Suena H Massey1, Norrina B Allen2, Lindsay R Pool3, Emily S Miller4, Nicole R Pouppirt5, Deanna M Barch6, Joan Luby7, Susan B Perlman8, Cynthia E Rogers9, Chris D Smyser10, Lauren S Wakschlag11. 1. Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, 676 North Saint Clair Street, Suite 1000, Chicago, IL 60611, USA; Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, 625 N Michigan Avenue, Suite 2100, Chicago, IL 60611, USA; Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19(th) floor, Chicago, IL 60611, USA. Electronic address: suena.massey@northwestern.edu. 2. Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19(th) floor, Chicago, IL 60611, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 North Lakeshore Drive, Suite 1400, Chicago, IL 60611, USA. Electronic address: norrina.allen@northwestern.edu. 3. Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19(th) floor, Chicago, IL 60611, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 North Lakeshore Drive, Suite 1400, Chicago, IL 60611, USA. Electronic address: lindsay.pool@northwestern.edu. 4. Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19(th) floor, Chicago, IL 60611, USA; Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, 250 East Superior Street, Room 05-2175, Chicago, IL 60611, USA. Electronic address: emily-miller-1@northwestern.edu. 5. Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19(th) floor, Chicago, IL 60611, USA; Department of Pediatrics, Division of Neonatology, Ann & Robert H. Lurie Children's Hospital of Chicago, 225 East Chicago Avenue, Box 45, Chicago, IL 60611, USA. Electronic address: npouppirt@luriechildrens.org. 6. Department of Psychological & Brain Sciences, Washington University, Box 1125, One Brookings Drive, St. Louis, MO 63130, USA. Electronic address: dbarch@wustl.edu. 7. Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S. Euclid Box 8511, St. Louis, MO 63110, USA. Electronic address: lubyj@wustl.edu. 8. Department of Child and Adolescent Psychiatry, Washington University School of Medicine in St. Louis, 4444 Forest Park Ave, St. Louis, MO 63110, United States of America. Electronic address: perlmansusan@wustl.edu. 9. Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S. Euclid Box 8511, St. Louis, MO 63110, USA. Electronic address: rogersc@psychiatry.wustl.edu. 10. Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine in St. Louis, 4525 Scott Avenue, St. Louis, MO 63110, USA. Electronic address: smyserc@neuro.wustl.edu. 11. Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, 625 N Michigan Avenue, Suite 2100, Chicago, IL 60611, USA; Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19(th) floor, Chicago, IL 60611, USA. Electronic address: lauriew@northwestern.edu.
Abstract
BACKGROUND: A major challenge in prenatal drug exposure research concerns the balance of measurement quality with sample sizes necessary to address confounders. To inform the selection of optimal exposure measures for the HEALthy Brain and Child Development (HBCD) Study, we employed integrated analysis to determine how different methods used to characterize prenatal tobacco exposure influence the detection of exposure-related risk, as reflected in normal variations in birth weight. METHODS: Participants were N = 2323 mother-infant dyads derived from 7 independent developmental cohorts harmonized on measures of exposure, outcome (birthweight), and covariates. We compared estimates of PTE-related effects on birthweight derived from linear regression models when PTE was categorized dichotomously based on any fetal exposure (30% exposed; 69% not exposed); versus categorically, based on common patterns of maternal smoking during pregnancy (never smoked 69%; quit smoking 16%; smoked intermittently 2%; smoked persistently 13%). We secondarily explored sex differences in PTE-birthweight associations across these categorization methods. RESULTS: When PTE was categorized dichotomously, exposure was associated with a - 125-g difference in birthweight (95% C.I. -173.7 - -76.6, p < .0001). When PTE was characterized categorically based on maternal smoking patterns, however, exposure was associated with either no difference in birthweight if mothers quit smoking by the end of the first trimester (B = -30.6, 95% C.I. -88.7-27.4, p = .30); or a - 221.8 g difference in birthweight if mothers did not [95% C.I. (-161.7 to -282.0); p < .001]. Qualitative sex differences were also detected though PTE x sex interactions did not reach statistical significance. Maternal smoking cessation during pregnancy was associated with a 239.3 g increase in birthweight for male infants, and a 114.0 g increase in birthweight for females infants (p = .07). CONCLUSIONS: Categorization of PTE based on patterns of maternal smoking rather than the presence or absence of exposure alone revealed striking nuances in estimates of exposure-related risk. The described method that captures both between-individual and within-individual variability in prenatal drug exposure is optimal and recommended for future developmental investigations such as the HBCD Study.
BACKGROUND: A major challenge in prenatal drug exposure research concerns the balance of measurement quality with sample sizes necessary to address confounders. To inform the selection of optimal exposure measures for the HEALthy Brain and Child Development (HBCD) Study, we employed integrated analysis to determine how different methods used to characterize prenatal tobacco exposure influence the detection of exposure-related risk, as reflected in normal variations in birth weight. METHODS: Participants were N = 2323 mother-infant dyads derived from 7 independent developmental cohorts harmonized on measures of exposure, outcome (birthweight), and covariates. We compared estimates of PTE-related effects on birthweight derived from linear regression models when PTE was categorized dichotomously based on any fetal exposure (30% exposed; 69% not exposed); versus categorically, based on common patterns of maternal smoking during pregnancy (never smoked 69%; quit smoking 16%; smoked intermittently 2%; smoked persistently 13%). We secondarily explored sex differences in PTE-birthweight associations across these categorization methods. RESULTS: When PTE was categorized dichotomously, exposure was associated with a - 125-g difference in birthweight (95% C.I. -173.7 - -76.6, p < .0001). When PTE was characterized categorically based on maternal smoking patterns, however, exposure was associated with either no difference in birthweight if mothers quit smoking by the end of the first trimester (B = -30.6, 95% C.I. -88.7-27.4, p = .30); or a - 221.8 g difference in birthweight if mothers did not [95% C.I. (-161.7 to -282.0); p < .001]. Qualitative sex differences were also detected though PTE x sex interactions did not reach statistical significance. Maternal smoking cessation during pregnancy was associated with a 239.3 g increase in birthweight for male infants, and a 114.0 g increase in birthweight for females infants (p = .07). CONCLUSIONS: Categorization of PTE based on patterns of maternal smoking rather than the presence or absence of exposure alone revealed striking nuances in estimates of exposure-related risk. The described method that captures both between-individual and within-individual variability in prenatal drug exposure is optimal and recommended for future developmental investigations such as the HBCD Study.
Authors: Darya Gaysina; David M Fergusson; Leslie D Leve; John Horwood; David Reiss; Daniel S Shaw; Kit K Elam; Misaki N Natsuaki; Jenae M Neiderhiser; Gordon T Harold Journal: JAMA Psychiatry Date: 2013-09 Impact factor: 21.596
Authors: Lauren S Wakschlag; Darius Tandon; Sheila Krogh-Jespersen; Amelie Petitclerc; Ashley Nielsen; Rhoozbeh Ghaffari; Leena Mithal; Michael Bass; Erin Ward; Jonathan Berken; Elveena Fareedi; Peter Cummings; Karen Mestan; Elizabeth S Norton; William Grobman; John Rogers; Judith Moskowitz; Nabil Alshurafa Journal: Dev Psychobiol Date: 2020-11-22 Impact factor: 3.038