Capturing Changes in Dietary Patterns among Older Adults: A Latent Class Analysis of an Aging Irish Cohort

INTRODUCTION:  Analysis of dietary patterns is now an important tool for nutritional epidemiology, but data-driven, longitudinal analyses are still rare. We used latent class analysis (LCA) to identify sub-groups of people with similar dietary patterns, explore changes in dietary patterns over a 10 year period, and relate these dynamics to socio-demographic factors and health outcomes.   

METHODS:  Data are from Irish men and women enrolled in the Cork and Kerry Diabetes and Heart Disease Study. They were aged 50-69yr at baseline (1998; n=923) and followed-up 10-years later (2008; n=320). Diets were assessed with a standard FFQ. LCA, under the assumption of conditional independence, was used to identify mutually exclusive subgroups with different dietary patterns, based on food group consumption.

RESULTS:  Three dietary classes emerged. These were interpreted as '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 (non-significant).  

CONCLUSIONS: LCA is useful for exploring dietary patterns transitions.  Understanding the predictors of longitudinal stability/transitions in dietary patterns can help target public health initiatives by identifying subgroups most/least likely to change and those most/least likely to sustain a change.