P171 - MEAL PATTERNS IN AUTISM SPECTRUM DISORDER

P171

MEAL PATTERNS IN AUTISM SPECTRUM DISORDER

K. Castro^1,*, L. Hoffmann¹, E. Silva¹, L. Roman¹, S. Valle¹, J. Vaz¹

¹Programa de Pós-Graduação em Nutrição e Alimentos, Universidade Federal de Pelotas, Pelotas, Brazil

Rationale: Evaluating dietary patterns at meals allows the identification of irregularities in feeding habits and food-nutrient interactions. Research on Autism Spectrum Disorder (ASD) often examines specific dietary aspects, rather than a comprehensive analysis. Thus, this cross-sectional study aimed to characterize meal patterns in children and adolescents with ASD. 

Methods: Data were collected from the Protocol for Nutritional Care in Autism study (Ethical approval CAEE: 94253518.0.0000.5317), including individuals aged 2 to <19 years with non-syndromic ASD. Sociodemographic data were gathered via standard questionnaire, and dietary intake was assessed using three non-consecutive 24-hour food recalls. Principal component analysis was applied to derive dietary patterns for each meal, using food group intakes (g/day).

Results: A total of 361 individuals were included (mean age: 7.3 years; 80.1% male). Two breakfast patterns were defined: BP1 (bread, fat spreads, sugar and coffee) and BP2 (bread, fat spreads, sweets, biscuits and dairy). Lunch patterns included LP1 (rice, red/processed meat, pasta and soda); LP2 (white meat, rice, vegetables, roots/tubers and beverages); and LP3 (processed meat and roots/tubers). Snack patterns consisted of SP1 (sugar, bread, coffee and fat spreads); SP2 (sweets, soda, snacks and chips); and SP3 (sugar, coffee, cake and snacks). Dinner patterns included DP1 (rice, beans, red/white meat, vegetables, roots/tubers and soda); DP2 (beans, processed meat, pasta, vegetables and soda); and DP3 (soda, red/processed meat and vegetables). Adherence to most patterns was higher in older children, and varied by ethnicity, family income, antipsychotic use and anthropometric status.

Conclusion: These findings highlight the association of dietary intake, cultural and sociodemographic aspects. Given the influence of meal composition on overall health, understanding meal-specific patterns can guide targeted nutritional interventions for this population.

Disclosure of Interest: None declared