Online Program

Oral

Ongoing state- and locally-specific BMI surveillance is a critical component of the public health response to the obesity epidemic. However, fewer than one half of states operate statewide childhood BMI surveillance systems, many with limited sample sizes lacking representativeness at the city or school-district level. No states collect objectively-measured data on adult BMI distributions needed to project future state obesity-related medical expenditures and plan public health interventions. However, statistical matching and bootstrap sampling methods can be used to combine data from a range of publicly-available sources to provide bias-corrected prevalence estimates at state and local levels in the absence of a robust surveillance infrastructure.

Session Objectives: Panel attendees will be able to: 1. Understand strengths and limitations of existing BMI surveillance structure at the state and national level as well as best practices for surveillance systems 2. Understand importance of statistical matching and bootstrap sampling methods for synthesizing new datasets from existing publicly available administrative and public health sources 3. Through the lens of bias-corrected state-specific obesity prevalence estimates, understand how applied public health statistics can shape public health agenda

CE Credits: Medical (CME), Health Education (CHES), Nursing (CNE), Public Health (CPH) , Masters Certified Health Education Specialist (MCHES)