Comparison of Small-Area Analysis Techniques for Estimating Prevalence by Race
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Comparison of Small-Area Analysis Techniques for Estimating Prevalence by Race

Filetype[PDF-414.70 KB]


  • English
    • Details Supporting Files You May Also Like

    Details:

    • Alternative Title:
      Prev Chronic Dis
    • Personal Author:
      Goodman, Melody S
    • Description:
      Introduction

      The Behavioral Risk Factor Surveillance System (BRFSS) is commonly used for estimating the prevalence of chronic disease. One limitation of the BRFSS is that valid estimates can only be obtained for states and larger geographic regions. Limited health data are available on the county level and, thus, many have used small-area analysis techniques to estimate the prevalence of disease on the county level using BRFSS data.

      Methods

      This study compared the validity and precision of 4 small-area analysis techniques for estimating the prevalence of 3 chronic diseases (asthma, diabetes, and hypertension) by race on the county level. County-level reference estimates obtained through local data collection were compared with prevalence estimates produced by direct estimation, synthetic estimation, spatial data smoothing, and regression. Discrepancy statistics used were Pearson and Spearman correlation coefficients, mean square error, mean absolute difference, mean relative absolute difference, and rank statistics.

      Results

      The regression method produced estimates of the prevalence of chronic disease by race on the county level that had the smallest discrepancies for a large number of counties.

      Conclusion

      Regression is the preferable method when applying small-area analysis techniques to obtain county-level prevalence estimates of chronic disease by race using a single year of BRFSS data.

    • Subject:
    • Source:
      Prev Chronic Dis. 7(2).
    • Document Type:
      Journal Article
    • Name as Subject:
      Behavioral Risk Factor Surveillance System
    • Place as Subject:
      United States
    • Collection(s):
      Preventing Chronic Disease
    • Main Document Checksum:
    • File Type:

    Supporting Files

    More +

    You May Also Like

    Checkout today's featured content at stacks.cdc.gov