Creatine and Cognition in Aging: A Systematic Review of Evidence in Older Adults

Abstract

Context

Creatine is a well-studied dietary supplement that is known to benefit aging muscle and bone, especially when combined with resistance training. Some studies suggest that creatine may also be favorable for cognitive function, yet these independent effects have not been thoroughly reviewed in older adults.

Objective

The objective of this study was to systematically examine the current literature on creatine and cognition in older adults.

Data Sources

A comprehensive search was conducted across eight electronic databases.

Data Extraction

Original peer-reviewed studies investigating creatine supplementation and/or estimations of dietary creatine intake in older adults (aged 55+ years) with cognition assessed as an outcome were included. Studies not examining creatine and cognition exclusively, only in combination with another intervention (e.g., resistance training), were excluded. The methodological quality of each study was evaluated using a modified version of the Downs and Black (1998) checklist.

Data Analysis

Six studies were included, with a total of 1542 participants (55.7% female). Most participant samples included healthy community-dwelling older adults, with the exception of one study examining overweight older women. Two studies were double-blind interventions in which participants were supplemented with creatine monohydrate. Four studies were cross-sectional and estimated creatine consumption through dietary recall. Five of the six (83.3%) studies reported a positive relationship between creatine and cognition in older adults, particularly in the domains of memory and attention. One study achieved a methodological quality rating of “good”, two “fair”, and three “poor”.

Conclusion

The current limited evidence suggests that creatine may be associated with benefits for cognition in generally healthy older adults. However, high-quality clinical trials are warranted to further validate this relationship. Future research should investigate creatine supplementation in older clinical populations with notable cognitive deficits, objectively measure creatine concentrations, and consider additional factors that may influence creatine levels in the body and brain (e.g., body weight, muscle mass, dietary intake, physical activity levels).

Systematic Review Registration

PROSPERO No. CRD42025643617

INTRODUCTION

The proportion of the world’s population over 60 years is projected to double from 12% to 22% by 2050.¹ Aging is known to be associated with various declines in physical and cognitive function. Decreases in muscle mass, reductions in bone density, and physiological changes impacting organ function all underscore the aging process and increase the risk for falls and fractures.² Cognitive abilities, such as attention, memory, executive function, language, and visuospatial abilities also exhibit quantifiable declines with age.³ By approximately 70 years of age on average, it is estimated that ⅔ of Americans experience some form of cognitive impairment, with disadvantaged subgroups (e.g., less educated, racial/ethnic minorities) being at greater risk for younger age of onset and more years of impairment.⁴

Actively maintaining muscle mass is essential for reducing sarcopenia, frailty, and cognitive decline in older adults. Sarcopenia is defined as the loss of muscle mass, strength, and function with age and contributes to frailty—increased vulnerability to everyday stressors.⁵ Sarcopenia and frailty are known to be associated with adverse physical health outcomes, including higher risk of falls, fractures, and disability.⁶ Regarding cognitive health outcomes, a study with over 8000 older adults demonstrated longitudinal associations between low muscle mass and accelerated cognitive decline, specifically in executive functioning.⁷ Arosio and colleagues⁸ highlight the muscle–brain axis as a key link between muscle health and cognition, emphasizing the roles of metabolic dysregulation and neuromuscular junction deterioration with age, for example.

Resistance training (RT) is one established intervention to combat age-related declines in muscle, bone, and cognitive function. RT has consistently been shown to increase muscle fiber area and quality, improve bone density, and decrease fall and fracture risk.^9–12 Moreover, previous literature has suggested that RT is beneficial for cognitive function and overall brain health in older adults.^13,14 However, it is estimated that less than 15% of adults over 65 years in America meet the recommended physical activity guidelines.¹⁵ This statistic is concerning, considering the strong evidence to support physical activity as an effective health behavior for promoting wholesome aging.

Creatine is a well-researched dietary substance required for energy metabolism in the human body that is often taken as a supplement by individuals who engage in high-intensity activities, such as RT, with the goal of building muscle mass and strength. Creatine is naturally produced and synthesized in the kidney and liver and consumed exogenously through dairy products, meat, fish, and mollusks.^16,17 A typical omnivorous diet supplies approximately 1–2 g of creatine daily, lacto–ovo vegetarians consume around 0.03 g/day, and vegans consume next to no creatine through their diet.^18–20 Creatine is plentiful in organs with high energy demands, such as skeletal muscle and brain tissue.¹⁷ In muscle, for instance, creatine acts as a critical energy substrate for muscle contraction by facilitating the rapid regeneration of adenosine triphosphate (ATP) through a reversible reaction catalyzed by phosphocreatine (PCr) kinase.¹⁶ Notably, creatine levels in the body tend to decline with age, likely due to factors including less dietary intake, decreased functioning of organs responsible for creatine production, increased levels of physical inactivity, and decreased muscle mass (for supporting ample creatine storage).²¹

Previous research has shown that dietary creatine supplementation is associated with a reduction in the effects of aging on muscle and bone in older adults, especially when combined with RT.^22,23 Although there has been extensive research on creatine’s effects on physical function in both healthy and clinical populations,^24–26 the impact of creatine on cognition and brain health remains less well established. While there is evidence that creatine crosses the blood–brain barrier via the creatine transporter,²⁷ most creatine in the body is known to be stored in skeletal muscle, with only approximately 5% stored in the brain. This means that larger doses of creatine may be necessary to cross the blood–brain barrier and increase brain creatine levels.^21,28,29 Hence, the mechanisms by which creatine affects physical and cognitive function are distinct and should be studied separately. It is also known that creatine metabolism is implicated in cognitive functioning, as seen in those diseases resulting from the inability to synthesize or transport creatine (such as creatine deficiency syndrome, which is associated with cognitive impairments^23,30–32). Additionally, the presence of a brain-specific isoform of creatine kinase suggests that creatine plays a crucial role in energy supply and homeostasis within the central nervous system.^33–36

