CODI Prevalence Queries
| Module 1 | Introduction |
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| Module 2 | Getting Started |
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| Module 3 | Audiences/Roles |
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| Module 4 | People & Processes |
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| Module 5 | Standards |
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| Module 6 | Tools |
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| Module 7 | Implementations |
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| Module 8 | Resources |
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| Module 9 | Appendices |
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Who should use the CODI Prevalence Queries?
Researchers typically use the CODI prevalence queries (CODI-PQs) and should review the CODI-PQs implementation guidance links below for detailed information.
What are CODI-PQs?
CODI-PQs provide a suite of tools to calculate population obesity prevalence estimates for youth and teens, adults, and households from electronic health record (EHR) data. Statistical weighting is used to reduce non-probability sample bias and produce representative distributions of the populations of interest. Imputation is used to infer missing race/ethnicity and enable estimation across subpopulations.
CODI-PQs use the National Center for Health Statistics (NCHS) Data Presentation Standards for Proportions9 to suppress estimates based on small sample sizes.
Why use CODI-PQs?
CODI-PQs should be used to generate a population estimate of one of the three categories based on a sample of EHR data for a specific geography (e.g., state, state and county, state and ZIP Code Tabulation Areas [ZCTA-3]) and/or subpopulation (e.g., age group, sex, race).
How to use CODI-PQs
Visit the following links for details on how to use CODI prevalence queries.
Implementation guidance
Github links
