Statistical methods for modeling repeated measures of maternal environmental exposure biomarkers during pregnancy in association with preterm birth -No section-

Environmental Health: A Global Access Science Source

Volumn 14, Issue 1, 2015, Pages

  Chen, Yin Hsiu ^a   Ferguson, Kelly K ^a   Meeker, John D ^a   McElrath, Thomas F ^b   Mukherjee, Bhramar ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

Biomarkers; Environment; Prematurity; Repeated measures; Statistical methods

Indexed keywords

BIOLOGICAL MARKER; ENVIRONMENTAL CHEMICAL; PHTHALIC ACID; DANGEROUS GOODS; PHTHALIC ACID DERIVATIVE;

BIOMARKER; EPIDEMIOLOGY; FUTURE PROSPECT; MATERNAL HEALTH; MEASUREMENT METHOD; METABOLITE; PHTHALATE; POLLUTION EXPOSURE; PREGNANCY; STATISTICAL ANALYSIS; URINE;

ARTICLE; CLINICAL EVALUATION; DISEASE ASSOCIATION; ENVIRONMENTAL EXPOSURE; EPIDEMIOLOGICAL DATA; EXPOSURE VARIABLE; FEMALE; GESTATIONAL AGE; HUMAN; LOGISTIC REGRESSION ANALYSIS; MATHEMATICAL ANALYSIS; MAXIMUM LIKELIHOOD METHOD; MEASUREMENT ACCURACY; MULTIVARIATE LOGISTIC REGRESSION ANALYSIS; OUTCOME ASSESSMENT; PREGNANCY; PREGNANCY OUTCOME; PREMATURE LABOR; PREMATURITY; PRIORITY JOURNAL; STATISTICAL ANALYSIS; URINALYSIS; ADULT; ADVERSE EFFECTS; AGE; CASE CONTROL STUDY; CHEMICALLY INDUCED; CROSS-SECTIONAL STUDY; DANGEROUS GOODS; MASSACHUSETTS; MATERNAL EXPOSURE; METABOLISM; MIDDLE AGED; NEWBORN; SOCIOECONOMICS; STATISTICAL MODEL; URINE; YOUNG ADULT;

ADULT; AGE FACTORS; BIOMARKERS; BOSTON; CASE-CONTROL STUDIES; CROSS-SECTIONAL STUDIES; DATA INTERPRETATION, STATISTICAL; ENVIRONMENTAL EXPOSURE; FEMALE; HAZARDOUS SUBSTANCES; HUMANS; INFANT, NEWBORN; MATERNAL EXPOSURE; MIDDLE AGED; MODELS, STATISTICAL; PHTHALIC ACIDS; PREGNANCY; PREMATURE BIRTH; SOCIOECONOMIC FACTORS; YOUNG ADULT;

EID: 84928733056     PISSN: None     EISSN: 1476069X     Source Type: Journal    
DOI: 10.1186/1476-069X-14-9     Document Type: Article

References (30)

