Prenatal and Postnatal PCB-153 and p , p ′-DDE Exposures and Behavior Scores at 5–9 Years of Age among Children in Greenland and Ukraine
2017; National Institute of Environmental Health Sciences; Volume: 125; Issue: 10 Linguagem: Inglês
10.1289/ehp553
ISSN1552-9924
AutoresA Rosenquist, Birgit Bjerre Høyer, Jordi Júlvez, Jordi Sunyer, Henning Sloth Pedersen, Virissa Lenters, Bo Jönsson, Jens Peter Bonde, Gunnar Toft,
Tópico(s)Smoking Behavior and Cessation
ResumoVol. 125, No. 10 ResearchOpen AccessPrenatal and Postnatal PCB-153 and p,p′-DDE Exposures and Behavior Scores at 5–9 Years of Age among Children in Greenland and Ukraine Aske Hess Rosenquist, Birgit Bjerre Høyer, Jordi Julvez, Jordi Sunyer, Henning Sloth Pedersen, Virissa Lenters, Bo A.G. Jönsson, Jens Peter Bonde, and Gunnar Toft Aske Hess Rosenquist Address correspondence to A.H. Rosenquist, Department of Clinical Epidemiology, Olof Palmes Allé 43-45, 8200 Aarhus N, Denmark; Telephone: 4560241490, Email: E-mail Address: [email protected] Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark , Birgit Bjerre Høyer Department of Occupational and Environmental Medicine, Copenhagen University Hospital, Copenhagen, Denmark Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark , Jordi Julvez ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain , Jordi Sunyer ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Catalonia, Spain , Henning Sloth Pedersen Primary Health Care Clinic, Nuuk, Greenland , Virissa Lenters Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands , Bo A.G. Jönsson Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden , Jens Peter Bonde Department of Occupational and Environmental Medicine, Copenhagen University Hospital, Copenhagen, Denmark , and Gunnar Toft Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark Published:3 October 2017CID: 107002https://doi.org/10.1289/EHP553Cited by:1AboutSectionsPDF Supplemental Materials ToolsDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinked InRedditEmail AbstractBackground:Studies have reported some evidence of adverse effects of organochlorine exposures on child development, but the results have been inconsistent, and few studies have evaluated associations with child behavior.Objective:We investigated the association between prenatal and early-life exposures to 2,2′,4,4′,5,5′-hexachlorobiphenyl (PCB-153) and 1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene (p,p′-DDE) and behaviors in children between 5 and 9 y of age.Methods:In the Biopersistent organochlorines in diet and human fertility: Epidemiologic studies of time to pregnancy and semen quality in Inuit and European populations (INUENDO) cohort, consisting of mother–child pairs from Greenland and Ukraine (n=1,018), maternal serum PCB-153 and p,p′-DDE concentrations were measured during pregnancy, and cumulative postnatal exposures during the first 12 months after delivery were estimated using a pharmacokinetic model. Parents completed the Strengths and Difficulties Questionnaire (SDQ), and children's behaviors were dichotomized as abnormal (high) versus normal/borderline for five SDQ subscales and the total difficulties score.Results:The total difficulties score, an overall measure of abnormal behavior, was not clearly associated with pre- or postnatal exposures to PCB-153 or to p,p′-DDE. However, pooled adjusted odds ratios (ORs) for high conduct problem scores with a doubling of exposure were 1.19 (95% CI: 0.99, 1.42) and 1.16 (95% CI: 0.96, 1.41) for pre- and postnatal PCB-153, respectively, and 1.25 (95% CI: 1.04, 1.51) and 1.24 (95% CI: 1.01, 1.51) for pre- and postnatal p,p′-DDE, respectively. Corresponding ORs for high hyperactivity scores were 1.24 (95% CI: 0.94, 1.62) and 1.08 (95% CI: 0.81, 1.45) for pre- and postnatal PCB-153, respectively, and 1.43 (95% CI: 1.06, 1.92) and 1.27 (95% CI: 0.93, 1.73) for pre- and postnatal p,p′-DDE, respectively.Conclusion:Prenatal and early postnatal exposures to p,p′-DDE and PCB-153 were associated with a higher prevalence of abnormal scores for conduct and hyperactivity at 5–9 y of age in our study population. These findings