Author(s): DHOE, B., VANDECAUTER, J., LIEVENS, E., DERAVE, W., Institution: GHENT UNIVERSITY, Country: BELGIUM, Abstract-ID: 2242

INTRODUCTION:
Creatine research has reached unprecedented levels. Yet, most studies focus on supplemental dosages (g/day) targeting muscle performance, hypertrophy, or cognitive function. In contrast, dietary creatine intake varies substantially between individuals, and its relationship with muscle function remains unclear due to inconsistent quantification and limited representation in food composition databases. Bridging this gap is essential to strengthen the “food-first” approach, which promotes the consumption of nutrient-dense whole foods. We therefore aimed to develop a food-to-creatine conversion database and used it to calibrate dietary creatine intake from food frequency questionnaires (FFQs) and repeated 24-h recalls in the UK Biobank (UKB), the world’s largest deeply phenotyped population resource, and examined its associations with muscle phenotypical whole-body fat-free mass (FFM) and strength.
METHODS:
A food-to-creatine conversion database was developed by compiling published values for creatine content across relevant foods and standardizing portion-specific concentrations according to the UKB classification. This database was used to estimate habitual daily creatine intake in UKB participants with both FFQ data and at least two 24-h dietary recalls (n=123,256). A regression model was fitted between log-transformed recall-based and FFQ-derived creatine intake and subsequently applied to all participants with FFQ data (n=478,594) to obtain calibrated intake estimates. Associations between creatine intake and FFM, measured by bioelectrical impedance analysis, and handgrip strength were assessed using linear regression models adjusted for relevant covariates (e.g., age), genetic principal components, protein and energy intake, with nested ANOVA used for model comparison.
RESULTS:
Aggregating the creatine literature enabled quantification of creatine content in muscle-derived foods, with negligible levels in cheese. Meat and fish contain on average 4.4g creatine/kg wet weight (≈0.51g/portion). Calibration of FFQ-derived intake against the log-transformed mean of at least two 24-h recalls produced a regression slope of 0.59, indicating that FFQ overestimates true creatine intake. Applying this calibration to the full FFQ cohort yielded a daily creatine intake range of 0–1.8g/day, with both median and mean intakes of 0.5g/day. After correcting for protein and energy intake, creatine intake is a significant negative predictor for FFM and handgrip strength (p=2.64e-15 and p=0.00042, respectively).
CONCLUSION:
Using a newly developed food-to-creatine conversion database, we calculated habitual dietary creatine intake in nearly 500,000 UKB participants, adjusting for empirically derived FFQ bias. We demonstrated an independent inverse association between dietary creatine intake and both FFM and muscle strength. These findings suggest that the benefits of dietary creatine intake for muscle-related phenotypes at the population level may largely reflect underlying protein and energy intake.