{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:49:47Z","timestamp":1760150987424,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,2,2]],"date-time":"2022-02-02T00:00:00Z","timestamp":1643760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council","doi-asserted-by":"publisher","award":["RGPIN-2019-04-862"],"award-info":[{"award-number":["RGPIN-2019-04-862"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Despite the importance of maternal gestational weight gain, it is not yet conclusively understood how weight gain during different stages of pregnancy influences health outcomes for either mother or child. We partially attribute this to differences in and the validity of statistical methods for the analysis of longitudinal and scalar outcome data. In this paper, we propose a Bayesian joint regression model that estimates and uses trajectory parameters as predictors of a scalar response. Our model remedies notable issues with traditional linear regression approaches found in the clinical literature. In particular, our methodology accommodates nonprospective designs by correcting for bias in self-reported prestudy measures; truly accommodates sparse longitudinal observations and short-term variation without data aggregation or precomputation; and is more robust to the choice of model changepoints. We demonstrate these advantages through a real-world application to the Alberta Pregnancy Outcomes and Nutrition (APrON) dataset and a comparison to a linear regression approach from the clinical literature. Our methods extend naturally to other maternal and infant outcomes as well as to areas of research that employ similarly structured data.<\/jats:p>","DOI":"10.3390\/e24020232","type":"journal-article","created":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T05:42:33Z","timestamp":1643866953000},"page":"232","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Associations between Longitudinal Gestational Weight Gain and Scalar Infant Birth Weight: A Bayesian Joint Modeling Approach"],"prefix":"10.3390","volume":"24","author":[{"given":"Matthew","family":"Pietrosanu","sequence":"first","affiliation":[{"name":"Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2G1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3011-9216","authenticated-orcid":false,"given":"Linglong","family":"Kong","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2G1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Public Health, University of Alberta, Edmonton, AB T6G 1C9, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4298-9641","authenticated-orcid":false,"given":"Rhonda C.","family":"Bell","sequence":"additional","affiliation":[{"name":"Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7468-915X","authenticated-orcid":false,"given":"Nicole","family":"Letourneau","sequence":"additional","affiliation":[{"name":"Faculty of Nursing and Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bei","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2G1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2175","DOI":"10.1001\/jama.2017.6265","article-title":"Gestational weight gain and outcomes for mothers and infants","volume":"317","author":"Caughey","year":"2017","journal-title":"J. Am. Med. Assoc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/S0301-2115(00)00329-8","article-title":"Pregnancy-related changes in body fat","volume":"94","author":"Sidebottom","year":"2001","journal-title":"Eur. J. Obstet. Gynecol. Reprod. Biol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1093\/jn\/124.1.24","article-title":"Changes in maternal upper arm fat stores are predictors of variation in infant birth weight","volume":"124","author":"Hediger","year":"1994","journal-title":"J. Nutr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1750","DOI":"10.1093\/ajcn\/87.6.1750","article-title":"Combined associations of prepregnancy body mass index and gestational weight gain with the outcome of pregnancy","volume":"87","author":"Nohr","year":"2008","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"i555","DOI":"10.1136\/bmj.i555","article-title":"Gestational weight gain standards based on women enrolled in the fetal growth longitudinal study of the INTERGROWTH-21st Project: A prospective longitudinal cohort study","volume":"352","author":"Ismail","year":"2016","journal-title":"BMJ"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1056\/NEJMra0708473","article-title":"Effect of in utero and early-life conditions on adult health and disease","volume":"359","author":"Gluckman","year":"2008","journal-title":"N. Engl. J. Med."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/07853890.1999.11904392","article-title":"Fetal origins of cardiovascular disease","volume":"31","author":"Barker","year":"1999","journal-title":"Ann. Med."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1002\/oby.21006","article-title":"Patterns of gestational weight gain related to fetal growth among women with overweight and obesity","volume":"23","author":"Catov","year":"2015","journal-title":"Obesity"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.jogc.2015.12.014","article-title":"Timing of excessive weight gain during pregnancy modulates newborn anthropometry","volume":"38","author":"Ruchat","year":"2016","journal-title":"J. Obstet. Gynaecol. Can."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"502.e1","DOI":"10.1016\/j.ajog.2014.12.038","article-title":"Association of trimester-specific gestational weight gain with fetal growth, offspring obesity, and cardiometabolic traits in early childhood","volume":"212","author":"Karachaliou","year":"2015","journal-title":"Am. J. Obstet. Gynecol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1093\/jn\/129.5.988","article-title":"Low maternal weight gain in the second or third trimester increases the risk for intrauterine growth retardation","volume":"129","author":"Strauss","year":"1999","journal-title":"J. Nutr."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Sridhar, S.B., Xu, F., and Hedderson, M.M. (2016). Trimester-specific gestational weight gain and infant size for gestational age. