Ofthese,Niis themostcommonasitisanimportantcomponentofstainlesssteel (chromiumbeingtheother).Contactwithstainlesssteelappliances andresultingintakebyhand-to-mouthactivityseemsaplausible
Fig.1. MapoftheNorthernNorwaystudyarea.
sourceofNiespeciallyforchildren,anditcanalsobepresentin drinkingwaterwhentapsarenotflushedbeforedrinking(Niisa commoncomponentoffaucets).NeitherNinorCohaveessential functionsinhumans,althoughdiet-derivedvitaminB12contains Co.LowFestatusalsopromotestheuptakeofCo(Meltzeretal., 2010).
Zn,Cu,Mn,MoandSeareessentialelementsthatarerequired forgoodhealthandaretakeninthroughthediet.Znispresentin alltypesoffood,withhighproteinitemsrepresentingprominent sources(ShenkinandRoberts,2012;Barceloux,1999c).Bycontrast, meatsanddairyproductsarepoorinCu,whilemushrooms,dried fruits,legumes,whole-cerealgrainproducts,peanutbutter,nuts, organmeats(liver),andshellfish(crustaceans,oysters)haverela- tivelyhighcontents(ShenkinandRoberts,2012;Barceloux,1999d).
SourcesofMnalsoincludewholegrainfoods,nuts,leafyvegeta- bles,aswellassoyproductsandteas(ShenkinandRoberts,2012;
Barceloux,1999e).Cereals(rice,grains,especiallyflour)andcertain vegetables,legumes(especiallypeasandbeans)alsohavehighMo content(ShenkinandRoberts,2012;Barceloux,1999f).Andfinally, wheat,cerealproductsandespeciallyfisharegoodprovidersofSe (Brantsaeteretal.,2010).
Theaimsofthisstudywerefourfold:(i)characterizethesources and predictors of theAMAP’s suite of persistent organicpollu- tants,toxicandessentialelementsinserumand/orwholebloodof pregnantwomenrecruitedaspartoftheMother-and-ChildCon- taminantCohortStudyconductedinNorthernNorway(TheMISA study);(ii)comparetheexplanatoryimpactofusingsingleversus PCA-generateddietaryintakevariablesandofsinglecontaminant groups versuscombiningthem;and (iii),determinewhat influ- encepersonalandsocialcharacteristicshadonbothdietaryand contaminantfactors.
Materialandmethods
DescriptionofGeographicalareaandrecruitment
TherecruitmentandsamplingfortheMISAprojectstartedin May2007andcontinuedforthenext31months,untilDecember 2009. Pregnantwomen from thethree northern-most counties ofNorway,namelyFinnmark,TromsandNordland(Fig.1),were invitedtoparticipateinthestudywhenmakingtheirfirstultra- sound appointmentatantenatal centres.Allwomen receiveda
letter of invitation describing in layman’s terms thedetails of the study: its objectives; the physical, chemical and biological tests/examinationstobeconducted;projectfinances;andethical approvaldetails.Enrolmentwasconfirmedafterwrittenconsent wasreceived.Theobjectivewastoenrolthewomenbeforethey reachedgestationalweek20.Atotalof2600womenwereinvited toparticipate,609respondedofwhom52avoidedfurthercontact.
Theremaining557womenreceivedaprojectpackage,including aquestionnaireandabiologicalsamplingkit.Ofthese,15didnot donateblood and27didnothandinthewrittenconsentform, therebyfailingtheinclusioncriteria.Thisleft515eligiblestudy subjects.AdditionaldetailsareprovidedinVeyheetal.(2012).
Sampling
Fulldetailsofthespecimensamplingandotherprocedureswere providedpreviously(Veyheetal.,2012).Inshort,atinclusionpar- ticipantsdonatedbloodandurinesamples,theirbloodpressure wasmeasuredandbody weightassessed(wearing lightclothes andmeasuredtothenearestkg);andself-reportedheight(veri- fiedagainstthatinthemedicalrecord).Optimally,thisprocedure wasrepeatedthree days and 6weeks postpartum. Atdelivery, bloodpressureandbodyweightweremeasuredandamaternal hairsamplewasalsoobtained.
Questionnaire
Thefoodfrequencyquestionnaire(FFQ)wasdescribedearlier (Veyheet al.,2012).Briefly, thequestionnairewasdividedinto two parts. Part one pertained topersonal information, suchas lifetimeresidency (includingmunicipality), educationandwork histories,householdincome,ethnicaffiliationsandmaritalstatus.
Parttwoprovidedinformationabouttobaccoandalcoholuse,and foodconsumptiondetailsforthepastyear.TheFFQwasadapted fromNOWAC,theNorwegianWomenandCancerStudy(Hjartåker etal.,2007),althoughwithexpandeddetailsoffishintake,includ- inglifetimeseafoodintake(i.e.,childhood,youthandinadultlife).
Intakeoffishoilproducts,vitaminsandothersupplementswere alsoaskedfor.Thedietaryinformationwasconvertedfromamount andfrequencytodailyintakeingramsperdayusingastandardized measurementtable(Blaker’sNorwegianWeightandMeasurement Table;BlakerandAarsland,1995).Dailyenergyandnutrientintakes werecalculatedusingTheNorwegianFoodCompositionDatabase 2006(Matportalen,2014).
