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Profiles and predictors of child neurodevelopment and anthropometry: The maternal-infant research on environmental
Marisa A Patti1, Karl T Kelsey1, Amanda J MacFarlane2,3
1Department of Epidemiology, Brown University, Providence, RI, USA.
Insights
This study identified distinct profiles of child neurodevelopment and adiposity, revealing associations with socioeconomic factors and maternal health. Understanding these complex patterns is crucial for targeted interventions in early childhood development.
Area of Science:
- Child Health Research
- Developmental Pediatrics
- Environmental Health
Background:
- Individual health metrics overlook co-occurring conditions in children.
- Childhood health is multifaceted, encompassing neurodevelopment and physical growth.
- Comprehensive assessment is needed to understand children's health trajectories.
Purpose of the Study:
- To define distinct profiles of neurodevelopment and anthropometry in 3-year-old children.
- To identify predictors associated with these identified health profiles.
- To explore the interplay between neurodevelopmental and anthropometric outcomes.
Main Methods:
- Latent profile analysis applied to 12 neurodevelopmental and anthropometric traits in 501 mother-child pairs from the MIREC Study.
- Prospective cohort study design examining children at age 3.
- Multinomial regression used to assess associations with maternal, sociodemographic, and child characteristics.
Main Results:
- Three neurodevelopmental profiles emerged: Non-optimal (9%), Typical (49%), and Optimal (42%).
- Three anthropometric profiles were identified: Low (12%), Average (61%), and Excess Adiposity (27%).
- Lower socioeconomic status, birth factors, and maternal mental health predicted non-optimal neurodevelopment; maternal BMI predicted excess adiposity.
Conclusions:
- Childhood neurodevelopment and adiposity present in distinct phenotypic profiles.
- These profiles are linked to a range of maternal, sociodemographic, and child-level factors.
- Co-occurrence of non-optimal neurodevelopment and excess adiposity was infrequent.
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.
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