provide further support for the importance of minimizing organochlorine exposures to young children and to women of childbearing age. https://doi.org/10.1289/EHP553IntroductionPolychlorinated biphenyls (PCBs) have been widely used in, for example, hydraulic equipment, dyes, plasticizers, capacitors, transformers and flame retardants. Dichlorodiphenyltrichloroethane (DDT) has been used primarily as a pesticide and for vector control. Even though PCBs and DDT were banned from use in most Western countries in the 1970s and 1980s, DDT continues to be used for disease vector control in some developing countries (van den Berg 2009), and both are persistent and ubiquitous substances found in the environment (Ibarluzea et al. 2011).The main exposure routes of organochlorine compounds such as PCBs and DDT and its breakdown product dichlorodiphenyldichloroethylene (DDE) are through food consumption and breastfeeding, and given their lipophilic properties and long half-lives of 5 to 10 y, they bioaccumulate within human adipose tissue (Glynn et al. 2007; Malarvannan et al. 2013; Ribas-Fitó et al. 2005). These compounds may also cross the placental barrier, potentially resulting in fetal exposures decades after maternal exposure (Glynn et al. 2007; Vizcaino et al. 2014). Environmental pollutants such as pesticides, solvents, and organochlorines may act as developmental neurotoxins, inducing brain injury during early-life development at doses much lower than those required for adverse effects in adults, with potential long-term implications for the child (Grandjean and Landrigan 2006; Rosas and Eskenazi 2008).Based on concentrations measured in cord serum, prenatal exposures to PCBs and DDE were found to be associated with attention deficit hyperactivity disorder (ADHD)-related behaviors in 573 U.S. children at 8 y of age (Sagiv et al. 2010). Verner et al. (2015) used a pharmacokinetic model to estimate postnatal exposures in the same cohort and reported positive associations between postnatal PCB exposures and ADHD-related behaviors that were weaker than associations with prenatal exposures. PCB concentrations in maternal blood samples were also negatively associated with attention deficit disorders in 117 German children at 8–9 y of age (Neugebauer et al. 2015). However, other studies have not found associations between behavior outcomes and PCB or DDE exposures (Grandjean et al. 2012; Ribas-Fitó et al. 2007b; Strøm et al. 2014).In the present prospective cohort study, we investigated associations between prenatal and early-life exposures to organochlorine compounds, specifically 2,2′,4,4′,5,5′-hexachlorobiphenyl (PCB-153) and 1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene (p,p′-DDE), and abnormal behavior scores among children at 5–9 y of age.MethodsStudy PopulationThe study population consisted of mother–child pairs from the Biopersistent organochlorines in diet and human fertility: Epidemiologic studies of time to pregnancy and semen quality in Inuit and European populations (INUENDO) birth cohort. The target population was pregnant women attending antenatal care visits between May 2002 and February 2004 at three hospitals and eight antenatal clinics in Kharkiv, Ukraine, and at 19 local hospitals in municipalities and settlements in Greenland. Ukraine was chosen because of recent agricultural organochlorine pesticide use, and Greenland was chosen owing to a diet with a high bioaccumulation of organochlorines. Furthermore, women from Warsaw, Poland, were included in the cohort as a reference population, but given the low participation rate at follow-up (n=92), these women were not included in the main analyses of this study. Women were eligible for the study if they were pregnant (regardless of the week of gestation), ≥18y of age, and born in the country where they were being recruited. Neither paternal participation nor a successful delivery was required to be eligible for the cohort. At baseline, 1,238 women were enrolled, with a participation rate (out of all potentially eligible women in each respective subcohort, including women who declined to provide a blood sample) of 