Work Description

Title: ABC Baby - Data for Developmental Trajectories of Eating Behaviors and Cross-Lagged Associations with Weight Across Infancy Open Access Deposited

h
Attribute Value
Methodology
  • Mothers completed questionnaires and infants were weighed and length measured. For details, please see Manuals of Operations file in this deposit, and the published manuscript.
Description
  • Healthy full-term infants were enrolled in a longitudinal study designed to examine the development of infant eating behavior. Infant weight and length was measured, mothers completed questionnaires regarding infant eating behaviors, and infants were weighed and length measured at ages 1, 2, 4, 6 and 10 months. Trajectories of eating behaviors were identified using latent class growth modeling and bivariate analyses examined associations of infant eating behavior trajectory membership with infant and maternal characteristics. Cross-lagged analyses examined associations between BEBQ subscales and infant weight-for-length z-score.
Creator
Creator ORCID iD
Depositor
  • jlumeng@umich.edu
Contact information
Discipline
Funding agency
  • National Institutes of Health (NIH)
ORSP grant number
  • 15-PAF00113
Keyword
Date coverage
  • 2015-10-01 to 2023-07-01
Citations to related material
  • Harlan McCaffery, Julie Zaituna, Sophie Busch, Niko Kaciroti, Alison L. Miller, Julie C. Lumeng, Katherine L. Rosenblum, Ashley Gearhardt, Megan H. Pesch, Developmental trajectories of eating behaviors and cross-lagged associations with weight across infancy, Appetite, 2023, 106978
Resource type
Last modified
  • 08/09/2023
Published
  • 08/09/2023
Language
DOI
  • https://doi.org/10.7302/3ykn-qa06
License
To Cite this Work:
Lumeng, J. C. (2023). ABC Baby - Data for Developmental Trajectories of Eating Behaviors and Cross-Lagged Associations with Weight Across Infancy [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/3ykn-qa06

Relationships

In Collection:

Files (Count: 5; Size: 746 KB)

Thumbnailthumbnail-column Title Original Upload Last Modified File Size Access Actions
README.txt 2023-07-24 2023-08-09 1.81 KB Open Access
Informed_Consent_Document.zip 2023-07-24 2023-07-24 175 KB Open Access
Manuals_of_Operations.zip 2023-07-24 2023-07-24 364 KB Open Access
Data_Dictionaries.zip 2023-07-24 2023-07-24 112 KB Open Access
Data.zip 2023-07-24 2023-07-24 93.3 KB Open Access

Date: July 24, 3023

Dataset Title: dataset_for_Developmental_Trajectories_Eating

Dataset Creators: Julie C Lumeng

Dataste Contact: Julie Lumeng jlumeng@umich.edu

Funding: R01HD084163

Key points: We identify eating behavior profiles among healthy, full-term infants and assess their associations with weight and eating behaviors.

Research Overview: Infant eating behavior was reported by questionnaire. Infant anthropometry was obtained. Trajectory analysis was used to identify latent classes of eating behaviors and cross-lagged anlaysis was used to identify associations between weight-for-length z-scores and eating behaviors.

Methodology: That data were generated from maternal report of infant behaviors and demographics by questionniare, and anthropometry performed by trained research assistants.

Instrument and/or Software specifications: NA

Files Contained here within Zipped Folder:

-Data: Final data set used in published manuscript
-Data Dictionaries: Data dictionary for each measure used, including questionnaire items and variable definitions
-Informed Consent Document: Informed Consent Document signed by participants
-Manuals of Operations: Manuals describing how all data were collected in detail

Related publication: Harlan McCaffery, Julie Zaituna, Sophie Busch, Niko Kaciroti, Alison L. Miller, Julie C. Lumeng, Katherine L. Rosenblum, Ashley Gearhardt, Megan H. Pesch, Developmental trajectories of eating behaviors and cross-lagged associations with weight across infancy, Appetite, 2023, 106978

Use and Access: This data set is made available under a Creative Commons Public Domain license (CC0 1.0).

To Cite Data: To Cite Data:
Lumeng, J.C. (2023). ABC Baby Sucking Data [Data set]. University of Michigan - Deep Blue.

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