title: Comparison of gestational dating methods and implications for exposure-outcome associations: an example with PM2.5 and preterm birth.
abstract: Estimating gestational age is usually based on date of last menstrual period (LMP) or clinical estimation (CE); both approaches introduce potential bias. Differences in methods of estimation may lead to misclassification and inconsistencies in risk estimates, particularly if exposure assignment is also gestation-dependent. This paper examines a 'what-if' scenario in which alternative methods are used and attempts to elucidate how method choice affects observed results.
  
  
  
  We constructed two 20-week gestational age cohorts of pregnancies between 2000 and 2005 (New Jersey, Pennsylvania, Ohio, USA) using live birth certificates: one defined preterm birth (PTB) status using CE and one using LMP. Within these, we estimated risk for 4 categories of preterm birth (PTBs per 106pregnancies) and risk differences (RD (95% CIs)) associated with exposure to particulate matter (PM2.5).
  
  
  
  More births were classified preterm using LMP (16%) compared with CE (8%). RD divergences increased between cohorts as exposure period approached delivery. Among births between 28 and 31 weeks, week 7 PM2.5exposure conveyed RDs of 44 (21 to 67) for CE and 50 (18 to 82) for LMP populations, while week 24 exposure conveyed RDs of 33 (11 to 56) and -20 (-50 to 10), respectively.
  
  
  
  Different results from analyses restricted to births with both CE and LMP are most likely due to differences in dating methods rather than selection issues. Results are sensitive to choice of gestational age estimation, though degree of sensitivity can vary by exposure timing. When both outcome and exposure depend on estimate of gestational age, awareness of nuances in the method used for estimation is critical.
authors.affiliation: National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Office of Research and Development, Chapel Hill, North Carolina, USA.
authors.forename: Kristen M
authors.initials: KM
authors.lastname: Rappazzo
authors.affiliation: National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Office of Research and Development, Chapel Hill, North Carolina, USA.
authors.forename: Danelle T
authors.initials: DT
authors.lastname: Lobdell
authors.affiliation: School of Community Health-College of Urban and Public Affairs, Portland State University Portland, Portland, Oregon, USA.
authors.forename: Lynne C
authors.initials: LC
authors.lastname: Messer
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA.
authors.forename: Charles
authors.initials: C
authors.lastname: Poole
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA.
authors.forename: Julie L
authors.initials: JL
authors.lastname: Daniels
mesh_terms: D000328:Adult; D015982:Bias; D015331:Cohort Studies; D004781:Environmental Exposure / Q000009:adverse effects; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D008597:Menstrual Cycle / Q000502:physiology; D010316:Particle Size; D052638:Particulate Matter / Q000009:adverse effects; D011247:Pregnancy; D047928:Premature Birth / Q000145:classification*; D012044:Regression Analysis; D015203:Reproducibility of Results; D013997:Time Factors; D014481:United States; D055815:Young Adult
chemical_list: D052638:Particulate Matter
keywords: environmental exposure; gestational dating; particulate matter; preterm birth