Characterizing a “Big Data” Cohort of Over 200,000 Low-Income U.S. Infants and Children for Obesity Research: The ADVANCE Early Life Cohort
Introduction Low-income populations have elevated exposure to early life risk factors for obesity, but are understudied in longitudinal research. Our objective was to assess the utility of a cohort derived from electronic health record data from safety net clinics for investigation of obesity emergi...
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Veröffentlicht in: | Maternal and child health journal 2017-03, Vol.21 (3), p.421-431 |
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Sprache: | eng |
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Zusammenfassung: | Introduction
Low-income populations have elevated exposure to early life risk factors for obesity, but are understudied in longitudinal research. Our objective was to assess the utility of a cohort derived from electronic health record data from safety net clinics for investigation of obesity emerging in early life.
Methods
We examined data from the PCORNet ADVANCE Clinical Data Research Network, a national network of Federally-Qualified Health Centers serving >1.7 million safety net patients across the US. This cohort includes patients who, in 2012–2014, had ≥1 valid body mass index measure when they were 0–5 years of age. We characterized the cohort with respect to factors required for early life obesity research in vulnerable subgroups: sociodemographic diversity, weight status based on World Health Organization ( |
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ISSN: | 1092-7875 1573-6628 |
DOI: | 10.1007/s10995-016-2232-5 |