1. Behrman RE, Butler AS: Preterm Birth: Causes, Consequences, And Prevention. Washington, DC: The National Academies Press; 2007.
2. Bastek JA, Elovitz MA: The role and challenges of biomarkers in spontaneous preterm birth and preeclampsia. Fertil Steril 2013, 99:1117-23. 10.1016/j.fertnstert.2013.01.104
3. Genc MR, Ford CE: The clinical use of inflammatory markers during pregnancy. Curr Opin Obstet Gynecol 2010, 22:116-21. 10.1097/GCO.0b013e3283374ac8
4. Menon R, Torloni MR, Voltolini C, Torricelli M, Merialdi M, Betran AP, et al.: Biomarkers of spontaneous preterm birth: an overview of the literature in the last four decades. Reprod Sci 2011, 18:1046-70. 10.1177/1933719111415548
5. Ferguson KK, O'Neill MS, Meeker JD: Environmental contaminant exposures and preterm birth: a comprehensive review. J Toxicol Environ Health B Crit Rev 2013, 16:69-113. 10.1080/10937404.2013.775048
6. Sanchez BN, Hu H, Litman HJ, Tellez-Rojo MM: Statistical methods to study timing of vulnerability with sparsely sampled data on environmental toxicants. Environ Health Perspect 2011, 119:409-15.
7. Bhadra D, Daniels MJ, Kim S, Ghosh M, Mukherjee B: A Bayesian semiparametric approach for incorporating longitudinal information on exposure history for inference in case-control studies. Biometrics 2012, 68:361-70. 10.1111/j.1541-0420.2011.01686.x
8. Patelarou E, Kargaki S, Stephanou EG, Nieuwenhuijsen M, Sourtzi P, Gracia E, et al.: Exposure to brominated trihalomethanes in drinking water and reproductive outcomes. Occup Environ Med 2011, 68:438-45. 10.1136/oem.2010.056150
9. Wilhelm M, Ghosh JK, Su J, Cockburn M, Jerrett M, Ritz B: Traffic-related air toxics and preterm birth: a population-based case-control study in Los Angeles county, California. Environ Health 2011, 10:89. 10.1186/1476-069X-10-89
10. Ferguson KK, McElrath TF, Meeker JD: Environmental phthalate exposure and preterm birth. JAMA Pediatr 2014, 168:61-7. 10.1001/jamapediatrics.2013.3699
11. Ferguson KK, McElrath TF, Ko YA, Mukherjee B, Meeker JD: Variability in urinary phthalate metabolite levels across pregnancy and sensitive windows of exposure for the risk of preterm birth. Environ Int 2014, 70:118-24.
12. Cantonwine D, Hu H, Sánchez BN, Lamadrid-Figueroa H, Smith D, Ettinger AS, et al.: Critical windows of fetal lead exposure: adverse impacts on length of gestation and risk of premature delivery. J Occup Environ Med 2010, 52:1106. 10.1097/JOM.0b013e3181f86fee
13. Farrar DE, Glauber RR: Multicollinearity in regression analysis: the problem revisited. Rev Econ Stat 1967, 92-107.
14. Baltagi B: Econometric Analysis of Panel Data. John Wiley & Sons; 2008.
15. Warren J, Fuentes M, Herring A, Langlois P: Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure. Biometrics 2012, 68:1157-67. 10.1111/j.1541-0420.2012.01774.x
16. Arellano-Valle R, Bolfarine H, Lachos V: Skew-normal linear mixed models. J Data Sci 2005, 3:415-38.
17. Zhang P, Song PXK, Qu A, Greene T: Efficient estimation for patient-specific rates of disease progression using nonnormal linear mixed models. Biometrics 2008, 64:29-38. 10.1111/j.1541-0420.2007.00824.x
18. Wood SN: Low-rank scale-invariant tensor product smooths for generalized additive mixed models. Biometrics 2006, 62:1025-36. 10.1111/j.1541-0420.2006.00574.x
19. Fraley C, Raftery AE: Model-based clustering, discriminant analysis, and density estimation. J Am Stat Assoc 2002, 97:611-31. 10.1198/016214502760047131
20. Banfield JD, Raftery AE: Model-based Gaussian and non-Gaussian clustering. Biometrics 1993, 803-21.
21. Schwarz G: Estimating the dimension of a model. Ann Stat 1978, 6:461-4. 10.1214/aos/1176344136
22. Flury BA: Principal points. Biometrika 1990, 77:33-41. 10.1093/biomet/77.1.33
23. Tarpey T, Kinateder KK: Clustering functional data. J Classification 2003, 20:093-114. 10.1007/s00357-003-0007-3
24. MÜLLER HG: Functional modelling and classification of longitudinal data∗. Scand J Stat 2005, 32:223-40. 10.1111/j.1467-9469.2005.00429.x
25. Yao F, Müller H-G, Wang J-L: Functional data analysis for sparse longitudinal data. J Am Stat Assoc 2005, 100:577-90. 10.1198/016214504000001745
26. Peng J, Paul D: A geometric approach to maximum likelihood estimation of the functional principal components from sparse longitudinal data. J Comput Graph Stat 2009, 18:995-1015. 10.1198/jcgs.2009.08011
27. Auger N, Naimi AI, Smargiassi A, Lo E, Kosatsky T: Extreme heat and risk of early delivery among preterm and term pregnancies. Epidemiology 2014, 25:344-50. 10.1097/EDE.0000000000000074
28. Suh YJ, Kim H, Seo JH, Park H, Kim YJ, Hong YC, et al.: Different effects of PM10 exposure on preterm birth by gestational period estimated from time-dependent survival analyses. Int Arch Occup Environ Health 2009, 82:613-21. 10.1007/s00420-008-0380-7
29. Wei P, Tang H, Li D: Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study. Genet Epidemiol 2014, 38:638-51. 10.1002/gepi.21852
30. Little RJ, Rubin DB: Statistical Analysis With Missing Data. Second edition. John Wiley & Sons; 2002.