ReviewA primer on the use of cluster analysis or factor analysis to assess co-occurrence of risk behaviors

- The use of cluster and factor analysis in multiple behavior research is clarified.
- Cluster analysis classifies individuals showing the same behaviors into clusters.
- Factor analysis summarizes interrelated behaviors into latent constructs.
- Choice between techniques has different implications for inferences and policy.
- A systematic approach is suggested to improve effectiveness of interventions.

ObjectiveThe aim of this paper is to provide a guideline to a universal understanding of the analysis of co-occurrence of risk behaviors. The use of cluster analysis and factor analysis was clarified.MethodA theoretical introduction to cluster analysis and factor analysis and examples from literature were provided. A representative sample (N = 4395) of the Dutch population, aged 16-40 and participating from fall 2005 to spring 2006, was used to illustrate the use of both techniques in assessing the co-occurrence of risk behaviors.ResultsWhereas cluster analysis techniques serve to focus on particular clusters of individuals showing the same behavioral pattern, factor analysis techniques are used to assess possible groups of interrelated health-risk behaviors that can be explained by an unknown common source. Choice between the techniques partly depends on the research question and the aim of the research, and has different implications for inferences and policy.ConclusionBy integrating theory and results from an illustrative example, a guideline has been provided that contributes towards a systematic approach in the assessment of co-occurrence of risk behaviors. Following this guideline, a better comparison between outcomes from various studies is expected, leading to improved effectiveness of multiple behavior change interventions.