Bloodsamplecollection
Blood/serumsampleswerecollectedduringthe2ndtrimester (meanof18.2weeksandrange9.0–36.0).Thebloodwasdrawn fromtheantecubital veinintoBDVacutainers.Theserumsam- plestubes(SSTIIPlusAvance10/8.5ml)werecentrifugedat2000 RCFfor10min.Forthewholebloodtubesthedetailsare:Hemog- ardTM/Royal Blue, Ref# 368381, plastic, 6mL, with 10.8mgK2 EDTA (Becton Dickinson, Plymouth, UK). The vacutainers were transportedto theUniversityof Tromsø, where theserumwas transferredintoglassvialspre-rinsedwithn-hexane/acetoneand wholebloodto4.5mLcryo-vials.Sampleswerestoredat−20◦C untilanalysis.
Analyticalmethodology
Serumsamplepreparation
SerumsampleswereanalysedattheNorwegianInstitutefor AirResearch’s(NILU) laboratoryinTromsøNorway.Theextrac- tionandclean-upproceduresforthePOPshavebeendescribedby
Hansenetal.(2010).Briefly,serumsampleswereextractedinan OasisHLBsolidphaseextraction(SPE)column(540mgofsorbent;
WatersCorp.,Milford,MA,USA)andwerecleanedupusingFlorisil columns.
Lipiddetermination
As reported previously (Veyhe et al., 2013) lipids in serum weredeterminedenzymaticallyandtheamountineachsample wascalculatedusingthefollowingsummationformula:TL=1.677 (TC–FC)+FC+TG+PL,whereTL=totallipids,TC=totalcholesterol, FC=freecholesterol,TG=triglyceridesandPL=phospholipids.
AnalysisofseraandQA/QC
InstrumentaldetailsforthemeasurementsofPCBsandpesti- cidesareprovidedinHansenetal.(2010).Briefly,theextractswere analysedusinganAgilent7890Agaschromatograph(GC),equipped witha5975cmassspectrometer(AgilentTechnologies,Böblingen, Germany).TheGCwasfittedwitha30mDB5-MScolumn(0.25mm idand0.25mfilmthickness;J&W,Folsom,USA),withhelium(6.0 quality,Hydrogas,Porsgrunn,Norway)asthecarriergas.Twol ofthesampleextract wereinjectedinthesplitless modeusing a split/splitlessinjector(injectorand autosampler–Agilent7683 Series,AgilentTechnologies,Böblingen,Germany).Theselectedion monitoring(SIM)modewasusedforbothelectroncapturedisso- ciationandimpactionization.
The NILU Laboratory participatesin the internationalAMAP HumanHealthringtestforPersistentOrganicPollutants(POPs)in humanserumfromthisprogramme’soutsetandtodatehasper- formedwell(within±20%ofassignedvalues).Also,summedlipid concentrationsintestsamples(n=10)werewithina15%deviation fromassignedvalues.[AMAPringtestresultsareavailablefrom theLaboratoiredetoxicology,Institutnationaldesantépublique duQuébec(INSPQ,2014).]
AblankandaSRM(StandardReferenceMaterial®1958,Organic ContaminantsinFortifedHumanSerum;NationalInstituteofStan- dardsandTechnology,Gaithersburg,MD,USA)wereanalysedfor every10samplesmeasuredtoquantifylaboratory-derivedsample contaminationandtheaccuracyofthemethod.Internalstandard mixtures contained 29 different13C-labelledOCs. Thelimits of detection(LODs)werecalculated asthreetimestheareaofthe chromatogramnoiseortheaverageconcentrationsfoundinblank samples.Theaveragerecoveriesoftheinternalstandardsvaried between60%and97%.
Wholebloodsamplepreparation
Allanalyticalworkinvolvingwholebloodsampleswascarried outattheNationalInstituteofOccupationalHealth(NIOH),Oslo, Norway.To1.0mLofwholebloodinanacid-precleanedpolypropy- lenedigestiontube,1.5mLof65%ultrapurenitricacid(Chemscan Ltd.,Elverum,Norway)wasadded.Afterheatingina laboratory ovenat90◦Cfor1h,thedigestwascooledtoroomtemperature and200Lofaninternalstandardsolutionwasaddedcontain- ing72Ge for75Asand77,78,82Se;115In for98Moand114Cd; 205Tl for206,207,208Pband200,201,202Hg;60Nifor55Mn,59Co,63,65Cuand
64,66,68Zn;andwassubsequentlydilutedtoafinalvolumeof10mL withultrapurewater.FurtherdetailsareprovidedbyHansenetal.
(2011).
AnalysisofwholebloodandQA/QC
Detailsforthemeasurementsofselectedelementsareoutlined inHansenetal.(2011).Inbrief,maternalwholebloodwasanalysed
A.S.Veyheetal./InternationalJournalofHygieneandEnvironmentalHealth218(2015)254–264 257
forAs,Cd,Co,Cu,Hg,Mn,Mo,Pb,SeandZnbyinductivelyplasma- massspectrometry(ICPMS),employingahighresolutionmagnetic sectorfieldElement2massspectrometer(ThermoElectron,Bre- men,Germany) calibrated withwhole-blood matched standard solutions.Routineacidleachingofallvesselsanduseofultrapure waterandnitricacidassuredthattheblanksampleswereaslowas possibleinordertoobtainadequatelimitsofdetection(LOD)(three timesthestandarddeviationforblanksamples).Onealiquotofeach bloodsamplewasanalysedintriplicate.
