Abstract
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).
Conclusions:
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.