90% in Greenland and 26% in Ukraine. After providing informed consent, enrolled women were interviewed and had a venous blood sample drawn. Further details on the baseline study population are available elsewhere (Toft et al. 2005).A follow-up study was conducted between January 2010 and May 2012, when the children were 5–9 y of age (Høyer et al. 2015). Parents or guardians responded to retrospective questions concerning behavioral development and other characteristics in a face-to-face interview or by filling in a questionnaire themselves. Out of the women participating at baseline, the follow-up participation rate was 88% in Greenland and 77% in Ukraine. The decision to participate at both baseline and follow-up was made without personal knowledge of the exposure levels.Mother–child pairs that completed follow-up were included in the present analysis if the child was a singleton birth and the blood sample collected at enrollment was sufficient to measure the exposures of interest (n=1,018). The study population was evenly distributed between Greenland (52%) and Ukraine (48%).EthicsThe study was approved by local ethics committees: the Ethical Committee for Human Research in Greenland (approval no. 2010-13), and the Commission on Ethics and Bioethics Kharkiv National Medical University in Ukraine (protocol no. 7, 7 October 2009). The storage and use of data are registered at the Danish Data Protection Agency. All participants signed an informed consent prior to study enrollment at baseline as well as at follow-up.Prenatal ExposureThe median gestational week of baseline enrollment and blood sample collection (10th–90th percentile) was 25 (13–37) in Greenland and 23 (9–40) in Ukraine. Cubital vein blood samples were drawn into 10-mL vacuum tubes without additives (Becton Dickinson) for serum collection. Sera were stored at −20°C until shipment. After arrival at the Department of Occupational and Environmental Medicine in Lund, Sweden, sera were stored at −80°C until analysis within one year after sample collection.Maternal serum concentrations of PCB-153 and p,p′-DDE were analyzed using gas chromatography–mass spectrometry following solid-phase extraction. PCB-153 was chosen as a proxy for PCB exposure because it is strongly correlated with other PCB congeners and has a long half-life in humans (DeVoto et al. 1997; Muckle et al. 2001; Ritter et al. 2011). The levels of PCB-153 and p,p′-DDE were adjusted for lipids based on serum concentrations of cholesterol and triglycerides determined using enzymatic methods (Rylander et al. 2006).The limits of detection (LODs) were 0.05 ng/mL for PCB-153 and 0.1 ng/mL for p,p′-DDE. For PCB-153, 24 samples were below the LOD, and for p,p′-DDE, nine samples were below the LOD. When concentrations were below the LOD, they were set to half of the LOD based on fresh-weight concentrations and adjusted for lipids for all subsequent analyses. For each blood sample, analyses were performed twice on different days, and the mean concentration of the two was used. If the difference between the two samples was >30%, a third, and if necessary, a fourth, reanalysis was performed, and the concentration was calculated as a mean of two sample concentrations that met the criteria. However, at sample concentrations LOD analyzed in duplicate on different days for all samples included in the original study (Jönsson et al. 2005). The total sample in the INUENDO cohort was divided into three groups (n=990 in each group for PCB-153; n=1,058 in each group for p,p′-DDE). For PCB-153 (2,970 total samples), the relative standard deviations for samples in the lowest, middle, and highest thirds of the overall distribution were 18% (mean=0.1 ng/mL), 10% (mean=0.5 ng/mL), and 10% (mean=2 ng/mL), respectively. For p,p′-DDE (3,174 total samples), the corresponding relative standard deviations were 11% (mean=1 ng/mL), 8% (mean=3 ng/mL), and 7% (mean=8 ng/mL), respectively. For external quality control, the laboratory participates in an international round-robin intercomparison program. Further details on the analysis of the serum samples can be found elsewhere (Jönsson