Foetal ultrasound measurement imputations based on growth curves versus multiple imputation chained equation (MICE)
dc.contributor.author | Ferguson, Kelly K. | |
dc.contributor.author | Yu, Youfei | |
dc.contributor.author | Cantonwine, David E. | |
dc.contributor.author | McElrath, Thomas F. | |
dc.contributor.author | Meeker, John D. | |
dc.contributor.author | Mukherjee, Bhramar | |
dc.date.accessioned | 2018-11-20T15:31:56Z | |
dc.date.available | 2019-11-01T15:10:32Z | en |
dc.date.issued | 2018-09 | |
dc.identifier.citation | Ferguson, Kelly K.; Yu, Youfei; Cantonwine, David E.; McElrath, Thomas F.; Meeker, John D.; Mukherjee, Bhramar (2018). "Foetal ultrasound measurement imputations based on growth curves versus multiple imputation chained equation (MICE)." Paediatric and Perinatal Epidemiology 32(5): 469-473. | |
dc.identifier.issn | 0269-5022 | |
dc.identifier.issn | 1365-3016 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/146300 | |
dc.description.abstract | BackgroundUltrasound measures are valuable for epidemiologic studies of risk factors for growth restriction. Longitudinal measurements enable investigation of rates of change and identification of windows where growth is impacted more acutely. However, missing data can be problematic in these studies, limiting sample size, ability to characterise windows of vulnerability, and in some instances creating bias. We sought to compare a parametric linear mixed model (LMM) approach to multiple imputation in this setting with multiple imputation by chained equation (MICE) methodology.MethodsUltrasound scans performed for clinical purposes were abstracted from women in the LIFECODES birth cohort (n = 1003) if they were close in time to three study visits (median 18, 26, and 35 weeks’ gestation). We created imputed datasets using LMM and MICE and calculated associations between demographic factors and ultrasound parameters cross‐sectionally and longitudinally. Results were compared with a complete‐case analysis.ResultsMost participants had ultrasounds at 18 weeks’ gestation, and ~50% had measurements at 26 and 35 weeks; 100% had birthweight. Associations between demographic factors and ultrasound measures were similar in magnitude, but more precise, when either imputed datasets were used, compared with a complete‐case analysis, in both the cross‐sectional or longitudinal analyses.ConclusionsMICE, though ignoring the non‐linear features of the trajectory and within subject correlation, is able to provide reasonable imputation of foetal growth data when compared to LMM. Because it simultaneously imputes missing covariate data and does not require specification of variance structure as in LMM, MICE may be preferable for imputation in this setting. | |
dc.publisher | Wiley Periodicals, Inc. | |
dc.subject.other | statistical methodology | |
dc.subject.other | ultrasound | |
dc.subject.other | MICE | |
dc.subject.other | longitudinal modelling | |
dc.subject.other | Imputation | |
dc.subject.other | foetal growth | |
dc.title | Foetal ultrasound measurement imputations based on growth curves versus multiple imputation chained equation (MICE) | |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | |
dc.subject.hlbsecondlevel | Pediatrics | |
dc.subject.hlbtoplevel | Health Sciences | |
dc.description.peerreviewed | Peer Reviewed | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/146300/1/ppe12486_am.pdf | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/146300/2/ppe12486.pdf | |
dc.identifier.doi | 10.1111/ppe.12486 | |
dc.identifier.source | Paediatric and Perinatal Epidemiology | |
dc.identifier.citedreference | Grewal J, Grantz KL, Zhang C, et al. Cohort profile: NICHD fetal growth studies‐singletons and twins. Int J Epidemiol. 2018; 47: 25 ‐ 25l. | |
dc.identifier.citedreference | Aguilera I, Garcia‐Esteban R, Iñiguez C, et al. Prenatal exposure to traffic‐related air pollution and ultrasound measures of fetal growth in the INMA Sabadell cohort. Environ Health Perspect. 2010; 118: 705. | |
dc.identifier.citedreference | van den Hooven EH, Pierik FH, de Kluizenaar Y, et al. Air pollution exposure during pregnancy, ultrasound measures of fetal growth, and adverse birth outcomes: a prospective cohort study. Environ Health Perspect. 2012; 120: 150. | |
dc.identifier.citedreference | Casas M, Valvi D, Ballesteros‐Gomez A, et al. Exposure to bisphenol A and phthalates during pregnancy and ultrasound measures of fetal growth in the INMA‐Sabadell cohort. Environ Health Perspect. 2016; 124: 521. | |
dc.identifier.citedreference | Jaddoe VW, Verburg BO, De Ridder M, et al. Maternal smoking and fetal growth characteristics in different periods of pregnancy: the generation R study. Am J Epidemiol. 2007; 165: 1207 ‐ 1215. | |
dc.identifier.citedreference | Zheng T, Zhang J, Sommer K, et al. Effects of environmental exposures on fetal and childhood growth trajectories. Ann Glob Health. 2016; 82: 41 ‐ 99. | |
dc.identifier.citedreference | Zhang C, Hediger ML, Albert PS, et al. Association of maternal obesity with longitudinal ultrasonographic measures of fetal growth: findings from the NICHD fetal growth studies–singletons. JAMA Pediatr. 2017; 172: 24 ‐ 31. | |
dc.identifier.citedreference | Manzano‐Salgado CB, Casas M, Lopez‐Espinosa M‐J, et al. Prenatal exposure to perfluoroalkyl substances and birth outcomes in a Spanish birth cohort. Environ Int. 2017; 108: 278 ‐ 284. | |
dc.identifier.citedreference | Pinheiro J BD, DebRoy S, Sarkar D; R Core Team. nlme: linear and nonlinear mixed effects models. 2017; R package version 3.1‐131, https://CRAN.R-project.org/package=nlme. Accessed 07/09/18. | |
dc.identifier.citedreference | Hadlock FP, Harrist RB, Martinez‐Poyer J. In utero analysis of fetal growth: a sonographic weight standard. Radiology. 1991; 181: 129 ‐ 133. | |
dc.identifier.citedreference | Cantonwine DE, Ferguson KK, Mukherjee B, et al. Utilizing longitudinal measures of fetal growth to create a standard method to assess the impacts of maternal disease and environmental exposure. PLoS One. 2016; 11: e0146532. | |
dc.identifier.citedreference | van Buuren S, Groothuis‐Oudshoorn K. mice: multivariate imputation by chained equations in R. J Stat Softw. 2011; 45: 1 ‐ 67. | |
dc.identifier.citedreference | Bondarenko I, Raghunathan T. Graphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models. Stat Med. 2016; 35: 3007 ‐ 3020. | |
dc.identifier.citedreference | American College of Obstetricians and Gynecologists. ACOG practice bulletin. Diagnosis and management of preeclampsia and eclampsia. Number 33, January 2002. American College of Obstetricians and Gynecologists. Int J Gynaecol Obstet. 2002; 77: 67. | |
dc.identifier.citedreference | Nguyen PH, Addo OY, Young M, et al. Patterns of fetal growth based on ultrasound measurement and its relationship with small for gestational age at birth in rural Vietnam. Paediatr Perinat Epidemiol. 2016; 30: 256 ‐ 266. | |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.