Exploratory dietary patterns: a systematic review of methods applied in pan-European studies and of validation studies.

Franziska Jannasch,Fiona Riordan,Matthias B Schulze,Lene F Andersen

doi:10.1017/s0007114518001800

Abstract

Besides a priori approaches, using previous knowledge about food characteristics, exploratory dietary pattern (DP) methods, using data at hand, are commonly applied. This systematic literature review aimed to identify exploratory methods on DP in pan-European studies and to inform the development of the DEterminants of DIet and Physical ACtivity (DEDIPAC) toolbox of methods suitable for use in future European studies. The search was conducted in three databases on prospective studies in healthy, free-living people across the whole life span. To identify validated DP methods, an additional search without regional restrictions was conducted. Studies including at least two European countries were retained. The search resulted in six pan-European studies applying principal component/factor analysis (PC/FA) (n 5) or cluster analysis (n 2). The criteria to retain PC/factors ranged from the application of the eigenvalue>1 criterion, the scree plot and/or the interpretability criterion. Furthermore, seven validation studies were identified: DP, derived by PC/FA (n 6) or reduced rank regression (RRR) (n 1) were compared using dietary information from FFQ (n 6) or dietary history (n 1) as study instrument and dietary records (n 6) or 24-h dietary recalls (n 1) as reference. The correlation coefficients for the derived DP ranged from modest to high. To conclude, PC/FA was predominantly applied using the eigenvalue criterion and scree plot to retain DP, but a better description of the applied criteria is highly recommended to enable a standardised application of the method. Research gaps were identified for the methods cluster analysis and RRR, as well as for validation studies on DP.

Highlights

As people naturally eat a combination of many different foods, the association between single dietary factors and chronic disease risk can be difficult to determine and interpret(1)
Examples for exploratory approaches are factor analysis and principal component analysis (PCA), which use the covariance matrix of the food groups to reduce the dimensionality from a high number of food groups to few patterns of food consumption(5)
Two exploratory dietary pattern approaches were identified in pan-European studies: PCA/factor analysis and cluster analysis

Summary

Introduction

As people naturally eat a combination of many different foods, the association between single dietary factors and chronic disease risk can be difficult to determine and interpret(1). While principal components are linear combinations of the observed variables, factors derived by factor analysis can be understood as latent constructs(6) Another exploratory approach is cluster analysis, which groups participants with similar dietary habits instead of correlated food groups(7). In the Framework of the Joint Programming Initiative ‘A Healthy Diet for a Healthy Life’ within the EU Committee, the DEterminants of DIet and Physical ACtivity (DEDIPAC) Knowledge Hub has been developed This was a European transdisciplinary research network programme, which aimed to realise a more effective promotion of healthy diets and physical activity. It aimed to identify state-of-the-art methods, enabling future cross-country interventions and policies(10) Within this framework, this systematic literature review aimed to identify and compare (validated, if possible) exploratory dietary pattern methods, which were conducted in panEuropean studies in order to deduce recommendations for such analyses in pan-European settings and beyond and to identify potential research gaps

Objectives

Methods

Results

Discussion

Conclusion