• The method of generating small area estimation (SAE) of the measures is a multilevel statistical modeling framework.
  • Specifically, CDC uses an innovative peer-reviewed multilevel regression and poststratification (MRP) approach that links geocoded health surveys and high spatial resolution population demographic and socioeconomic data.
  • The approach also accounts for the associations between individual health outcomes, individual characteristics, and spatial contexts and factors at multiple levels (e.g., state, county); predicts individual disease risk and health behaviors in a multilevel modeling framework; and estimates the geographic distributions of population disease burden and health behaviors.
  • The MRP approach is flexible and will help CDC provide modeled estimates of the prevalence for each indicator at the census tract and city levels.
  • Small area estimates using this MRP approach have been published using data from CDC’s Behavioral Risk Factor Surveillance System (BRFSS) and the National Survey of Children’s Health.
  • CDC’s internal and external validation studies confirm the strong consistency between MRP model-based SAEs and direct BRFSS survey estimates at both state and county levels.
  • The primary data sources for this project are the CDC Behavioral Risk Factor Surveillance System, the Census 2010 population, and the American Community Survey estimates.
  • The 27 measures include 5 unhealthy behaviors, 13 health outcomes, and 9 prevention practices.
  • The measures include major risk behaviors that lead to illness, suffering, and early death related to chronic diseases and conditions, as well as the conditions and diseases that are the most common, costly, and preventable of all health problems.
  • Each measure has a comprehensive definition that includes the background, significance, limitations of the indicator, data source, and limitations of the data resources.
  • Measures complement existing sets of surveillance indicators that report state, metropolitan area, and county-level data, including County Health Rankings, Chronic Disease Indicators, and Community Health Status Indicators.
List of Measures