Application of a Latent Transition Model to Estimate the Usual Prevalence of Dietary Patterns

Background: This study aims to derive habitual dietary patterns of the Portuguese adult population by applying two methodological approaches: a latent class model and a latent transition model. The novel application of the latent transition model allows us to determine the day-to-day variability of diet and to calculate the usual prevalence of dietary patterns. Methods: Participants are from the National Food, Nutrition and Physical Activity Survey of the Portuguese population, 2015–2016 (2029 women; 1820 men, aged ≥18 years). Diet was collected by two 24 h dietary recalls (8–15 days apart). Dietary patterns were derived by: (1) a latent class model using the arithmetic mean of food weigh intake, with concomitant variables (age and sex); (2) a latent transition model allowing the transition from one pattern to another, with the same concomitant variables. Results: Six dietary patterns were identified by a latent class model. By using a latent transition model, three dietary patterns were identified: “In-transition to Western” (higher red meat and alcohol intake; followed by middle-aged men), “Western” (higher meats/eggs and energy-dense foods intake; followed by younger men), and “Traditional-Healthier” (higher intake of fruit, vegetables and fish, characteristic of older women). Most individuals followed the same pattern on both days, but around 26% transited between “In-transition to Western” and “Western”. The prevalence of the dietary patterns using a single recall day (40%, 27%, 33%, respectively) is different from the usual prevalence obtained by the latent transition probabilities (48%, 36%, 16%). Conclusion: Three dietary patterns, largely dependent on age and sex, were identified for the Portuguese adult population: “In-transition to Western” (48%), “Western” (36%), and “Traditional-Healthier” (16%), but 26% were transient between patterns. Dietary patterns are, in general, deviating from traditional habits.This Survey has received funding from the EEA Grants Program, Public Health Initiatives (PT06-000088SI3). Andreia Oliveira receives funds from FEDER, the Operational Programme Factors of Competitiveness—COMPETE and through national funding from the Foundation for Science and Technology—FCT (Portuguese Ministry of Education and Science) (IF/01350/2015—Andreia Oliveira)