SeronormhumanwholebloodTMTraceElements(SeroLtd., Billingstad,Norway)qualitycontrolmaterialsservedasreference materials.Afterevery10bloodsamples,acontrolsampleattwo differentconcentrationswasanalysed.
TheNIOHlaboratoryparticipatesintheWadsworthCenter,New YorkState(USA)DepartmentofHealthProficiencyTestingSched- ulesfortraceelementsinwholebloodandurine,withacceptable results(typicallywithin±2–10%deviationfromthetargetvalues) andnoindicationofanysystematicbiases.
Statisticalanalysis
The statisticalanalyses wereperformed usingthe IBM SPSS StatisticsforWindows(version21.0;SPSSInc.,Chicago,IL,USA).
AllconcentrationsbelowtheLODwerereplacedwithLOD/√2as recommendedbyEikAndaetal.(2007).Fordescriptivepurposes, meansandstandarddeviationsareprovidedforcontinuousvari- ablesaswellasthemedianandrange.Forcategoricalvariables, the%ineachcategoryisreported.Normalityofdistributionswas assessedbytheKolmogorov–Smirnovtest.Neitherthedietary variablesnorthecontaminantvariableswerenormallydistributed and toanalysedifferencesbetweengroups, thenon-parametric Mann–WhitneyTestwasused.TheANOVAand/orthePostHoc BonferroniTestwereemployedfor comparisonsinvolvingPCA- generatedvariables.ThecorrespondingP-valuesaredesignatedin thetextrespectivelyas:PMW,PAandPB.Statisticalsignificancewas setatP≤0.05.
Forvariabledimensionreduction,weusedPrincipalComponent Analysis(PCA)basedonEigenvalues>1andVarimaxrotationto produceasmallernumberofuncorrelatedvariableswhileretaining mostofthevarianceoftherawdata.Lipid-adjustedserumcon- centrationsofOCs,wholebloodconcentrationsofelements,and groupeddietaryintakevariablesweresubjectedtoPCAanalyses.
ForOCs,adetectionfrequencyof<70%constitutedtheinclusion criterion.Nosuchrestrictionwasrequiredfortheelements(see TableS4).
In the univariable linear regression analyses, links were exploredbetweencontaminantvariablesand:maternalage,edu- cational level and smoking habits in early pregnancy, parity, breastfeeding and pre-pregnancy BMI (pp-BMI), and between dietaryvariablesand:maternalage,educationallevel,smokingin earlypregnancy,andphysicalactivity(from1,indicatinglowactiv- ity,to10whichequalsveryhighactivitylevel)priortopregnancy wereexamined.Significantpredictors(p≤0.05)fromtheselinear regressionmodelswereincludedtogeneratemultivariablelinear regressionmodels.
Ethicalconsiderations
ThestudywasapprovedbytheRegionalCommitteesforMedical andHealth ResearchEthics (RECNorth),aswellasbytheNor- wegianDataInspectorate.Thewomenparticipatedonavoluntary basisand,asindicatedearlier,enrolmentrequiredreceivingwritten consent.
Results
Studygroupcharacteristics
Sociodemographicandpersonalcharacteristicsarepresentedin TableS1.Thewomenonaveragewere30.6yearsoldwitharange of25years(18–43years).Over40%hadhighereducation(>16 yearsofschooling,whichisequivalenttothelengthofabachelor (BA)educationwithamedianlengthof16years;60%hadayearly householdincomeoverNOK600,000;andthegreatmajoritywere marriedorcohabited(95.5%)andofNorwegianethnicaffiliation (89.9%).Nearly26%ofthewomenreportedsmoking6monthsprior topregnancy(notshown),whichdeclinedtoalmost18%inearly pregnancyandto6.6%bytermination.Only8%reportedtobetee- totallers,butalcoholintakeduringpregnancyappearstohavebeen modest:lessthan5%reportedanywineintakeduringpregnancy, and1.6%reportedhavingconsumedbeer.Themajority(64%)of thewomenhadpp-BMIvalueswithinthenormalrange(18.5– 24.9kg/m2),1.2%wereunderweight,24.3%overweightand10.4%
obese(>30.0kg/m2),withanaveragevalueof24.4(seeTableS1).
Themajority(55.3%)oftheparticipantslivedinthecountyof Troms, withtheremainder(see TableS1) divided betweenthe countiesofFinnmark(16.7%)andNordland(28%).Thewomenwere askedtorecordallmunicipalitiestheyhadlivedin.It wasthen decidedwhetherthemunicipalitywasontheoceanfront,inafjord orinland,andthatthelongestresidencetimedeterminedwhether arespondentwasrecordedas‘livingonthecoast’,‘bythefjord’
or‘inland’.Accordingly,nearly56%livedonthecoast,justunder 31%byfjordsand5%inland(notshown).Altogether91.7%reported habitationhistory.
About60%ofthewomenhadatleastonepreviousdelivery.