et al. 2005).Postnatal ExposureWe used a pharmacokinetic model developed by Verner et al. (2013) to estimate cumulative postnatal exposures to PCB-153 and p,p′-DDE over the first 12 months after delivery. A validation study of the pharmacokinetic model that compared predicted values to measured serum concentrations in samples collected at 6 months of age from children enrolled in Slovakian (n=216) and Canadian Inuit (n=150) birth cohorts reported R2 values of 0.59 and 0.81, respectively, for PCB-153, and 0.49 and 0.83, respectively, for p,p′-DDE (Verner et al. 2013). The model inputs used in the present study were maternal age at delivery; maternal prepregnancy weight; duration of exclusive breastfeeding; duration of partial breastfeeding; gestational age at birth; child's sex, birth weight, weight and age at one or more postnatal measurements, weight at the follow-up, and age at the follow-up; maternal serum levels of PCB-153 and p,p′-DDE during pregnancy; gestational age at blood sampling; and half-life of the compounds (Verner et al. 2013). Because duration of exclusive breastfeeding had the largest influence on the model estimates, only mother–child pairs with available breastfeeding data and measured maternal levels of PCB-153 and p,p′-DDE (n=977; 96%) were included in the postnatal modeling.We estimated the cumulative exposure of PCB-153 and p,p′-DDE during the first 12 months based on the area under the curve for the estimates at each individual month. The model has previously been used by Høyer et al. (2014) in the same birth cohort. The pharmacokinetic modeling was performed using acslX software (Aegis Technologies Group, Inc.).Outcome AssessmentWe assessed behavioral development using country-specific versions of the Strengths and Difficulties Questionnaire (SDQ) administered in the local language. The SDQ is a standardized screening tool comprising 25 questions, including both strengths and difficulties, on five different scales (emotional symptoms, conduct problems, hyperactivity, peer relationship problems, and prosocial behavior) (Goodman 1997). The SDQ can be applied internationally and has been thoroughly validated in the British population (Goodman et al. 2000; Goodman 2001). The questionnaire is used to assess the mental health of 2- to 17-y-old children. Three response options are available for each question ("not true," "somewhat true," or "certainly true," assigned values of 0, 1, or 2, respectively), and responses to the five questions for each subscale are summed to derive subscale scores from 0 through 10. A high score on the prosocial scale reflects strengths, whereas high scores on the other four scales indicate difficulties. In addition to individual subscales, scores for the emotional, conduct, hyperactivity, and peer problems scales may be summed to derive a "total difficulties" score ranging from 0 through 40 points. In a community sample of 9,998 British children 5–15 y of age, Cronbach's α for the parent-reported total difficulties SDQ score was 0.82, indicating high consistency (internal validity) among the individual SDQ questions (Goodman 2001).In the present study, parents completed the SDQ at follow-up when the children were between 5 and 9 y of age, reflecting their child's behavior during the preceding 6 months. We used the total difficulties score and the SDQ subscale according to guidelines published by the developer of the SDQ as outcomes (Goodman 1997, 2001). The SDQ scores were categorized into normal, borderline, and abnormal scores based on cut-off points (total difficulties score: normal 0–13, borderline 14–16, abnormal 17–40; emotional symptoms score: normal 0–3, borderline 4, abnormal 5–10; conduct problems score: normal 0–2, borderline 3, abnormal 4–10; hyperactivity score: normal 0–5, borderline 6, abnormal 7–10; peer problems score: normal 0–2, borderline 3, abnormal 4–10; prosocial behavior score: normal 6–10, borderline 5, abnormal 0–4) (Goodman 1997). We dichotomized the individual subscale and total difficulties scores as abnormal versus normal or borderline using the following cut-off points from published guidelines