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Related Experiment Videos

Model-based small area estimates of overweight prevalence using sample selection adjustment.

D Malec1, W W Davis, X Cao

  • 1U.S. Bureau of the Census, Statistical Research Division, room 3132-4, Washington, D.C. 20233, USA. donald.j.malec@ccmail.census.gov

Statistics in Medicine
|December 22, 1999
PubMed
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This study estimates adult overweight prevalence across U.S. states using a hierarchical model and NHANES III data. The model-based estimates showed excellent agreement with design-based estimates, offering reliable state-level overweight prevalence data.

Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Overweight prevalence is a significant public health concern.
  • Accurate state-level estimates are crucial for targeted interventions.
  • Existing survey data may require advanced modeling for precise geographic analysis.

Purpose of the Study:

  • To estimate adult overweight prevalence by U.S. state.
  • To utilize a hierarchical modeling approach for improved accuracy.
  • To validate model-based estimates against traditional methods.

Main Methods:

  • Employed a two-stage hierarchical model.
  • Adjusted for sample selection and accounted for geographic variability.
  • Utilized data from the Third National Health and Nutrition Examination Survey (NHANES III).

Related Experiment Videos

  • Compared model-based estimates with design-based and synthetic estimates.

    • Main Results:

    • Achieved excellent agreement between model-based and design-based estimates at the national level.
    • Validated the model's performance at the state level through comparisons.
    • Provided reliable state-specific overweight prevalence estimates.

    Conclusions:

    • Hierarchical modeling provides accurate and reliable estimates of overweight prevalence.
    • The model is effective in addressing geographic variability and sampling complexities.
    • This approach enhances the utility of national health surveys for state-level public health assessments.