Harmonisation potential

All of the original eight CLOSER studies have some form of diet-related questions; however the dietary assessment method used and the number of repeat assessments over time varied greatly between the studies. This heterogeneity will make it difficult to create harmonised dietary variables to apply to cross-cohort analyses.

Harmonisation aims to create comparable measures from various types of data across different studies. Harmonisation involves converting variables that capture the same latent construct across studies into a common format and it can be approached in different ways. Maelstrom Research developed guidelines for retrospective data harmonisation that can be found on their website.

The DAPA toolkit described elsewhere in this guide also provides harmonisation principles from a dietary perspective with these general steps

1. Define the target variable;
2. Assess harmonisation potential;
3. Derive common format data.

This section of the guide outlines these steps using the harmonisation of fish intake across 12 studies as an exemplar.