Evidence map›Paper›PMID 39803166›Full record

ArticleJournal of multimorbidity and comorbidity

Profiles and predictors of child neurodevelopment and anthropometry: The maternal-infant research on environmental chemicals study.

Marisa A Patti, Karl T Kelsey, Amanda J MacFarlane, George D Papandonatos, Bruce P Lanphear, Joseph M Braun

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Article in Journal of multimorbidity and comorbidity. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Marisa A PattiDepartment of Epidemiology, Brown University, Providence, RI, USA.ORCID https://orcid.org/0000-0003-1113-3207
Karl T KelseyDepartment of Epidemiology, Brown University, Providence, RI, USA.
Amanda J MacFarlaneNutrition Research Division, Health Canada, Ottawa, Canada.
George D PapandonatosDepartment of Biostatistics, Brown University, Providence, RI, USA.
Bruce P LanphearDepartment of Health Sciences, Simon Fraser University, Vancouver, Canada.
Joseph M BraunDepartment of Epidemiology, Brown University, Providence, RI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Evaluating individual health outcomes does not capture co-morbidities children experience. Purpose: We aimed to describe profiles of child neurodevelopment and anthropometry and identify their predictors. Methods: Using data from 501 mother-child pairs (age 3-years) in the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a prospective cohort study, we developed phenotypic profiles by applying latent profile analysis to twelve neurodevelopmental and anthropometric traits. Using multinomial regression, we evaluated odds of phenotypic profiles based on maternal, sociodemographic, and child level characteristics. Results: For neurodevelopmental outcomes, we identified three profiles characterized by Non-optimal (9%), Typical (49%), and Optimal neurodevelopment (42%). For anthropometric outcomes, we observed three profiles of Low (12%), Average (61%), and Excess Adiposity (27%). When examining joint profiles, few children had both Non-optimal neurodevelopment and Excess Adiposity (2%). Lower household income, lower birthweight, younger gestational age, decreased caregiving environment, greater maternal depressive symptoms, and male sex were associated with increased odds of being in the Non-optimal neurodevelopment profile. Higher pre-pregnancy body mass index was associated with increased odds of being in the Excess Adiposity profile. Conclusions: Phenotypic profiles of child neurodevelopment and adiposity were associated with maternal, sociodemographic, and child level characteristics. Few children had both non-optimal neurodevelopment and excess adiposity.

Indexed as

Anthropometrychild healthco-occurring conditionsmultimorbidityneurodevelopmentphenome

Identifiers

PMID39803166
PMCPMC11724418

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