obstetrical and medical history, and lifestyle factors. Women self-identified as white, white Hispanic, black, black Hispanic, or other. For the purpose of this analysis, white Hispanic and black Hispanics were jointly considered Hispanic. Maternal blood and urine samples were also obtained during a routine clinical visit, generally between 26 and 28 weeks of gestation. Delivery characteristics and birth outcomes, including birth weight, length, head circumference, gestational age and infant sex, were obtained from a computerized perinatal database within the Department of Obstetrics, Gynecology and Reproductive Science at Mount Sinai Hospital. The Bayley Scales of Infant Development, 2nd edition (BSID-II), was administered at the Mount Sinai Hospital at approximately 12 (n = 200) and 24 months (n = 276). The BSID-II provides age-standardized norms of mental [Mental Development Index (MDI)] and psychomotor [Psychomotor Development Index (PDI)] development. The MDI rates the child’s cognitive ability in a number of areas, including memory, habitua- tion, problem solving, early number concepts, generalization, classification, vocalizations, language, and social skills. The PDI rates the child’s fine and gross motor coordination. Scales are age standardized to a mean (± SD) of 100 ± 15 (Bayley 1993). Interviews and examinations were conducted in English or Spanish as required. Children were invited to return for Wechsler psychometric intelli- gence tests between the ages of 6 and 9 years. Children that returned before 7 years of age were administered the Wechsler Preschool and Primary Scale of Intelligence, 3rd edi- tion (WPPSI-III), which was administered in English or Spanish by one of four exam- iners. Block Design, Information, Matrix Reasoning, Vocabulary, Picture Concepts, Symbol Search, Word Reasoning, and Coding subtests were completed. Composite Verbal, Performance, Processing speed, and Full-Scale IQ (FSIQ) scores were derived using age-stan- dardized WPPSI-III norms. Children who returned between the ages of 7 and 9 years were administered the Wechsler Intelligence Scale for Children, 4th edition (WISC-IV) by one of four examiners. Children pro- vided witnessed assent before the start of the assessment. Block Design, Similarities, Digit Span, Picture Concepts, Coding, Vocabulary, Letter-Number Sequence, Matrix Reasoning, Comprehension, and Symbol Search subtests were completed. Composite Verbal, Perceptual Reasoning, Working Memory, Processing Speed, and FSIQ scores were derived using age-standardized WISC-IV norms. Both the WPPSI-III and the WISC-IV were admin- istered in a private room without the parent present. Mothers provided informed consent, and children ≥ 7 years of age provided verbal and witnessed assent. This study was approved by the Institutional Review Board of Mount Sinai School of Medicine. Maternal urine samples were analyzed by the Centers for Disease Control and Prevention (CDC) for six dialkylphosphate metabolites in two batches. Laboratory and quality control methods have been reported previously (Barr et al. 2005; Bravo et al. 2004; Wolff et al. 2005). In some cases, individual dialkylphosphate metabolite levels were miss- ing because of analytic interference. In these cases, missing dialkylphosphate metabolite lev- els were imputed using regression analysis to predict the missing metabolite on the basis of the other nonmissing metabolites measured for that woman within the group of correlated metabolites, as has been previously described (Engel et al. 2007). Samples below the lim–it of detection (LOD) were defined as LOD/√2. Diethyl- and dimethylphosphate metabo- lites were summed (as micromoles per liter) to obtain total diethylphosphate metabolites (ΣDEP) and total dimethylphosphate metabo- lites (ΣDMP), and total dialkylphosphate lev- els (ΣDAP). Very dilute samples of urine with < 20 gμ/dL creatinine ( n = 26) were excluded from organophosphate metabolite analyses, in accordance with methods that have previ- ously been applied for spot urine biomarker measures (Carrieri et al. 2001; Engel et al. 2007; Eskenazi et al. 2004; Wolff et al. 2007). Overall, approximately 97%, 89%, and 90% of the cohort