Incurrentdatasetofsingletonpregnancies,3.4%deliveredbefore gestationalweek37and9(1.8%)infantswerebornwithabirth weightbelow2500g(seeTableS1),ofwhomthreehadagesta- tionalage<37weeksand24(4.9%)werelargeforgestationalage (LGA)[ICD-10classificationP08.0;WHO,2010].Ninesetsoftwins wereincludedinthecohort;theyweredeliveredbetweengesta- tionalweek27–38(mean35.2weeks),withameanbirthweight of2257g(range:830–3070g).Thevastmajorityofmotherswith previousdeliveries(n=298)reportedeverbreastfeeding(n=228), 10onlybreastfeedingwithadditionalsupplements,andfournever breastfed.Breastfeedinginformationwasnotprovidedby70ofthe mothers.
Majorfindings Dietaryissues
Dailydietaryintakeintermsofenergyandmacro-andmicro- nutrientsispresentedinSupplementaryTableS2.Thedistribution ofthedailyenergyintakefrommajorfoodcomponentswas17%
(protein),46%(carbohydrates)and34%(fat).Intermsofdietary supplementsandfolicacid,47%and71%respectivelyreporteddaily intakeduringpregnancy.For fishoilproducts, 66%recordedan intakeonceaweekormoreduringthewinterseason.Thisfellto 52%inotherseasons(notshown).Sevensubjectsfailedtosubmit theFFQdespitereminders,and12wereincompleteandthuswere notincludedinthedietarycalculations.
ConcentrationsofOCsandelements
Concentrationsofwet-weightandlipid-adjustedPOPsinserum arepresentedinTable1,andlimitsofdetection(LODs)inSup- plementary Table S3. The highest averageconcentrations were foundforp,p-DDEand,relativetoit,indecliningorder:PCB153>
180>138>HCB>PCB170>187>118>163>trans-Nonachlor>PCB 156>99>183>cis-Nonachlor.Detectionfrequenciesforthepesti- cideswere≥96%andforeightofthe12PCBs≥81%.PCB101,156,
Table1
Wet-weightandlipid-adjustedconcentrations(pgg−1)ofPCBsandpesticidesinserumofpregnant(earlypregnancy)womenfromNorthernNorway.
Compounda Wet-weightlevels(pgg−1serum) Lipid-adjustedlevels(ngg−1lipids)
nb AMc SDd GMe Min–maxf AMc SDd GMe Min–maxf
PCB99 507 16.5 10.6 14.2 3.5–133 2.5 1.5 2.2 0.4–18.1
PCB118 508 31.1 20.6 26.5 7.1–228 4.8 3.2 4.1 1.0–38.3
PCB138 508 110 69.6 96.4 15.8–860 16.9 10.2 14.9 2.8–118
PCB163 501 26.2 17.2 22.3 5.7–181 4.0 2.5 3.4 0.7–24.6
PCB153 508 184 120 161 25.5–1470 28.2 17.4 24.8 5.3–201
PCB156g 499 17.3 12.2 15.0 LOD–192 2.7 1.8 2.3 LOD–26.3
PCB170 508 48.1 32.1 41.5 5.7–434 7.4 4.6 6.4 1.0–59.2
PCB180 508 123 84.3 107 16.8–1160 18.9 12.4 16.5 3.0–159
PCB183g 494 11.6 9.7 9.8 LOD–151 1.8 1.4 1.5 LOD–20.6
PCB187 502 32.5 20.7 28.0 3.8–216 5.0 3.0 4.3 0.8–29.5
p,p’-DDE 508 291 216 251 56.5–2440 44.9 32.9 38.7 10.9–351
HCB 507 67.6 31.6 62.2 21.2–317 10.3 4.4 9.6 3.5–53.3
trans-Nonachlor 508 21.8 15.0 17.9 3.6–129 3.3 2.2 2.8 0.6–17.6
cis-Nonachlor 507 5.2 4.0 4.0 0.4–33.3 0.8 0.6 0.6 0.1–4.5
aPCB(s),polychlorinatedbiphenyl(s);p,p-DDE,dichlorodiphenyldichloroethylene;HCB,hexachlorobenzene.Averagevaluesarepresentedonlyforcompoundswith detectionfrequencies≥70%(butseefootnote‘g’);alllevelsbelowtheLODweresettoLOD/√
2.
b Thenumberofparticipants(n)variedbecausetheobservedion-massratioswereunacceptable.
c AM=Arithmeticmean.
d SD=Standarddeviation.
eGM=Geometricmean.
f RangesaregivenasminimumtomaximumorLODtomaximum.
gDetectionfrequency:50–69%.
183and194wereomittedfromfurtheranalysisasthedetection frequencywas<70%(thecriterionforinclusion).
Table2summarizesconcentrationsforfiveessentialandfive toxicelementsinwholeblood.For7ofthe10elements(Cd,Pb,Cu, Mn,Mo,Se,andZn)the%detectedwas100%,andfortheothers (As,Co,andHg)itwas≥98.2%(seeSupplementaryTableS4).The elementsweremeasuredintworounds,withthefirstsetconsisting of211samplesasreportedbyHansenetal.(2011);thesecond batchof71wasmeasuredsubsequently.SincetheLODsforthe firstroundweremoreconservative(slightlyhighervalues)forall tenelements,thesewereadoptedforthepresentstudyandare reportedinSupplementaryTableS4.
Acomparisonofmeansbetweenthefirstandsecondrounds revealedsomedifferencesforCu(PMW<0.001),Mo(PMW<0.001) andZn(PMW=0.002).Buttheobservedrelativeconcentrationpat- terns remainedthe sameas presented earlier byHansen et al.