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0159500"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1001\/jamapediatrics.2017.4016","article-title":"Association of timing of weight gain in pregnancy with infant birth weight","volume":"172","author":"Retnakaran","year":"2018","journal-title":"JAMA Pediatr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1093\/oxfordjournals.aje.a116875","article-title":"A Bayesian approach to measurement error problems in epidemiology using conditional independence models","volume":"138","author":"Richardson","year":"1993","journal-title":"Am. J. Epidemiol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1080\/01621459.1995.10476485","article-title":"Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS","volume":"90","author":"Tsiatis","year":"1995","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1111\/j.0006-341X.1999.00463.x","article-title":"Finite mixture modeling with mixture outcomes using the EM algorithm","volume":"55","author":"Shedden","year":"1999","journal-title":"Biometrics"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1198\/016214501753208591","article-title":"Jointly modeling longitudinal and event time data with application to acquired immunodeficiency syndrome","volume":"96","author":"Wang","year":"2001","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1093\/biostatistics\/3.4.547","article-title":"The joint modeling of a longitudinal disease progression marker and the failure time process in the presence of cure","volume":"3","author":"Law","year":"2002","journal-title":"Biostatistics"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1111\/j.0006-341X.2002.00742.x","article-title":"A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data","volume":"58","author":"Song","year":"2002","journal-title":"Biometrics"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1111\/1541-0420.00028","article-title":"A Bayesian semiparametric joint hierarchical model for longitudinal and survival data","volume":"59","author":"Brown","year":"2003","journal-title":"Biometrics"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1111\/1541-0420.00079","article-title":"Bayesian approaches to joint cure-rate and longitudinal models with applications to cancer vaccine trials","volume":"59","author":"Brown","year":"2003","journal-title":"Biometrics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1198\/016214507000000400","article-title":"Individual prediction in prostate cancer studies using a joint longitudinal survival\u2013cure model","volume":"103","author":"Yu","year":"2008","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1111\/rssc.12102","article-title":"Modelling short- and long-term characteristics of follicle stimulating hormone as predictors of severe hot flashes in the Penn ovarian aging study","volume":"64","author":"Jiang","year":"2015","journal-title":"J. R. Stat. Soc. Ser. C (Appl. Stat.)"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1198\/1061860043010","article-title":"Bayesian P-splines","volume":"13","author":"Lang","year":"2004","journal-title":"J. Comput. Graph. Stat."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1214\/ss\/1038425655","article-title":"Flexible smoothing with B-splines and penalties","volume":"11","author":"Eilers","year":"1996","journal-title":"Stat. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1111\/biom.12284","article-title":"Joint modeling of cross-sectional health outcomes and longitudinal predictors via mixtures of means and variances","volume":"71","author":"Jiang","year":"2015","journal-title":"Biometrics"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1093\/biostatistics\/kxm003","article-title":"Identifying latent clusters of variability in longitudinal data","volume":"8","author":"Elliott","year":"2007","journal-title":"Biostatistics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1111\/j.1740-8709.2012.00433.x","article-title":"The Alberta pregnancy outcomes and nutrition (APrON) cohort study: Rationale and methods","volume":"10","author":"Kaplan","year":"2012","journal-title":"Matern. Child Nutr."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/S1701-2163(16)35316-6","article-title":"Gestational weight gain and early postpartum weight retention in a prospective cohort of Alberta women","volume":"34","author":"Begum","year":"2012","journal-title":"J. Obstet. Gynaecol. Can."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Che, M., Kong, L., Bell, R.C., and Yuan, Y. (2017). Trajectory modeling of gestational weight: A functional principal component analysis approach. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0186761"},{"key":"ref_31","first-page":"1","article-title":"Births: Final data for 2009","volume":"60","author":"Martin","year":"2011","journal-title":"Natl. Vital Stat. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ruppert, D., Wand, M.P., and Carroll, R.J. (2003). Semiparametric Regression, Cambridge University Press.","DOI":"10.1017\/CBO9780511755453"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1093\/biomet\/56.3.463","article-title":"Estimating the components of a mixture of normal distributions","volume":"56","author":"Day","year":"1969","journal-title":"Biometrika"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1214\/06-BA117B","article-title":"A default conjugate prior for variance components in generalized linear mixed models (Comment on article by Browne and Draper)","volume":"1","author":"Kass","year":"2006","journal-title":"Bayesian Anal."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v042.i12","article-title":"The Scythe statistical library: An open source C library for statistical computation","volume":"42","author":"Pemstein","year":"2011","journal-title":"J. Stat. Softw."},{"key":"ref_36","unstructured":"R Core Team (2021). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_37","unstructured":"Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (2014). Inference and assessing convergence In Bayesian Data Analysis, Chapman and Hall\/CRC. [3rd ed.]. Chapter 11.4."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/2\/232\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:12:54Z","timestamp":1760134374000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/2\/232"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,2]]},"references-count":37,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["e24020232"],"URL":"https:\/\/doi.org\/10.3390\/e24020232","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2022,2,2]]}}}