had detectable levels of ΣDAP, ΣDEP, and ΣDMP metabolites, respectively (Engel et al. 2007). A random subset of maternal peripheral blood samples from the entire cohort (n = 194), distributed roughly equally by maternal race/ethnicity (66 blacks, 64 Hispanics, 64 whites, the number being dictated by budgetary considerations), was analyzed for polychlorinated biphenyls (PCBs) and 1,1´-dichloro-2,2´-bis(4-chlorophenyl) ethylene (DDE). PCBs were defined as the sum of congeners 118, 153, 138, and 180 (Wolff et al. 2005). Total lipids (grams per liter) were calculated by using cholesterol and triglycerides (Phillips et al. 1989) determined on the 174 plasma samples with sufficient vol- ume. Distributions of biomarker levels have been previously reported (Engel et al. 2007; Wolff et al. 2007). Plasma was separated from prenatal mater- nal peripheral blood and cord blood at deliv- ery and was used to measure PON1 activity by phenylacetate hydrolysis (Chen et al. 2005). Using maternal and child DNA, PON1 poly- morphisms were also measured using clamp- dependent and linking emulsion allele-specific polymerase chain reaction (Chen et al. 2005). We examined interactions between prenatal organophosphate exposure (dichotomized as above and below the median exposure) and tertiles of PON1 activity in maternal prenatal Environmental Health Perspectives • volume 119 | number 8 | August 2011 Prenatal pesticides and cognitive development peripheral blood and child cord blood. We also examined interactions between prenatal organophosphate exposure and the maternal or child PON1 Q192R, –108C > T, and L55M polymorphisms. We closely examined interac- tions if the type 3 F-test for the product-term in Proc GLM (either the class variable rep- resenting biomarker tertiles × dichotomized genotypes or race/ethnicity, or the linear term for log10 organophosphate metabolites × dichotomized genotypes or race/ethnicity) was p < 0.20. The PON1 Q192R polymor- phism in particular has been shown to have a strong functional consequence on the relative rate of hydrolysis of certain organophophate substrates (Li et al. 2000) and has been shown to affect the catalytic efficiency for chlorpyrifos but not diazinon (Richter et al. 2009). Data were analyzed using SAS (version 9.1; SAS Institute Inc., Cary, NC). Generalized linear models were used to analyze the rela- tionship between biomarker levels and MDI and PDI. In total, 200 children were adminis- tered the BSID-II at approximately 12 months of age (mean ± SD, 13.1 ± 1.6 months). Children were excluded from analyses if their refusal to do a large proportion of the items on the examination influenced their overall score (12-month MDI, n = 1). Two children were excluded from the 12-month analysis because their parent reported a diagnosis of pervasive developmental disorder. We also excluded observations when urine creatinine was < 20 gμ/dL in the maternal urine sample (n = 20). Of the remaining 177 eligible chil- dren who completed 12-month exams, 174 had organophosphate metabolites measured in prenatal urine. At the 24-month BSID-II (mean ± SD, 27.4 ± 4.5 months), 276 children completed the exam. Two were excluded from the 24-month analysis because the parent reported a diagnosis of pervasive developmental disor- der. Samples of urine < 20 μg/dL creatinine (n = 23) were also excluded. Of the remaining 251 eligible observations, 247 had organo- phosphate metabolites measured in prenatal urine. We could not compute the MDI scores for 10 additional children because their refus- als were too extensive to accurately calculate scores; however, they were included in the PDI analyses because their scores were valid. To maximize the sample size of our mod- els, we conducted analyses that combined the FSIQ, Perceptual Reasoning, Verbal Comprehension, and Processing Speed com- posite scores from children who came for at least one of the Wechsler psychometric intel- ligence exams—in the text and tables we refer to this as the “combined population” (n = 169). For these analyses, we preferentially selected the WISC-IV composite scores and substituted the WPPSI-III composite scores if the child did not return for the later exam. We 1183