Statistical method use in public health research

Scand J Public Health. 2015 Nov;43(7):776-82. doi: 10.1177/1403494815592735. Epub 2015 Jul 10.

Abstract

Aims: The content of public health research is often statistically complex. This review seeks to assess the breadth of statistical literacy required to understand this material, with a view to informing practitioners' statistical training.

Methods: We review the statistical content of original research articles published in 2011 in four major public health journals. Categories of statistical methodologies are identified and their frequency of use recorded. Methods' "usefulness" in terms of the extent to which their understanding increases accessibility to the literature is assessed.

Results: A total of 482 articles were reviewed and 30 categories of methods identified. Along with descriptive statistics (467 articles), regression analyses were also common, with logistic regression (206 articles) more than twice as prevalent as linear regression (95 articles). More complex regression models for use with clustered data were also commonly encountered, appearing in 96 articles.

Conclusions: The public health literature features a wide variety of statistical methods, some of which are advanced. To ensure the literature remains accessible, training for public health practitioners should include statistical training that maximizes breadth as well as depth of understanding.

Keywords: Public health; education; preventive medicine; statistics.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Biomedical Research / methods*
  • Humans
  • Public Health*
  • Research Design*
  • Statistics as Topic*