Yu-Han Chiu1, Paige L Williams2, Matthew W Gillman3, Russ Hauser4, Sheryl L Rifas-Shiman3, Andrea Bellavia5, Abby F Fleisch6, Emily Oken7, Jorge E Chavarro8. 1. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address: yuc187@mail.harvard.edu. 2. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. 3. Division of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA; Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA. 4. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Vincent Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA 02114, USA. 5. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. 6. Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland, ME 04101, USA; Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, ME 04101, USA. 7. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Division of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA; Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA. 8. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA. Electronic address: jchavarr@hsph.harvard.edu.
Abstract
OBJECTIVES: To examine the associations of maternal intake of fruits and vegetables (FVs), considering pesticide residue levels, with fetal growth. METHODS: We studied 1777 mothers (1275 white, 502 non-white) and their infants from Project Viva, a prospective pre-birth cohort (1999-2002). We categorized FVs as containing high or low pesticide residues using data from the US Department of Agriculture. We then used a food frequency questionnaire to estimate each participant's intake of high and low pesticide residue FVs in the first and second trimester. The primary outcomes were small-for-gestational-age (SGA; <10th percentile in birth-weight-for-gestational-age), large-for-gestational-age (LGA; ≥10th percentile in birth-weight-for-gestational-age) and preterm birth (gestational age <37 weeks). We also evaluated whether the associations between high pesticide residue FV intake and birth outcomes were modified by race/ethnicity. RESULTS: 5.5% of newborns were SGA, 13.7% were LGA, and 7.3% were preterm. Intakes of high or low pesticide residue FVs, regardless of pregnancy trimester, were not associated with risks of SGA, LGA, or preterm birth. In addition, the associations of high pesticide FV intake with SGA and LGA were not modified by race/ethnicity. However, we observed heterogeneity in the relationship between first trimester high pesticide FV intake and risk of preterm birth by race/ethnicity (P value for interaction = 0.01), although this relationship did not persist after correction for multiple comparisons (Bonferroni corrected level of significance: P < 2.8 × 10-3). CONCLUSIONS: There were no clear associations between high or low pesticide FV intake during pregnancy with SGA, LGA or preterm birth.
OBJECTIVES: To examine the associations of maternal intake of fruits and vegetables (FVs), considering pesticide residue levels, with fetal growth. METHODS: We studied 1777 mothers (1275 white, 502 non-white) and their infants from Project Viva, a prospective pre-birth cohort (1999-2002). We categorized FVs as containing high or low pesticide residues using data from the US Department of Agriculture. We then used a food frequency questionnaire to estimate each participant's intake of high and low pesticide residue FVs in the first and second trimester. The primary outcomes were small-for-gestational-age (SGA; <10th percentile in birth-weight-for-gestational-age), large-for-gestational-age (LGA; ≥10th percentile in birth-weight-for-gestational-age) and preterm birth (gestational age <37 weeks). We also evaluated whether the associations between high pesticide residue FV intake and birth outcomes were modified by race/ethnicity. RESULTS: 5.5% of newborns were SGA, 13.7% were LGA, and 7.3% were preterm. Intakes of high or low pesticide residue FVs, regardless of pregnancy trimester, were not associated with risks of SGA, LGA, or preterm birth. In addition, the associations of high pesticide FV intake with SGA and LGA were not modified by race/ethnicity. However, we observed heterogeneity in the relationship between first trimester high pesticide FV intake and risk of preterm birth by race/ethnicity (P value for interaction = 0.01), although this relationship did not persist after correction for multiple comparisons (Bonferroni corrected level of significance: P < 2.8 × 10-3). CONCLUSIONS: There were no clear associations between high or low pesticide FV intake during pregnancy with SGA, LGA or preterm birth.
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