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Obesity Prevention in Early Life (OPEL) study: linking longitudinal data to capture obesity risk in the first 1000

Erika R Cheng1, Sami Gharbi1, Tammie L Nelson1

  • 1Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana, USA.

BMJ Nutrition, Prevention & Health
|July 5, 2024
PubMed

Insights

The Obesity Prevention in Early Life (OPEL) database links clinical data with birth records and community factors. This resource supports infant obesity risk prediction and child health outcome studies.

Area of Science:

  • Public Health
  • Epidemiology
  • Biostatistics

Background:

  • Developing accurate infant obesity risk prediction models requires comprehensive data.
  • Existing data sources often lack integrated multi-level information.
  • Longitudinal, population-based data are crucial for understanding early life influences on health outcomes.

Purpose of the Study:

  • To describe the creation of the Obesity Prevention in Early Life (OPEL) database.
  • To detail the methodology for linking diverse administrative and clinical data.
  • To highlight the potential of the OPEL database for child health research.

Main Methods:

  • Linked clinical data, birth certificates, and geocoded area-level indicators.
  • Population-based cohort of 19,437 children born in Marion County, Indiana (2004-2019).
  • Methodology focused on administrative data linkage and database establishment.

Main Results:

  • Established the Obesity Prevention in Early Life (OPEL) database.
  • The database integrates child health outcomes, maternal history, sociodemographics, and community factors.
  • Facilitated a robust dataset for longitudinal studies.

Conclusions:

  • The OPEL database provides a strong foundation for infant obesity research.
  • Supports the development of intergenerational linked clinical-public health databases.
  • Enables advanced longitudinal child health outcomes studies.

Keywords:
Preventive counsellingWeight management

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