title: County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control.
abstract: BACKGROUND
  Epidemiological analyses of aggregated data are often used to evaluate theoretical health effects of natural disasters. Such analyses are susceptible to confounding by unmeasured differences between the exposed and unexposed populations. To demonstrate the difference-in-difference method our population included all recorded Florida live births that reached 20 weeks gestation and conceived after the first hurricane of 2004 or in 2003 (when no hurricanes made landfall). Hurricane exposure was categorized using ≥74 mile per hour hurricane wind speed as well as a 60 km spatial buffer based on weather data from the National Oceanic and Atmospheric Administration. The effect of exposure was quantified as live birth rate differences and 95 % confidence intervals [RD (95 % CI)]. To illustrate sensitivity of the results, the difference-in-differences estimates were compared to general linear models adjusted for census-level covariates. This analysis demonstrates difference-in-differences as a method to control for time-invariant confounders investigating hurricane exposure on live birth rates.
  
  
  RESULTS
  Difference-in-differences analysis yielded consistently null associations across exposure metrics and hurricanes for the post hurricane rate difference between exposed and unexposed areas (e.g., Hurricane Ivan for 60 km spatial buffer [-0.02 births/1000 individuals (-0.51, 0.47)]. In contrast, general linear models suggested a positive association between hurricane exposure and birth rate [Hurricane Ivan for 60 km spatial buffer (2.80 births/1000 individuals (1.94, 3.67)] but not all models.
  
  
  CONCLUSIONS
  Ecological studies of associations between environmental exposures and health are susceptible to confounding due to unmeasured population attributes. Here we demonstrate an accessible method of control for time-invariant confounders for future research.
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive 2101 McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC 27599 USA.
authors.forename: Shannon C
authors.identifier: 0000-0003-3474-6874
authors.initials: SC
authors.lastname: Grabich
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive 2101 McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC 27599 USA.
authors.forename: Whitney R
authors.initials: WR
authors.lastname: Robinson
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive 2101 McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC 27599 USA.
authors.forename: Stephanie M
authors.initials: SM
authors.lastname: Engel
authors.affiliation: Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC USA.
authors.forename: Charles E
authors.initials: CE
authors.lastname: Konrad
authors.affiliation: Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive 2101 McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC 27599 USA.
authors.forename: David B
authors.initials: DB
authors.lastname: Richardson
authors.affiliation: Department of Epidemiology and Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, College Station, TX USA.
authors.forename: Jennifer A
authors.initials: JA
authors.lastname: Horney
keywords: Birth rates; Difference-in-difference; Disaster; Fixed-effect regression; General linear models; Hurricane