Statistical methods for modeling repeated measures of maternal environmental exposure biomarkers during pregnancy in association with preterm birth

Environmental Health

Research

Bhramar Mukherjee¹  Yin-Hsiu Chen¹  Kelly K Ferguson²  John D Meeker²  Thomas F McElrath³ 

[1] Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA;Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA;Division of Maternal-Fetal Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;

关键词: Prematurity;    Environment;    Statistical methods;    Biomarkers;    Repeated measures;   

DOI  :  10.1186/1476-069X-14-9

 received in 2014-09-18, accepted in 2015-01-16,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundIt is of critical importance to evaluate the role of environmental chemical exposures in premature birth. While a number of studies investigate this relationship, most utilize single exposure measurements during pregnancy in association with the outcome. The studies with repeated measures of exposure during pregnancy employ primarily cross-sectional analyses that may not be fully leveraging the power and additional information that the data provide.MethodsWe examine 9 statistical methods that may be utilized to estimate the relationship between a longitudinal exposure and a binary, non-time-varying outcome. To exemplify these methods we utilized data from a nested case–control study examining repeated measures of urinary phthalate metabolites during pregnancy in association with preterm birth.ResultsThe methods summarized may be useful for: 1) Examining sensitive windows of exposure in association with an outcome; 2) Summarizing repeated measures to estimate the relationship between average exposure and an outcome; 3) Identifying acute exposures that may be relevant to the outcome; and 4) Understanding the contribution of temporal patterns in exposure levels to the outcome of interest. In the study of phthalates, changes in urinary metabolites over pregnancy did not appear to contribute significantly to preterm birth, making summary of average exposure across gestation optimal given the current design.ConclusionsThe methods exemplified may be of great use in future epidemiologic research projects intended to: 1) Elucidate the complex relationships between environmental chemical exposures and preterm birth; 2) Investigate biological mechanisms in prematurity using repeated measures of maternal factors throughout pregnancy; and 3) More generally, address the relationship between a longitudinal predictor and a binary, non-time-varying outcome.

【 授权许可】

Unknown   
© Chen et al.; licensee BioMed Central. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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.