sex, tobacco exposure (assessed using serum cotinine), and blood lead concentrations. Any of these covariates showing univariate associa- tions (p < 0.2) with both DAP concentrations and birth outcomes were included in our mul- tivariable analyses. Only blood lead and serum cotinine concentrations fit these criteria. Our final model included maternal age (continu- ous), race/ethnicity (black or white), and mari- tal status (married or not married), household income (contiuous), parity (0, 1, or ≥ 2), and blood lead and serum cotinine concentra- tions (log10-transformed). We did not include gestational age in the primary birth weight analysis because of its potentially being on the causal pathway. However, for comparison with prior results in other cohorts, we con- structed gestational age-adjusted models in a sensitivity analysis. We assessed the form of the exposure– response relationship using locally weighted regression (LOESS) plots of log-transformed concentrations and outcomes. Because a straight line fit inside the 95% confidence bands, we concluded that it was appropriate to use a linear term to describe the relationship. Based on our preliminary analyses, we observed that the pattern for associations of DAP concentrations and birth outcomes varied by race/ethnicity. Because almost all mothers identified themselves as either black or white (the “other” group contained only 15 mothers), we restricted our analyses to black and white mothers. We then ran race- stratified models to obtain effect estimates, and formally assessed interactions in separate models using cross-product terms between race and urinary OP pesticide metabolite con- centrations, using p < 0.1 as the criteria for a statistically significant interaction. To examine gene–environment inter- actions between PON1 genotype and OP pes- ticides, we ran several PON-stratified analyses, stratifying by PON1192 or PON1–108. We also formally assessed interactions using dummy variables and interaction terms. Because race appeared to be an effect modifier and PON1 genotype can vary across racial groups, we also ran the PON1-stratified analyses separately for black and white mothers whenever possible given sample sizes. We also performed several sensitivity analyses. First, we examined whether moth- ers’ pregnancy medical conditions might confound the relationship between urinary DAP concentrations and birth outcomes. These included abruptio placenta, placenta previa, chorioamnionitis, preeclampsia, and pregnancy-induced hypertension. Next, we examined whether relationships between DAP concentrations and birth weight were evident for only term newborns (≥ 37 weeks) (Wilcox 2006). We considered child sex as an effect modifier and assessed interactions Organophosphate pesticides and perinatal outcomes with cross-product terms. Next, we assessed whether different methods of creatinine adjustment altered our results. We used DAP concentrations as our exposure variable with- out creatinine standardization or adjustment, and also ran a model with log10-transformed mean urinary creatinine concentrations as a covariate, as suggested by Barr et al. (2005). We also examined whether dilute urine sam- ples changed the pattern of our results by excluding women who had at least one sample with creatinine < 20 mg/dL. Finally, to assess the effects of different time periods of sample collection, we ran separate models using the DAP concentrations in samples taken at the 16-week and 26-week visits. Results Mothers participating in the study were pre- dominantly white, 25–35 years