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 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 (<2 years) or Centers for Disease Control (≥2 years) growth curves, and data longitudinality. Results The cohort includes 216,473 children and is racially/ethnically diverse (e.g., 17.9% Black, 45.4% Hispanic). A majority (56.9%) had family incomes below the Federal Poverty Level (FPL); 32% were <50% of FPL. Among children <2 years, 7.6 and 5.3% had high and low weight-for-length, respectively. Among children 2–5 years, 15.0, 12.7 and 2.4% were overweight, obese, and severely obese, respectively; 5.3% were underweight. In the study period, 79.2% of children had ≥2 BMI measures. Among 4–5 year olds, 21.9% had >1 BMI measure when they were <2 years. Discussion The ADVANCE Early Life cohort offers unique opportunities to investigate early life determinants of obesity in the understudied population of low income and minority children.