(2011):for thetoxic elementsthe highestconcentrations were againfoundforPb,followedbyAs>Hg>Cd(smoker)>Cd(non- smoker)>Co, with the relative concentrations of the essential elementsexhibitingthepatternZn>Cu≫SeMnMo.
PrincipalcomponentanalysesofPOPs,elementsanddietaryhabits InthePCAwithallcontaminants(POPsandelements),sixdis- tinctfactorsreflected74%ofthetotalvariance(Table3,Model1).
AllofthePOPsappearinthefirstPCvariable,anditexplains41.5%
ofthevariation.BasedontherelativelyhighloadingsofPOPs,itis designatedasthe‘POPsaxis’.Theelementsgroupontheremaining fivePCAfactors(PC-2–PC-6)andexplainedfrom9.3%to5.6%of thetotalvariation.Baseduponthesubstantiveloadingsindicated inboldtypeinModel1(Allcontaminants),PC-2canbedescribed asan‘arsenic/mercury/selenium’axis;PC-3a‘cobalt/manganese’
axis;PC-4a‘copper/molybdenum’axis;PC-5a‘zinc’axis;andPC-6 a‘cadmium/lead’axis.Sincetheelementalchemicalanalysiswas limitedto282samples,thePCAofPOPswasconductedseparately onallavailableresultstoincreasethestatisticalpower(N=498).
ThefindingsaresummarizedinTable3(Model2).Twoprimary factorswereevidentthatexplained83.3%oftotalvariation(Model 2,Table3).PC-1featuresp,p-DDEandallPCBsbutPCB118,while PC-2includesthepesticidesandPCB118.Whenconsideringthe elementsalone(Model3,Table3),thecorrespondingloadingsof PC-1–PC-5accountedfor68.7%ofthevariation,andresembled
Table2
Wholebloodconcentrationsoftoxicandessentialelementsinpregnantwomen(earlypregnancy)fromNorthernNorway.
Elementsa Concentrations(WtL−1) nb AMc SDd GMe Min–max
Toxic As g 282 2.09 2.08 1.46 0.14–12.8
Cd g 282 0.23 0.26 0.18 0.04–2.74
Co g 282 0.13 0.11 0.10 0.02–0.60
Hg g 282 1.51 1.02 1.21 0.10–6.64
Pb g 280 8.02 3.25 7.44 2.22–25.8
Essential Cu mg 282 1.64 0.26 1.62 1.00–2.87
Mn g 282 11.1 3.73 10.6 3.79–37.8
Mo g 282 0.74 0.26 0.70 0.24–2.28
Se g 281 85.8 13.6 84.7 58.17–128
Zn mg 282 5.27 0.84 5.20 2.73–9.85
aAs,arsenic;Cd,cadmium;Co,cobalt;Hg,mercury;Pb,lead;Cu,copper;Mn,manganese;Mo,molybdenum;Se,Selenium;Zn,zinc.
b Thevariationinnumberofparticipantsisduetotheexclusionofextremevalues.
c AM=Arithmeticmean.
d SD=Standarddeviation.
eGM=Geometricmean.
A.S.Veyheetal./InternationalJournalofHygieneandEnvironmentalHealth218(2015)254–264259 Table3
PrincipalComponentAnalysis(PCA)scoresofPOPs(lipidadjusted)andelementspresentedinthreemodels;allcontaminants(Model1),POPsonly(Model2)andelementsonly(Model3)inmaternalserum(meangestational ageof18.2weeks)a,b.
Allcontaminantsc Model1(Allcontaminants)n=266 Model2(POPsonly)dn=498 Model3(Elementsonly)n=279
PC-1(41.5%) PC-2(9.3%) PC-3(6.2%) PC-4(6.0%) PC-5(5.7%) PC-6(5.6%) PC-1(50.4%) PC-2(32.9%) PC-1(19.1%) PC-2(13.5%) PC-3(12.4%) PC-4(12.1%) PC-5(11.6%)
PCB99 0.892 0.128 −0.019 0.098 0.048 −0.026 0.692 0.573
PCB118 0.861 0.093 −0.045 0.113 0.062 −0.004 0.552 0.666
PCB138 0.962 0.080 0.001 −0.052 0.029 −0.045 0.825 0.480
PCB163 0.894 0.120 −0.032 0.024 −0.070 −0.002 0.768 0.452
PCB153 0.975 0.090 −0.005 −0.089 0.000 −0.034 0.875 0.448
PCB170 0.879 0.007 0.022 −0.176 −0.097 0.032 0.890 0.297
PCB180 0.915 0.072 0.034 −0.185 −0.041 −0.024 0.897 0.331
PCB187 0.949 0.076 0.042 −0.087 −0.014 −0.011 0.862 0.435
p,p’-DDE 0.700 0.046 0.101 −0.014 0.087 −0.212 0.706 0.222
HCB 0.813 0.047 −0.117 0.060 0.039 0.030 0.464 0.682
trans-NCe 0.767 0.288 −0.077 0.321 −0.048 −0.017 0.337 0.889
cis-NCe 0.719 0.324 −0.106 0.371 −0.041 0.006 0.251 0.920
As 0.042 0.838 0.007 −0.038 −0.099 0.066 0.799 0.054 0.017 −0.137 −0.014
Cd −0.105 −0.032 0.177 0.008 −0.106 0.778 −0.087 0.180 0.795 −0.171 −0.054
Co −0.080 0.159 0.802 −0.049 −0.141 0.138 0.111 0.813 0.133 −0.113 −0.046
Cu −0.036 −0.118 0.089 0.761 0.025 −0.196 −0.107 0.108 −0.227 0.031 0.742
Pb 0.036 0.022 0.003 0.029 0.482 0.662 0.057 −0.016 0.695 0.422 0.059
Mn 0.039 −0.077 0.795 0.135 0.257 0.047 −0.035 0.792 0.020 0.236 0.115
Hg 0.240 0.787 0.055 −0.025 0.028 0.001 0.836 0.029 0.017 −0.012 −0.026
Mo −0.005 0.033 −0.003 0.596 −0.130 0.215 0.076 −0.043 0.207 −0.119 0.759
Se 0.227 0.649 0.048 −0.004 0.413 −0.173 0.728 −0.005 −0.101 0.376 0.014
Zn −0.075 0.039 0.065 −0.122 0.829 0.040 0.019 0.091 0.036 0.868 −0.096
aThePCAisbasedonEigenvalues>1andVarimaxrotation.
