Although recent data suggests childhood obesity prevalence has stabilized, an estimated 1 in 3 U.S. children are overweight or obese.1 Further, there is variation by racial and ethnic groups, location, age, and poverty2, resulting in a need for local data to support public health planning and evaluation efforts. Current methods for surveillance of childhood weight status rely on self-report from community-based surveys. However, surveys have long time intervals between data collection periods, are expensive, and are not often able to produce precise small-area estimates. EHRs have been increasingly proposed as an alternative or supplement to community surveys. Childhood weight and height is collected as a part of routine care, and leveraging these data from EHRs may provide rapid and locally precise estimates of childhood weight status. A concern for the use of EHRs is the potential for selection bias. EHRs represent only those seeking healthcare and may not generalize to the population. Additionally, the type of clinical visit (e.g., wellness vs. acute) may affect the prevalence estimates and the likelihood of collecting height and weight data in the EHR. Thus, in addition to EHRs being a convenience sample, there may be additional selection biases based on the type of visit and whether height and weight was measured and recorded. The current work sought to quantify the effect of visit type on childhood overweight and obesity prevalence and generate weights to adjust prevalence for potential EHR-related selection bias.

Objective: To discuss the use of electronic health records (EHRs) for estimation of overweight and obesity prevalence in children aged 2 to 19 years and to compare prevalence between the convenience sample obtained from EHRs to prevalence adjusted for potential selection bias.