PD960 - EXPLORING POTENTIAL BIOMARKERS MEDIATING RELATIONSHIPS BETWEEN BODY COMPOSITION, APPETITE AND ENERGY INTAKE IN OLDER ADULTS

PD960

EXPLORING POTENTIAL BIOMARKERS MEDIATING RELATIONSHIPS BETWEEN BODY COMPOSITION, APPETITE AND ENERGY INTAKE IN OLDER ADULTS

A. Quinn^1,2,3,*, C. Corish^1,2, B. Mullen^1,2,3,4, F. Gonnelli⁵, M. Bozzato⁵, P. Scheufele⁶, D. Dardevet⁷, G. De Vito⁵, M. Visser⁸, D. Volkert⁶, H. Roche^1,2,4,9, K. Horner^1,2,3

¹School of Public Health, Physiotherapy and Sport Science, University College Dublin, ²Institute for Food and Health, University College Dublin, ³Institute for Sport and Health, University College Dublin, ⁴Nutrigenomics Research Group, UCD Conway Institute, University College Dublin, Dublin, Ireland, ⁵Department of Biomedical Sciences, University of Padova, Padova, Italy, ⁶Institute for Biomedicine of Ageing, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nuremberg, Germany, ⁷Université Clermont Auvergne, INRAE, UNH, Clermont-Ferrand, France, ⁸Department of Health Sciences, Faculty of Science, and the Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands, ⁹Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, Belfast, United Kingdom

Rationale: Ageing is associated with body composition changes (increased adiposity and decreased fat-free mass (FFM)) alongside reduced appetite and energy intake (EI). To better understand reduced appetite with ageing, this cross-sectional analysis examined the potential role of gut, inflammatory and metabolic biomarkers in mediating relationships of body composition with appetite and EI in older adults.

Methods: 163 community-dwelling older adults (72.5±6.1y, 110F, BMI 25.2±2.9kg/m²) from three European sites in the APPETITE study were included. Body composition (fat mass (FM)(kg), FM (%), FM index (FMI), FFM (kg), FFM index) was assessed by bioelectrical impedance. Appetite was assessed via Simplified Nutritional Appetite Questionnaire (SNAQ) and visual analogue scales (VAS) and EI by test meal and 3-day food diary. Fasting biomarkers included glucose, insulin, HOMA-IR, CRP, leptin, ghrelin, Glucagon-like Peptide-1 (GLP-1) and Peptide YY (PYY) with postprandial measures available at one site. Associations were examined using generalised linear models adjusted for age, sex, centre and physical activity. Mediation analyses examined direct and indirect associations.

Results: FM variables (FM (kg), FM%, FMI) were associated with fasting leptin, CRP, insulin and HOMA-IR (β=0.11-0.90, all p<0.05) and FM% and FMI with fasting glucose (β=0.70-1.49, all p<0.05). FFM was not associated with the biomarkers investigated, except for leptin (β=0.11, p=0.01). Mediation analyses demonstrated that higher FM was indirectly associated with lower appetite and/or EI via higher CRP, HOMA-IR, and glucose (β=-0.04 to -0.09, all p<0.05), with no direct associations observed (p≥0.17).

Conclusion: Findings suggest that higher FM in older adults is associated with lower appetite and EI indirectly via metabolic pathways and markers of inflammation and may assist in informing strategies to combat undernutrition.

Disclosure of Interest: None declared