old, mar- ried, and primiparous (Table 1). Household income and education varied among the women, with the greatest proportion falling in the $55,000–$85,000 range, with either a high school diploma or bachelor’s degree. Relatively few infants were born preterm (n = 31, 9.0%) or were low birth weight (< 2,500 g, n = 20, 5.8%). All mothers had detectable levels of at least one DMAP metabolite, and at least one DEAP metabolite was detected in 92.7% of women. The ΣDAP metabolites median was 81.3 nmol/L (IQR = 42–220) (Table 1). Concentrations were higher at 16 weeks than at 26 weeks; however, creatinine-standardized DAP concentrations were similar at both time points. The two creatinine-standardized measurements were weakly correlated (r = 0.22). ΣDMAP metabolite concentra- tions (median = 56.9 nmol/L; IQR = 26–185) were considerably higher than those of ΣDEAP metabolites (median = 17.7 nmol/L; IQR = 8–37). The median blood lead concen- tration was 0.66 μg/dL (IQR = 0.51–0.87), and the median serum cotinine level was 0.027 ng/mL (IQR = 0.01–0.18). In the final models, we dropped one mother because of a missing creatinine value, 22 because of missing covariate values, and 15 in the “other race” cat- egory, giving us a final sample size of 306. PON1 genotype was also associated with maternal race/ethnicity in the study sample. Infants born to white mothers were more likely to have PON1192QQ (51.4% vs. 12.7%) and PON1–108CT genotypes (45.7% vs. 20.0%) than infants born to black mothers. Infants with black mothers were more likely to have PON1192RR (44.3% vs. 10.4%) and PON1–108CC (76.3% vs. 29.8%) genotypes (all chi-square p-values < 0.001). Table 1. Demographic characteristics of HOME study participants: Cincinnati, Ohio, 2003–2006 (n = 344).a Birth weight (g) Gestational age (weeks) (mean ± SD) (mean ± SD) 3,383 ± 622 39.0 ± 1.7 ΣDAPs (nmol/L) Median (25th–75th) 81.3 (41.7–220.0) 3,055 ± 619 3,508 ± 576 3,476 ± 573 3,392 ± 682 3,128 ± 539 3,516 ± 602 3,249 ± 648 3,121 ± 467 3,432 ± 658 3,515 ± 634 3,410 ± 561 3,130 ± 533 3,316 ± 581 3,532 ± 606 3,451 ± 652 3,477 ± 616 3,215 ± 563 3,342 ± 607 3,451 ± 587 3,369 ± 697 3,290 ± 572 3,487 ± 660 38.6 ± 2.2 39.3 ± 1.5 39.1 ± 1.6 38.7 ± 1.7 38.6 ± 1.8 39.2 ± 1.5 38.9 ± 2.3 38.9 ± 1.5 38.9 ± 1.7 39.1 ± 1.8 39.2 ± 1.7 38.8 ± 1.6 39.0 ± 1.7 39.2 ± 1.6 39.0 ± 1.8 39.1 ± 1.7 38.9 ± 1.7 39.3 ± 1.6 39.0 ± 1.5 38.4 ± 2.1 39.0 ± 1.7 39.0 ± 1.7 108.1 (55.0–244.2) 77.9 (41.7–220.0) 66.7 (39.3–169.8) 93.7 (46.9–232.2) 126.5 (44.8–319) 75.2 (41.3–192.3) 142.6 (73.4–231.6) 97.5 (41.7–254.2) 101.8 (39.7–245.7) 75.0 (36.5–169.8) 104.2 (52.5–213.7) 92.4 (41.4–216.5) 76.1 (36.2–192.7) 85.0 (44.1–243.6) 91.8 (47.6–219.7) 80.7 (43.6–219.6) 90.6 (40.4–239.9) 99.1 (46.3–234.1) 76.1 (41.9–192.7) 66.0 (32.6–192.3) 76.1 (39.2–207.4) 90.2 (46.3–232.2) All participants Age (years) Under 25 25–29.9 30–34.9 35 or Older Race/ethnicity Black White Other Household income < $22,500 $22,500–$45,000 $55,000–$85,000 > $85,000 Education Less than high school High school diploma Bachelor’s degree Graduate degree Marital status Married Not married Parity 0 1 ≥ 2 Child sex Female Male n (%) 344 (100) 72 (21.4) 96 (28.6) 111 (33.0) 57 (17.0) 97 (28.4) 229 (67.2) 15 (4.4) 64 (19.2) 86 (25.7) 117 (35.0) 67 (20.1) 32 (9.4) 129 (37.8) 102 (29.9) 78 (22.9) 233 (68.3) 108 (31.7) 155 (45.2) 109 (31.8) 79 (23.0) 181 (52.6) 163 (47.4) 25th and 75th are percentiles. aStudy population included women who provided spot urine samples at the 16-week and 26-week visits. Environmental Health Perspectives • volume 120 | number 7 | July 2012 1057