Oral Presentation 49th Nutrition Society of Australia Annual Scientific Meeting 2025

Diet quality is sub-optimal in masters distance runners (130046)

Alison M Hill 1 , Erin A Colebatch 1 , Joel T Fuller 2 , Evangeline Mantzioris 1
  1. Clinical & Health Sciences & Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, SA, Australia
  2. Department of Health Sciences, Macquarie University, NSW, Australia

Nutrition plays a critical role in athletic performance and recovery, with particular emphasis on adjusting macronutrient intake, especially carbohydrate and protein, to match the increased energy demands of training and competition(1). Athletes may rely on sports nutrition products to meet their increased carbohydrate and protein requirements due to the inherent convenience of these products. This behaviour may displace nutrient-dense whole foods and compromise overall diet quality. Higher-quality diets, rich in a variety of core food groups, are linked to improved health and reduced chronic disease risk(2) and may potentially enhance performance in athletes through better recovery and reduced injury risk. Notably, better diet quality is frequently linked to better nutrition knowledge(3). Despite these potential benefits, diet quality in older athletic populations has been infrequently evaluated. Therefore, the aim of this study was to describe and assess associations between diet quality and sports nutrition knowledge in masters distance runners (≥35 years, ≥ 30km/week). Dietary intake was captured via 3-day food-records (FoodWorks; Xyris Australia), with diet quality assessed using the Dietary Guideline Index (DGI)(4). Total DGI scores ranged from 0-120, with sub scores for consumption of core (0-70) and non-core foods (0-50). For all scores, a higher score reflects better diet quality. Sports nutrition knowledge was assessed using the Abridged Nutrition for Sport Knowledge Questionnaire (A-NSKQ, % correct). Differences in diet quality and nutrition knowledge between sexes were assessed using independent t-tests / Mann-Whitney U-tests as appropriate. Data are reported as mean ± standard deviation or median (interquartile range). Spearman rho (rs) evaluated associations between Total DGI and A-NSKQ scores. Participants were predominantly middle-aged (48.5 ± 8.2 years), of healthy weight (BMI 22.8 ± 2.8 kg/m2), and averaged 46.1 ± 18.2 km of running per week, with a near equal distribution of males and females (54:45). Diet quality scores were low with no difference between sexes for Total DGI (males 55.5 (22.2) vs. females 56.0 (39.1), p=0.694), core (males 37.8 (14.6) vs. females 38 (16.5), p=0.684) or non-core (males 10 (10) vs. females 10 (30), p=0.433) sub-scores. Participants tended to meet recommended serves of grains (50% meeting), but the majority failed to meet recommended serves of vegetables (15%), fruits (25%), protein foods (31%) or dairy and alternatives (19%). Only 28% met recommendations for discretionary foods. Most participants met alcohol guidelines (88%). Sports nutrition knowledge was on average “poor” with females scoring higher than males (55.5 ± 12.2 % vs 45.4 ± 13.5 % respectively, p<0.001). There was no relationship between Total DGI and A-NSKQ scores (rs= 0.160, P=0.113). These findings emphasise the importance of including diet quality when assessing dietary intake in athletes and suggest that older athletes may benefit from both general and sports-specific nutrition education.

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  2. Morze J et al. (2020) J Acad Nutr Diet 120(12), 1998-2031
  3. Janiczak A et al. (2022) British J Nutr 128(6), 1156-1169.
  4. Ward SJ, Coates AM, Hill AM (2019) Nutrients 11(6), 1286.
  5. Trakman GL et al (2018) J Int Soc Sports Nutr 15, 7.