Cargando…

County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Grabich, Shannon C., Robinson, Whitney R., Engel, Stephanie M., Konrad, Charles E., Richardson, David B., Horney, Jennifer A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4688997/
https://www.ncbi.nlm.nih.gov/pubmed/26702293
http://dx.doi.org/10.1186/s12982-015-0042-7
_version_ 1782406774775611392
author Grabich, Shannon C.
Robinson, Whitney R.
Engel, Stephanie M.
Konrad, Charles E.
Richardson, David B.
Horney, Jennifer A.
author_facet Grabich, Shannon C.
Robinson, Whitney R.
Engel, Stephanie M.
Konrad, Charles E.
Richardson, David B.
Horney, Jennifer A.
author_sort Grabich, Shannon C.
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12982-015-0042-7) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4688997
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-46889972015-12-24 County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control Grabich, Shannon C. Robinson, Whitney R. Engel, Stephanie M. Konrad, Charles E. Richardson, David B. Horney, Jennifer A. Emerg Themes Epidemiol Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12982-015-0042-7) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-22 /pmc/articles/PMC4688997/ /pubmed/26702293 http://dx.doi.org/10.1186/s12982-015-0042-7 Text en © Grabich et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Grabich, Shannon C.
Robinson, Whitney R.
Engel, Stephanie M.
Konrad, Charles E.
Richardson, David B.
Horney, Jennifer A.
County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
title County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
title_full County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
title_fullStr County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
title_full_unstemmed County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
title_short County-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
title_sort county-level hurricane exposure and birth rates: application of difference-in-differences analysis for confounding control
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4688997/
https://www.ncbi.nlm.nih.gov/pubmed/26702293
http://dx.doi.org/10.1186/s12982-015-0042-7
work_keys_str_mv AT grabichshannonc countylevelhurricaneexposureandbirthratesapplicationofdifferenceindifferencesanalysisforconfoundingcontrol
AT robinsonwhitneyr countylevelhurricaneexposureandbirthratesapplicationofdifferenceindifferencesanalysisforconfoundingcontrol
AT engelstephaniem countylevelhurricaneexposureandbirthratesapplicationofdifferenceindifferencesanalysisforconfoundingcontrol
AT konradcharlese countylevelhurricaneexposureandbirthratesapplicationofdifferenceindifferencesanalysisforconfoundingcontrol
AT richardsondavidb countylevelhurricaneexposureandbirthratesapplicationofdifferenceindifferencesanalysisforconfoundingcontrol
AT horneyjennifera countylevelhurricaneexposureandbirthratesapplicationofdifferenceindifferencesanalysisforconfoundingcontrol