to define abnormal scores: total difficulties score ≥17, emotional symptoms score ≥5, conduct problems score ≥4, hyperactivity score ≥7, peer problems score ≥4, and prosocial behavior score ≤4 (Goodman 1997).Statistical AnalysesWe derived Spearman's correlation coefficients to assess correlations between prenatal and estimated postnatal PCB-153 and p,p′-DDE concentrations. We used separate logistic regression models to estimate associations between abnormal SDQ scores (for individual subscales and for the total difficulties score, dichotomized as indicated above) and each exposure (prenatal PCB-153, postnatal PCB-153, prenatal p,p′-DDE, and postnatal p,p′-DDE), and we performed additional sensitivity analyses using separate sets of mutually adjusted logistic regression models that included both prenatal PCB-153 and prenatal p,p′-DDE, or postnatal PCB-153 and postnatal p,p′-DDE. All exposures were modeled after log2 transformation such that odds ratios (ORs) represent the relative difference in the odds of an abnormal SDQ score associated with a doubling of exposure. The SDQ scores of the children were dichotomized into normal and borderline versus abnormal according to the approach described by Goodman et al. (Goodman 1997; Goodman et al. 2000). All analyses were performed separately for each subcohort and as pooled analyses for both countries combined. In addition, we report estimates from crude models (with pooled analyses adjusted for country) and from adjusted models. We performed complete-case analyses, such that observations with missing covariate data were excluded.We identified potential confounders a priori based on previous evidence of associations with behavioral outcomes in children, associations with early-life organochlorine exposures, or associations with both (Ellis et al. 2012; Fergusson and Woodward 1999; Pauly and Slotkin 2008; Zahn-Waxler et al. 2008). Because we performed complete-case analyses, we also considered the potential impact of missing data on our sample size and power when selecting covariates. Based on these considerations, we adjusted our primary models for maternal age at birth (continuous, years), maternal smoking during the index pregnancy (yes or no, based on serum cotinine >10 ng/mL or ≤10 ng/mL measured at enrollment in the INUENDO cohort), child's sex, child's age at follow-up (continuous, years), and, for pooled analyses, country. Our primary models of associations with postnatal PCB and p,p′-DDE exposures were additionally adjusted for breastfeeding duration (categorized as none, 12 months) because breastfeeding duration has been associated with better child behavior and with higher postnatal exposures (Mimouni-Bloch et al. 2013; Ribas-Fitó et al. 2007a). We also performed secondary models of prenatal exposures after additional adjustment for breastfeeding duration because breastfeeding might act as a causal intermediate between maternal blood levels during pregnancy and subsequent child behaviors by influencing postnatal exposure levels.We performed sensitivity analyses of the impact of adjusting for additional potential confounders that were not included in the primary model because of missing data. We used separate models to evaluate one additional potential confounder at a time, including parity (first vs. second or above), maternal educational level (left school at or before 15 y of age , left school at 16–17 y of age, left school at 18 y of age or older), gestational age at blood draw (continuous, weeks), and gestational age at birth (continuous, weeks) because the models could not accommodate all confounders at once without significant loss of power. In a sensitivity analysis, we used the top 10th percentile of the SDQ scores as the abnormal groups instead of the cut-off points given by Goodman (1997) because the questionnaires were validated in the British population and not in the Greenlandic or Ukrainian populations; this analysis was performed within each country specifically as well as in the pooled data. Furthermore, to assess the excluded participants from Poland, we performed a sensitivity analysis including