Conference Contribution Details
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JM Harrington, DL Dahly, MS Gilthorpe, AP Fitzgerald, IJ Perry
International Society for Behaviour, Nutrition and Physical Activity
Capturing changes in dietary patterns among older adults: A latent class analysis of an aging Irish cohort
Ghent, Belgium
Oral Presentation
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Purpose: Data driven approaches to dietary patterns are underutilized, particularly, Latent Class Analysis models have been rarely used.  This study aimed to explore the applicability of LCA methods to classify diet patterns to determine long term diet stability. 

Methods: Cross sectional and longitudinal analyses from the 1998 baseline and 2008 follow up waves of the Cork and Kerry Diabetes and Heart Disease Study. Participant diets were surveyed with a standard FFQ. Latent class analysis was used to identify mutually exclusive subgroups with different dietary patterns.

Setting: General population in the Republic of Ireland

Subjects: 923 Men and women aged 50-69yr at baseline (n=923) and at 10-year follow up (n=320)

Results: Three dietary classes emerged: Western, Healthy and Low Energy.  Significant differences in demographic, lifestyle and health outcomes were associated with class membership. Between baseline and follow-up most people remained ‘stable’ in their dietary class.  Most of those who changed class moved to the healthy class. Higher education was associated with transition to a healthy diet; lower education was associated with stability in an unhealthy pattern. Transition to a healthy diet was associated with higher CVD risk factors at baseline: respondents were, significantly more likely to be smokers, centrally obese and to have hypertension (though non-significant). 


Latent Class Models are useful to explore dietary patterns and diet transitions.  Understanding the predictors of longitudinal stability/transitions in dietary patterns will assist with targeting public health initiatives by identifying subgroups most/least likely to change and those most/least likely to sustain a change.