b Highlightedscores(alsocalledloadings)indicatethatthevarianceinthecorrespondingelementitemscontributesubstantiallytothevariancesummarizedbythatprincipalcomponent(PC).
c Seefootnote‘a’ofTables1and2forfullnames.
d WhenthePCAanalysiswasbasedonwet-weightcontaminantlevels,onlyonefactordescribing76%ofthevariationresulted.
eNC,Nonachlor.
Table4
PCAscoresof20foodgroupsderivedfromFFQrecordedinearlypregnancy(meangestationalageof18.2weeks;n=496)representinglast12month’sintakea,b. Foodgroups PC-1(9.4%) PC-2(8.0%) PC-3(7.9%) PC-4(7.8%) PC-5(7.4%) PC-6(6.6%) PC-7(5.8%) PC-8(5.1%)
Fruit 0.650 0.251 −0.018 0.121 −0.160 −0.166 −0.153 −0.205
Berries 0.617 −0.035 0.344 −0.057 0.148 −0.018 −0.069 −0.179
Soup 0.579 −0.007 0.032 −0.004 0.029 0.046 0.149 0.133
Coffeeandtea 0.554 −0.044 −0.251 0.141 0.199 0.054 0.194 0.221
Vegetables 0.523 0.439 −0.149 0.096 −0.145 0.296 −0.104 −0.003
Marineleanfishandshellfish −0.004 0.769 −0.035 0.074 −0.083 0.166 0.062 −0.056
Marinefattyfish 0.127 0.736 0.001 0.014 0.162 −0.002 0.007 0.183
Saltysnacksandchocolate 0.057 0.087 0.682 0.104 −0.128 0.051 −0.070 0.229
Dessert 0.262 0.015 0.642 0.132 0.120 0.083 0.126 −0.128
Softdrinksandjam −0.187 −0.143 0.611 −0.110 0.010 0.035 0.013 0.048
Grainsandcereals 0.295 −0.007 0.067 0.713 0.082 0.123 −0.077 0.071
Fatonbreadandwithfish,mayonnaise −0.096 0.038 0.051 0.682 0.141 0.009 −0.134 0.090
Milkandmilkproducts,andriceporridge −0.043 −0.006 0.014 0.538 −0.243 −0.207 0.409 −0.195
Pasta,potatoesandrice 0.055 0.139 −0.016 0.462 −0.028 0.263 0.122 0.054
Freshwaterfish 0.017 0.115 −0.037 0.014 0.785 −0.040 0.003 0.024
Reindeer,reindeerproducts,mooseandgrouse 0.058 −0.043 0.038 0.083 0.779 0.127 0.013 −0.064
Sauce 0.068 0.095 0.017 0.061 0.082 0.842 0.072 −0.052
Meatandmeatproducts −0.090 0.067 0.418 0.203 0.026 0.588 −0.048 0.015
Whaleandseal 0.111 0.005 −0.009 −0.080 −0.027 0.125 0.790 0.131
Fishliver -0.063 0.452 0.087 0.079 0.238 −0.119 0.500 −0.118
Seagulleggs 0.015 0.072 0.122 0.117 −0.044 −0.047 0.058 0.854
aThePCAisbasedonEigenvalues>1andVarimaxrotation.
b Highlightedscores(alsocalled)loadingsindicatethatthevarianceinthecorrespondingelementitemscontributesubstantiallytothevariancesummarisedbythe principalcomponent(PC).
axesPC-2–PC-6ofModel1(butnotetheshiftinsequenceofthe axes).
Toreduce the number dietary variables, summary variables combiningseveralrelatedfoodfrequencyvariables weregener- atedforuseinthePCA(seeTable4).Theeightprimaryaxesshown explained58%ofthevariation,withindividualaxescontributing from9.4%to5.1%ofthetotalvariance.Toreflecttheirloadings, thefollowingshort-handlabelswereadoptedfortheeightaxes:
PC-1(‘fruit&vegetables’);PC-2(‘marinefish’);PC-3(‘junkfood’);
PC-4(‘grains&dairy’);PC-5(‘localtraditionalfood’);PC-6(‘sauce
&meat’);PC-7(‘whale/seal&fishliver’);andPC-8(‘seagulleggs’).