Poland in the pooled analysis.All statistical analyses were performed using Stata software (version 14.1; StataCorp LLC). A p-value 10 ng/mL at the time of enrollment in the study cohort), and 11% reported that they consumed more than seven alcoholic drinks per week when they were trying to conceive; whereas in Ukraine, only 15% were classified as having smoked during pregnancy, and none reported consuming more than seven drinks per week. The women from Greenland were more often multiparous and were slightly older than the women from Ukraine. Further, the women from Greenland completed fewer years of school on average, and 45% breastfed their children for >12 months, compared with 22% in Ukraine. Among Greenlandic women, the median (10th–90th percentile) pregnancy serum concentration was 107 (30−369) ng/g lipids for PCB-153 and 229 (75−954) ng/g lipids for p,p′-DDE. Among Ukrainian women, the median (10th–90th percentile) pregnancy serum concentration was 27 (11−54) ng/g lipids for PCB-153 and 639 (329−1,303) ng/g lipids for p,p′-DDE. The same pattern of considerably higher levels of PCB-153 in Greenlandic women and p,p′-DDE in Ukrainian women was observed in the estimated postnatal exposures.Table 1 Characteristics of mothers and their children.Table 1 lists characteristics in the first column; the corresponding n values for Greenland (n equals 525), Ukraine (n equals 493), and pooled values (n equals 1018) are listed in the other columns.CharacteristicGreenland (n=525)Ukraine (n=493)Pooled (n=1,018)Exposure [median (10th–90th percentile)] Pregnancy serum PCB-153 (ng/g lipids)107 (30–369)27 (11–54)45 (15–253) Estimated postnatal PCB-153 (ng/g lipids)2647 (558–9,618)516 (104–1,419)1001 (173–6,368) Pregnancy serum p,p′-DDE (ng/g lipids)299 (75–954)639 (329–1,303)465 (124–1,158) Estimated postnatal p,p′-DDE (ng/g lipids)7075 (1,282–23,133)12,459 (2,914–34,724)9642 (1,836–28,807)Outcome [median score (number of children with abnormal scoresa)] Total difficulties (score 0 to 40)7 (30)8 (27)7 (57) Emotional problems (score 0 to 10)1 (44)1 (26)1 (70) Conduct problems (score 0 to 10)1 (58)1 (40)1 (98) Hyperactivity (score 0 to 10)2 (23)3 (24)3 (47) Peer problems (score 0 to 10)2 (113)2 (69)2 (182) Prosocial behavior (score 0 to 10)6 (65)6 (51)6 (116)Maternal characteristics Maternal age at delivery (y), median (10th–90th percentile)26 (20–36)24 (19–32)25 (20–35) Parity, n (%) 1st166 (33)402 (82)568 (57) 2nd or above335 (67)91 (18)426 (43) Smoking during pregnancy,bn (%) Yes (serum cotinine >10 ng/mL)295 (56)75 (15)370 (37) No (serum cotinine ≤10 ng/mL)230 (44)413 (84)643 (63) Alcohol consumption when trying to conceive, n (%) ≤7 drinks per week465 (89)493 (100)958 (94) >7 drinks per week60 (11)0 (0)60 (6) Educational level, left school at age (y), n (%) ≤1544 (10)25 (6)69 (8) 16–17169 (36)116 (27)285 (32) ≥18251 (54)293 (67)544 (60)Child characteristics Sex, n (%) Male284 (54)261 (53)545 (54) Female239 (46)229 (47)468 (46) Age at follow-up (y), median (10th–90th percentile)8 (7–9)7 (7–8)7 (7–9) Total breastfeeding duration (months), n (%) 018 (4)42 (9)60 (6) 12213 (45)108 (22)321 (33) Gestational age at blood sample (weeks), median (10th–90th percentile)25 (13–37)23 (9–40)24 (10–39) Gestational age at birth (weeks), n (%) ≥37 weeks498 (95)481 (98)979 (97) 10 ng/mL or ≤10 ng/mL measured at enrollment.The Spearman's correlation coefficient between PCB-153 and p,p′-DDE was 0.92 in Greenland and 0.46 in Ukraine for the prenatal exposures and 0.93 in Greenland and 0.76 in Ukraine for the postnatal exposures. In Greenland, the correlation between the prenatal and postnatal exposures was 0.81 for PCB-153 and 0.82 for p,p′-DDE. In Ukraine, the correlation between the prenatal and postnatal exposures was 0.56 for PCB-153 and 0.49 for p,p′-DDE.Crude odds ratios for associations between the exposures and outcomes are presented (see Table S1), and adjusted estimates (from the primary model) are presented in Table 2. In general, crude ORs were consistent with adjusted estimates with regard to the direction and patterns of associations.Table 2 Adjusted odds ratios (95% confidence intervals) for