PD636 - DIET–ADIPOKINE ASSOCIATIONS IN INDIVIDUALS WITH METABOLIC RISK FACTORS

PD636

DIET–ADIPOKINE ASSOCIATIONS IN INDIVIDUALS WITH METABOLIC RISK FACTORS

S. Ivanova^1,*, A. Fedulovs¹, S. Plavina², N. Paramonova², P. J. Giraudi³, M. M. Milito³, Z. Smite⁴, G. Bilande¹, M. Arisova¹, J. Sokolovska¹

¹Department of Clinical and Personalized Medicine, ²Department of Pharmaceutical Sciences, University of Latvia, Riga, Latvia, ³The Italian Liver Foundation NPO (FIF), Trieste, Italy, ⁴Department of Public Health and Healthcare, University of Latvia, Riga, Latvia

Rationale: Diet is a modifiable factor that may influence leptin and adiponectin levels involved in metabolic regulation. Exploring these associations may support the development of more personalized approaches to metabolic disease prevention. 

Methods: Adults with normal glucose metabolism (fasting glucose <5.6 mmol/L, HbA1c <5.7%) and BMI 25.0-34.9 kg/m² were included. Participants completed a 3-day food diary and a Food Frequency Questionnaire (FFQ), and blood samples were collected. Plasma adipokine concentrations were determined using ELISA. Spearman’s rank correlation was performed, followed by linear regression analysis. FFQ-derived variables were log-transformed prior to inclusion in linear regression models. A p-value <0.05 was considered statistically significant.

Results: A total of 70 participants (median age 35.0 years, 27% male) were included. Their median BMI was 28.47 kg/m², waist circumference 92.0 cm, leptin 3.94 ng/mL, adiponectin 8.39 µg/mL, and adiponectin/leptin ratio 2.42. Intake of milk and milk products showed positive correlation with leptin levels (rs = 0.34, p = 0.004), but negative with adiponectin/leptin ratio (rs = -0.32, p = 0.007). Carbohydrate and fiber intake negatively correlated with leptin levels (rs = -0.26, p = 0.033; rs = -0.29, p = 0.015, respectively). Adiponectin positively correlated with fruits and berries, coffee and tea, confectionery, and supplement use (rs = 0.27–0.32, p < 0.05). However, none of the associations between dietary factors and adipokines remained statistically significant after adjustment for age, BMI, waist circumference, and sex in linear regression models.

Conclusion: This exploratory study observed initial correlations between dietary factors and adipokines, but associations were not statistically significant in adjusted analyses.

References: Project "PHYSICS INFORMED MACHINE LEARNING-BASED PREDICTION AND REVERSION OF IMPAIRED FASTING GLUCOSE MANAGEMENT (PRAESIIDIUM)", Nr. 101095672.

Disclosure of Interest: None declared