Relationshipsbetweenfoodconsumptionandpersonal characteristics(posthoctests)
Overallmaternalageandeducationassociatedpositivelywith theindividualdietaryfactorscoresPC-1(‘fruit&vegetables’),while forPC-3(‘junkfood)’anegativetrendwasevident(PA≤0.05).Edu- cation(yearsatschoolgroupedbyage:<13years,13–16years,and
>16years)showedincreasingtrendsforPC-1(Diet)(PA=0.03)and PC-4(Diet)(PA=0.08);itwasnegativeforPC-3(Diet)(PA=0.004).
For smoking a negative trend was observed for PC-1(‘fruit
& vegetables’), while it was positive for PC-3(‘junk food’), PC- 7(‘whale/seal&fishliver’)andPC-8(‘seagulleggs’)(PA≤0.05).No consistentpatternswereobservedforassociationswithphysical activityandpp-BMI,exceptforanegativetrendforPC-1(‘fruit&
vegetables’)withpp-BMI(PA=0.03).
Intakeofgameandfreshwaterfishwassignificantly(PB<0.001) higheramong womenliving inland(intakes ing/dayof 22 and 3g/dayof game and freshwaterfish, respectively),than among thoselivingbythecoast(2.4g/dayand0.5g/day,respectively)orby fjords(3and1g/day,respectively).Forotherfoodgroupslikemeat, fruit,vegetablesormilkproductsnodistinctpatternbetweenthe geographicalareaswasfound.
Women living inland had significantly higher factor scores for PC-1(All contaminants) than those residing on the coast (PB=0.001)orbyfjords(PB=0.03).Comparabletrendswerefound forPC-1(POPsonly),PC-2(POPsonly)andPC-6(Allcontaminants) (respectively,withPA values of 0.04, 0.02 and0.05); these dif- ferences did not reach significance for PC-2(All contaminants) (PA=0.13).
SincemostofthedietaryPC-factorshavesomedependenceon maternalage,andthelatterisarecognizedpredictorofplasma POPs,theirrelationshipstocontaminantPC-factorsaredealtwith inthemultivariableregressionmodellingsection.
Predictorsofcontaminantconcentrationsinserum
In the multivariable linear regression models (see Table 5) forPC-1(Allcontaminants),37.6%ofthevariancewasexplained bymaternalage,parity,freshwaterfishandgameintake.When fish liverwas includedinto themodel R2 increasedsomewhat (38.4%), althoughthepredictor variableitself wasonly roughly significant (p=0.08). Maternal age, parity, pp-BMI and PC- 2(‘marine fish’) explained almost 20% of total variation of PC-1(POPsonly).ReplacementofPC-2(‘marinefish’)inthismodel withthePC-8(‘seagullaxis’)slightlyimprovedtheoverallfit(R2 increasedfrom19%to20%).PC-2(POPsonly)wasbestexplained bymaternalageandbreastfeedingalongwithdietaryPCvariables (R2=26.2%).PC-2(Allcontaminants) exhibitedthebestfit when thePCaxesrepresentingfruit&vegetables(PC-1)andseafoodaxes (PC-2andPC-7)wereincludedinthemodel(R2=24.2%).Basedon ˇandR2values(seeTable5),theassociationofcurrentsmoking (contemporarywithbloodcollection) wasmorerobustlyassoci- atedwithPC-6(Allcontaminants)comparedtotheconsumption of grainsand oftraditional foods. Up to 42.6% ofthe variation wasaccounted for.No foodvariables or personal characteristic explainedfactorsPC-3toPC-5(Allcontaminants).
Discussion
Overviewofmultivariablelinearregressionmodels
Maternal age was a recurring positive explanatory variable in the multivariable linear regression models involving PC- contaminantaxes(in7ofthe12models)andintwoofthreedietary models;seeTable5.Forthesamesevenmodels,parity(substi- tutedinonecasebybreastfeeding)constitutedanegativepredictor.
Thesetrendswerealsoevidentinourpreliminaryreportofthe incompleteMISAcohort(Hansenetal.,2010).Theimportanceof thesethreepredictorsofOCsinmaternalseraarewellestablished, Incross-sectionalstudies,ageisapositivepredictor(Liberdaetal.,
A.S.Veyheetal./InternationalJournalofHygieneandEnvironmentalHealth218(2015)254–264 261
Table5
Multivariablelinearregressionmodels:SignificantpredictorsforselectedfactorsfromTable3Model1andModel2(Contaminantfactors)andfromTable4(Dietaryfactors).
