Probability of predicting dietary pattern adherence among primary schoolchildren based on socio-demographic data, anthropometric parameters, physical activity levels, and nutritional knowledge.
Drywień M, Czarniecka-Skubina E, et al. • Scientific reports • 2026
Three dietary patterns were identified among Polish schoolchildren (Salty-Sweet, Plant-Dairy, and Protein), with nutritional knowledge and physical activity emerging as the main modifiable determinants of dietary pattern adherence.
Key Findings
Results
Principal component analysis identified three distinct dietary patterns among Polish primary schoolchildren: Salty-Sweet, Plant-Dairy, and Protein.
PCA with varimax rotation was used to identify dietary patterns, with MSA = 0.796 indicating sampling adequacy
The study included 7,763 schoolchildren aged 10-12 from Polish schools (49.2% boys, 50.8% girls)
This was a cross-sectional study design using a validated questionnaire to assess nutritional knowledge, dietary habits, and physical activity
Results
Children classified as overweight according to the RFMp index and children who were very physically active showed less adherence to the Salty-Sweet Pattern.
The RFMp (relative fat mass percentile) index was used to classify overweight status
Very physically active children were less likely to be in the highest tertile of the Salty-Sweet Pattern
Logistic regression was used to model predictors of belonging to the highest tertile of each dietary pattern
Results
Underweight children (by BMI) and those with low nutritional knowledge were more likely to follow the Salty-Sweet Pattern.
BMI was used to classify underweight status in schoolchildren
Low nutritional knowledge was associated with greater adherence to the Salty-Sweet Pattern
Nutritional knowledge was assessed using a validated questionnaire
Results
Girls, children with elevated waist-to-height ratio (WHtR), and very physically active children were more likely to be in the highest tertile of the Plant-Dairy Pattern.
Sex (female) was a significant predictor of Plant-Dairy Pattern adherence
Elevated WHtR was associated with greater likelihood of belonging to the third tertile of the Plant-Dairy Pattern
Very physically active children showed greater adherence to the Plant-Dairy Pattern
Results
Low nutritional knowledge was associated with less adherence to the Plant-Dairy Pattern.
Children with low nutritional knowledge were less likely to be in the highest tertile of the Plant-Dairy Pattern
Nutritional knowledge was identified as a key modifiable determinant across multiple dietary patterns
The association was identified through logistic regression modeling
Results
Girls showed less adherence to the Protein Pattern, whereas underweight children and very physically active children showed greater adherence to it.
Female sex was negatively associated with the highest tertile of the Protein Pattern
Underweight classification (by BMI) was positively associated with Protein Pattern adherence
Very physical activity level was positively associated with Protein Pattern adherence
Conclusions
Nutritional knowledge and physical activity were identified as the main modifiable determinants of dietary pattern adherence in schoolchildren.
Low nutritional knowledge was consistently associated with worse dietary pattern adherence across patterns
Physical activity level influenced adherence to all three identified dietary patterns
The authors stated these factors 'can be utilised when developing strategies for regularly assessing nutritional status and providing specialist advice to schoolchildren, their families, and teachers'
Methods
Multiple anthropometric indices were calculated to assess body composition and adiposity in this sample of schoolchildren.
Standard anthropometric measurements included body weight, height, and waist circumference
Calculated indices included BMI, WHtR (waist-to-height ratio), RFMp (relative fat mass percentile), and TMI (tri-ponderal mass index)
Different indices yielded different classifications (e.g., overweight by RFMp vs. underweight by BMI) and were associated with different dietary pattern outcomes
What This Means
This research examined what factors predict which types of diets children aged 10-12 follow, using data from nearly 8,000 Polish schoolchildren. Researchers identified three main eating patterns: a 'Salty-Sweet' pattern (likely characterized by processed, snack-type foods), a 'Plant-Dairy' pattern (likely featuring fruits, vegetables, and dairy products), and a 'Protein' pattern. They then looked at whether factors like sex, body composition measures, physical activity levels, and nutrition knowledge could predict which pattern a child was most likely to follow.
The study found that girls were more likely to follow the Plant-Dairy pattern but less likely to follow the Protein pattern compared to boys. Children who were very physically active were less likely to follow the unhealthy Salty-Sweet pattern and more likely to follow the Plant-Dairy and Protein patterns. Interestingly, children classified as underweight by BMI were more likely to follow the Salty-Sweet pattern, suggesting that unhealthy eating may contribute to underweight as well as overweight. Across all patterns, children with low nutritional knowledge consistently showed worse dietary choices — they were more likely to eat a Salty-Sweet diet and less likely to follow a Plant-Dairy diet.
This research suggests that nutrition education and encouraging physical activity are the most actionable ways to improve children's eating habits, since these are factors that can be changed through intervention. The findings highlight that a one-size-fits-all approach may be insufficient — different groups of children (e.g., by sex or activity level) have different dietary tendencies that should inform how nutrition programs are designed for schools, families, and healthcare providers.
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Drywień M, Czarniecka-Skubina E, Hamułka J, Gębski J, Januszko O, Sadowska J, et al.. (2026). Probability of predicting dietary pattern adherence among primary schoolchildren based on socio-demographic data, anthropometric parameters, physical activity levels, and nutritional knowledge.. Scientific reports. https://doi.org/10.1038/s41598-026-70753-6