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Problems in using age-stratum-specific reference rates for indirect standardization.

Y Yasui1, J Whitton

  • 1Cancer Prevention Research Program, Fred Hutchinson Cancer Research Center, Seattle, Washington 19024, USA.

Journal of Clinical Epidemiology
|June 9, 1999
PubMed
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Categorizing age in epidemiological studies can bias results. Using linear splines offers a simple solution to improve the accuracy of disease risk estimation and statistical inference in cohort studies.

Area of Science:

  • Epidemiology
  • Biostatistics
  • Statistical Modeling

Background:

  • Indirect standardization is commonly used to compare disease risk between a study cohort and a reference population.
  • This method adjusts for differences in age distribution, typically using 5-year age strata.

Purpose of the Study:

  • To discuss the problems associated with age categorization in epidemiological studies.
  • To propose a remedy for biased estimation and incorrect statistical inference in relative risk parameter analyses.

Main Methods:

  • The study discusses issues arising from the categorization of age in indirect standardization.
  • It extends the discussion to general analyses using Poisson regression.
  • A remedy using linear splines is proposed and illustrated with a hypothetical example.

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Main Results:

  • Categorical age adjustments in epidemiological studies can lead to biased estimation of relative risk.
  • Incorrect statistical inference on relative risk parameters can occur due to age categorization.
  • Linear splines provide a simple and effective method to mitigate these issues.

Conclusions:

  • Age categorization in epidemiological analyses, including indirect standardization and Poisson regression, introduces significant biases.
  • Implementing linear splines offers a straightforward solution to improve the accuracy of risk estimation and inference.