Predictorsa B 95%CI p-Value ˇ R2
PC-1(Allcontaminants) 1
n=258
Maternalage 0.11 0.09;0.13 <0.001 0.52 0.376
Parity −0.40 −0.51;−0.29 <0.001 −0.38
Freshwaterfishb 0.07 0.02;0.12 0.004 0.17
Reindeer,innards,mooseandgrouseb 0.02 0.006;0.03 0.004 0.17
2 n=258
Maternalage 0.10 0.08;0.13 <0.001 0.50 0.384
Parity −0.40 −0.51;−0.29 <0.001 −0.38
Freshwaterfishb 0.07 0.02;0.12 0.005 0.17
Reindeer,innards,mooseandgrouseb 0.02 0.005;0.03 0.005 0.16
Fish-livera 0.28 -0.04;0.60 0.08 0.09
PC-1(POPsonly) 1
n=466
Maternalage 0.09 0.07;0.11 <0.001 0.42 0.189
Parity −0.26 −0.35;−0.14 <0.001 −0.24
pp-BMIc −0.05 −0.06;−0.03 <0.001 −0.21
PC-2(‘marinefish’) −0.11 −0.19;−0.03 0.009 −0.11
2 n=466
Maternalage 0.08 0.06;0.10 <0.001 0.40 0.197
Parity −0.25 −0.35;−0.16 <0.001 −0.23
pp-BMIc −0.05 −0.06;−0.03 <0.001 −0.21
PC-8(‘seagulleggs’) 0.14 0.06;0.22 0.001 0.14
3 n=475
Maternalage 0.08 0.07;0.10 <0.001 0.41 0.181
Parity −0.26 −0.35;−0.16 <0.001 −0.24
pp-BMIc −0.04 −0.06;−0.03 <0.001 −0.20
PC-2(POPsonly) 1
n=418
Maternalage 0.05 0.03;0.07 <0.001 0.25 0.262
Breastfeedingd −0.60 −0.79;−0.41 <0.001 −0.29
PC-2(‘marinefish’) 0.26 0.17;0.35 <0.001 0.25
PC-5(‘localtraditionalfood’) 0.24 0.15;0.32 <0.001 0.24
PC-7(‘whale/seal&fishliver’) 0.18 0.10;0.27 <0.001 0.18
2 n=483
Maternalage 0.04 0.02;0.06 <0.001 0.21 0.177
Parity −0.22 −0.32;−0.12 <0.001 −0.20
Freshwaterfishb 0.06 0.03;0.09 <0.001 0.16
Marinefattyfishb 0.02 0.01;0.03 <0.001 0.19
Shellfishb 0.09 0.02;0.16 0.01 0.11
PC-2(Allcontaminants) 1
n=258
Marineleanfishandshellfishb 0.01 0.005;0.02 <0.001 0.22 0.196
Marinefattyfishb 0.02 0.01;0.04 <0.001 0.24
Whaleandsealb 0.22 0.09;0.35 0.001 0.19
2 n=258
Marineleanfishandshellfishb 0.008 0.001;0.01 0.02 0.15 0.227
Marinefattyfishb 0.02 0.009;0.03 0.001 0.21
Whaleandsealb 0.23 0.10;0.36 0.001 0.19
Vegetablesb 0.002 0.001;0.003 0.002 0.19
3 n=258
PC-1(‘fruit&vegetables’) 0.20 0.09;0.32 0.001 0.19 0.242
PC-2(‘marinefish’) 0.37 0.27;0.47 <0.001 0.38
PC-7(‘whale/seal&fishliver’) 0.24 0.14;0.34 <0.001 0.25
PC-6(Allcontaminants) 1
n=250
Yearsatschool −0.04 −0.07;0.000 0.05 −0.10 0.426
PC-4(‘grains&dairy’) 0.18 0.09;0.28 <0.001 0.19
PC-5(‘localtraditionalfood’) 0.12 0.03;0.21 0.006 0.13
Presentsmokinge(Yes/No) 2.57 2.13;3.00 <0.001 0.58
2 n=253
Reindeer,innards,mooseandgrouseb 0.01 0.001;0.02 0.03 0.11 0.388
Grainsandcerealsb 0.001 0.000;0.003 0.01 0.13
Presentsmokinge(Yes/No) 2.60 2.18;3.02 <0.001 0.61
PC-1Diet(Fruit&vegetables)
n=469 Maternalage 0.02 −0.001;0.04 0.06 0.09 0.07
Yearsatschool 0.03 0.003;0.06 0.03 0.10
pp-BMIc −0.02 −0.04;−0.001 0.04 −0.10
Physicalactivitybeforepregnancyf 0.09 0.04;0.14 <0.001 0.16
PC-2Diet(Marinefish)
n=492 Maternalage 0.03 0.02;0.05 <0.001 0.17 0.04
Physicalactivitybeforepregnancyf 0.07 0.02;0.13 0.005 0.13
PC-3Diet(Junkfood)g
n=471 Maternalage −0.03 −0.05;−0.01 0.002 −0.15 0.06
Yearsatschool −0.04 −0.08;−0.009 0.01 −0.12
pp-BMIc 0.02 −0.002;0.04 0.08 0.08
aForasummaryofeligiblepersonalinformationanddietarypredictors,seeTableS5(i.e.,thosewithsignificantp-valuesinthelinearregressionanalyses).
bDietaryintakeing/day.
c BMI:Basedonself-reportedpre-pregnancyweightandheight(pp-BMI).
d Breastfeeding(Yes/No).
ePresentsmoking(whenfillinginFFQ:meangestationalage18.2weeks(Yes/No)).
f Scalefrom1to10.
gAnalysesinvolvingthedietaryaxesPC-4andPC-8showednoassociations,andwaslimitedtoonevariableforPC-5(Yearsatschool,p=0.04),PC-6(Yearsatschool, p=0.05)andPC-7(pp-BMI,p=0.001).
