Nutrients, Vol. 18, Pages 977: Dietary Patterns, Cooking Methods, and Their Association with Prediabetes Risk Markers in Romanian University Students: A Cross-Sectional Analysis
Nutrients doi: 10.3390/nu18060977
Authors:
Teodora Piroș
Raluca Lupusoru
Lavinia Cristina Moleriu
Călin Muntean
Radu Dumitru Moleriu
Dora Mihalea Cîmpian
Mădălina Gabriela Cincu
Elena Gabriela Strete
Amalia Gabriela Timofte
Ruxandra-Cristina Marin
Background: Young adulthood represents a critical period for the emergence of early metabolic disturbances, potentially influenced by dietary shifts toward convenience and ultra-processed foods. However, evidence linking dietary patterns and cooking practices with objective metabolic biomarkers in Romanian university students remains limited. Methods: This cross-sectional study included 693 students aged 18–24 years at the Victor Babeș University of Medicine and Pharmacy, Romania (June–July 2025). Dietary habits, food preferences, and cooking practices were assessed using a structured online questionnaire, while anthropometric and biochemical data were obtained from university health records. The primary outcome was glycated hemoglobin (HbA1c), a marker of average blood glucose levels over the previous 2–3 months. Prediabetes was defined as HbA1c 5.7–6.4%. Dietary patterns were identified using k-means clustering based on fast-food consumption frequency, main meal of the day, fruit and vegetable intake frequency, and predominant cooking method. Multivariable regression models assessed associations between dietary variables and glycemic or lipid outcomes. Results: Prediabetes prevalence was 21.1% (diabetes: 1.4%). Three dietary patterns were identified: health-conscious (prediabetes 15.4%), mixed (20.0%), and fast-food oriented (27.3%; χ2 p = 0.003). Fast-food consumption frequency was independently associated with higher prediabetes risk (OR = 1.78 per category; 95% CI 1.38–2.30; p < 0.001) and higher HbA1c levels (β = 0.147; p < 0.001), while fruit and vegetable intake showed an inverse association with HbA1c (β = −0.109; p < 0.001). A dose–response relationship was observed between fast-food frequency and both HbA1c and prediabetes prevalence (p-trend < 0.001). An interaction between high-temperature cooking methods and frequent fast-food consumption was observed for HbA1c (p = 0.023). BMI and sex were the strongest predictors of lipid outcomes, although fast-food intake was associated with higher triglyceride levels (p = 0.034). Conclusions: Among Romanian university students, dietary patterns characterized by frequent fast-food consumption were associated with higher HbA1c levels and greater prediabetes prevalence. A high-temperature cooking method was associated with higher glycemic levels when combined with frequent fast-food intake. These findings suggest that early dietary behaviors during university years may be relevant for metabolic risk profiles in young adults.
Background: Young adulthood represents a critical period for the emergence of early metabolic disturbances, potentially influenced by dietary shifts toward convenience and ultra-processed foods. However, evidence linking dietary patterns and cooking practices with objective metabolic biomarkers in Romanian university students remains limited. Methods: This cross-sectional study included 693 students aged 18–24 years at the Victor Babeș University of Medicine and Pharmacy, Romania (June–July 2025). Dietary habits, food preferences, and cooking practices were assessed using a structured online questionnaire, while anthropometric and biochemical data were obtained from university health records. The primary outcome was glycated hemoglobin (HbA1c), a marker of average blood glucose levels over the previous 2–3 months. Prediabetes was defined as HbA1c 5.7–6.4%. Dietary patterns were identified using k-means clustering based on fast-food consumption frequency, main meal of the day, fruit and vegetable intake frequency, and predominant cooking method. Multivariable regression models assessed associations between dietary variables and glycemic or lipid outcomes. Results: Prediabetes prevalence was 21.1% (diabetes: 1.4%). Three dietary patterns were identified: health-conscious (prediabetes 15.4%), mixed (20.0%), and fast-food oriented (27.3%; χ2 p = 0.003). Fast-food consumption frequency was independently associated with higher prediabetes risk (OR = 1.78 per category; 95% CI 1.38–2.30; p < 0.001) and higher HbA1c levels (β = 0.147; p < 0.001), while fruit and vegetable intake showed an inverse association with HbA1c (β = −0.109; p < 0.001). A dose–response relationship was observed between fast-food frequency and both HbA1c and prediabetes prevalence (p-trend < 0.001). An interaction between high-temperature cooking methods and frequent fast-food consumption was observed for HbA1c (p = 0.023). BMI and sex were the strongest predictors of lipid outcomes, although fast-food intake was associated with higher triglyceride levels (p = 0.034). Conclusions: Among Romanian university students, dietary patterns characterized by frequent fast-food consumption were associated with higher HbA1c levels and greater prediabetes prevalence. A high-temperature cooking method was associated with higher glycemic levels when combined with frequent fast-food intake. These findings suggest that early dietary behaviors during university years may be relevant for metabolic risk profiles in young adults. Read More