abnormala behavior scores associated with a doubling of prenatal and postnatal PCB-153 and p,p′-DDE.Table 2 lists outcomes in the first column; the corresponding number of cases, total number, and adjusted odds ratio for Greenland, Ukraine, and pooled values are listed in the other columns.OutcomeGreenlandUkrainePooledbn casesn totalAdjusted OR (95% CI)cn casesn totalAdjusted OR (95% CI)cn casesn totalAdjusted OR (95% CI)cPrenatal PCB-153 Total difficulties264521.02 (0.77, 1.36)254561.24 (0.77, 1.99)519081.09 (0.86, 1.38) Emotional374540.88 (0.70, 1.11)234561.16 (0.71, 1.90)609100.94 (0.76, 1.15) Conduct544541.18 (0.96, 1.46)374561.32 (0.89, 1.96)919101.19 (0.99, 1.42) Hyperactivity194521.35 (0.96, 1.89)224560.96 (0.60, 1.53)419081.24 (0.94, 1.62) Peer924531.04 (0.88, 1.22)664561.19 (0.88, 1.61)1589091.05 (0.92, 1.21) Prosocial514531.17 (0.94, 1.45)474560.83 (0.59, 1.16)989091.06 (0.89, 1.26)Postnatal PCB-153 Total difficulties194120.90 (0.65, 1.25)244491.30 (0.81, 2.10)438611.06 (0.82, 1.38) Emotional314140.87 (0.67, 1.12)224491.16 (0.70, 1.91)538630.94 (0.75, 1.17) Conduct464141.14 (0.91, 1.42)364491.24 (0.84, 1.83)828631.16 (0.96, 1.41) Hyperactivity154121.05 (0.72, 1.53)214491.03 (0.64, 1.66)368161.08 (0.81, 1.45) Peer814131.03 (0.86, 1.22)644491.51 (1.11, 2.04)1458621.12 (0.97, 1.30) Prosocial434131.16 (0.92, 1.45)464490.88 (0.64, 1.22)898621.06 (0.89, 1.28)Prenatal p,p′-DDE Total difficulties264521.09 (0.82, 1.45)254561.46 (0.87, 2.44)519081.15 (0.90, 1.48) Emotional374540.94 (0.76, 1.17)234561.24 (0.71, 2.15)609100.97 (0.79, 1.19) Conduct544541.24 (1.00, 1.54)374561.58 (1.02, 2.44)919101.25 (1.04, 1.51) Hyperactivity194521.36 (0.95, 1.94)224561.42 (0.84, 2.40)419081.43 (1.06, 1.92) Peer924531.11 (0.94, 1.30)664561.36 (0.96, 1.91)1589091.12 (0.97, 1.29) Prosocial514531.24 (1.00, 1.54)474560.99 (0.66, 1.47)989091.16 (0.97, 1.39)Postnatal p,p′-DDE Total difficulties194121.02 (0.74, 1.41)244491.51 (0.93, 2.45)438611.16 (0.88, 1.52) Emotional314140.97 (0.76, 1.23)224491.23 (0.73, 2.08)538631.00 (0.80, 1.25) Conduct464141.21 (0.96, 1.52)364491.42 (0.93, 2.18)828631.24 (1.01, 1.51) Hyperactivity154121.11 (0.76, 1.60)214491.50 (0.90, 2.52)368611.27 (0.93, 1.73) Peer814131.10 (0.93, 1.31)644491.79 (1.28, 2.50)1458621.20 (1.03, 1.40) Prosocial434131.28 (1.01, 1.61)464491.03 (0.70, 1.49)898621.20 (0.99, 1.45)Note: CI, confidence interval; DDE, dichlorodiphenyldichloroethylene; OR, odds ratio; PCB-153, 2,2′,4,4′,5,5′-hexachlorobiphenyl; p,p′-DDE, 1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene.aTotal difficulties score: abnormal ≥17; Emotional Symptoms Score: abnormal ≥5; Conduct Problems Score: abnormal ≥4; Hyperactivity Score: abnormal ≥7; Peer Problems Score: abnormal ≥4; Prosocial Behavior Score: abnormal ≤4.bOR for the pooled cohort is adjusted for country.cAdjusted for maternal age (continuous, years), maternal smoking during pregnancy (categorical, yes/no, based on serum cotinine >10 ng/mL or ≤10 ng/mL), child's sex (categorical, boy/girl), and child's age at follow-up (continuous, years). Estimated postnatal PCB-153 and p,p′-DDE are additionally adjusted for breastfeeding duration (categorical, >6 months, 6–12 months, or >12 months).Prenatal PCB-153 exposures were positively associated with abnormal conduct problem scores in both cohorts {adjusted OR for a doubling of exposure=1.18 [95% confidence interval (CI): 0.96, 1.46] based on 54 children with abnormal scores, hereafter referred to as "cases" for convenience, in Greenland; OR=1.32 (95% CI: 0.89, 1.96) based on 37 cases in Ukraine; pooled OR=1.19 (95% CI: 0.99, 1.42)} (Table 2). Associations differed between cohorts for total difficulties scores, with a null association in the Greenland cohort [OR=1.02 (95% CI: 0.77, 1.36); 26 cases] and nonsignificant positive associations in the Ukraine cohort [OR=1.24 (95% CI 0.77, 1.99); 25 cases] and in the pooled population [OR=1.09 (95% CI 0.86, 1.38)]. ORs also varied between the cohorts for prenatal PCB-153 exposure and abnormal hyperactivity scores, with a nonsignificant positive association in the Greenla
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