Recent reviews on creatine and cognition^23,37–39 have examined studies across a wide range of ages, with few focusing on the older adult population specifically. Moreover, previous reviews lack the inclusion of certain study designs and participant groups (e.g., observational studies, clinical populations), focus on specific domains of cognition (e.g., memory), and include studies where creatine is exclusively examined in conjunction with another intervention (e.g., RT), making it difficult to discern the individual effects of creatine. Therefore, the objectives of this systematic review are to: (1) compile all original peer-reviewed research studies on creatine and cognition in older adults, and (2) identify gaps in the current body of literature and suggest avenues for future research investigation. The research question guiding this review was: “What does the current literature suggest about the relationship between creatine and cognition in older adults?”

METHODS

Research Process and Registration

A comprehensive search of multiple electronic databases was performed to identify relevant articles. The selected articles were then screened in two stages based on predefined inclusion and exclusion criteria. Data from the selected articles were extracted and summarized in an Excel spreadsheet file. Following this, the quality of the included studies was evaluated using a validated tool. Finally, the results were synthesized narratively and disclosed through this review.

The protocol for this systematic review was registered on PROSPERO [CRD42025643617] prior to data extraction. All steps of this research were conducted in accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.⁴⁰ The completed PRISMA checklist can be found in the Supplementary Material, Appendix A.

Data Sources and Search Strategy

Between June 27 and July 2, 2024, a comprehensive search was conducted across eight electronic databases: (1) Medline (via OVID), (2) CINAHL (via EBSCOhost), (3) PsychINFO (via OVID), (4) EMBASE (via OVID), (5) PubMed (via NCBI), (6) Scopus, (7) the Cochrane Library, and (8) Web of Science. The main concepts of “older adults,” “creatine,” and “cognition” were combined with Medical Subject Headings (MeSH) terms, keywords, and truncated terms using the Boolean operators of “AND” and “OR” to form database-specific search strings (see Supplementary Material, Appendix B). The search strategies were tailored to the syntax and requirements of each database to ensure comprehensive coverage.

Article Screening and Selection

All search results were exported to Covidence via RIS files, where duplicate articles were automatically removed by the software. The article screening and selection process was conducted by four authors (S.M., J.W., A.K., and L.B.). Before commencing, the authors met to review the predefined inclusion and exclusion criteria to ensure consistency and familiarity with their application during the screening stages.

The screening process was conducted in two stages. First, article titles and abstracts were reviewed and voted upon independently by two authors. Qualified articles progressed onto full-text screening, where two authors again voted independently on the eligibility of each article. Any disagreements regarding inclusion were resolved through consultation with a third author who was not involved in the initial voting. A manual search of key author publications and references from included articles was conducted thereafter to retrieve any additional relevant literature. Criteria for the inclusion and exclusion of studies are presented in Table 1.

Table 1.

Criteria for Inclusion and Exclusion of Studies

Parameter	Inclusion criteria	Exclusion criteria
Population	All older adult populations aged 55+ years	Nonhuman populations
Intervention/Exposure	Dietary intake or supplementation of creatine	Other interventions/exposures examined in conjunction with creatine (e.g., strength training) exclusively, making the individual effects of creatine unable to be discerned
Comparator	The inclusion/exclusion of studies was not limited by the presence/absence of a comparison group.
Outcomes	At least one assessment of cognition (e.g., memory, attention, executive function)	No assessment of cognition
Study design	All original peer-reviewed studies with any study design published in English with full-text available	Reviews, protocols, books, conference proceedings, PhD theses, commentaries, editorials, gray literature

Data Extraction and Synthesis

An Excel spreadsheet was created to extract and summarize the relevant information from articles included in this review. Extracted information included article characteristics [i.e., author(s) and publication year], population characteristics (i.e., sample size and age), methods [i.e., study design, measure(s) of cognition, creatine supplementation or dietary recall details], and main findings. Three authors completed all extractions (J.W., A.K., L.B.), which were subsequently checked and confirmed by S.M. All extractions were conducted under the supervision of the senior author (L.S.N.).

Appraisal of Study Quality

The methodological quality of each included study was assessed using a modified version of the Downs and Black checklist⁴¹—similar to the modified checklist detailed by van Raath and colleagues.⁴² All questions were considered applicable for intervention studies and were scored out of a maximum of 28 points, where a higher score indicated better quality. Conversely, the following questions were considered not applicable for observational studies: 4, 8, 13–15, 19, 23, and 24. Therefore, these studies were scored out of a maximum of 20 points. Question 27 was answered as yes/no/unable to determine. Quality classifications were assigned as follows: excellent (26–28), good (20–25), fair (15–19) and poor (≤14).^43,44 Three authors (J.W., A.K., and L.B.) completed the quality assessment questionnaire independently for each study. A fourth author (S.M.) was present during the discussion meeting to resolve any disagreements.

RESULTS

Number of Studies

A total of six articles were included in this review (Table 2).^45–50 The initial search identified 2897 articles of interest, from which 961 duplicates were removed before screening. Based on title and abstract screening, 1837 articles were deemed irrelevant and 98 full texts were further screened for eligibility. One full-text article could not be obtained. From key author, key article, and reference searching, 11 further articles of interest were identified, but none of these met all criteria for inclusion in this review. Thus, six articles were identified and included from the initial search. Please see Figure 1 for a visual summary of the screening process.

Table 2.

Description and Characteristics of Included Studies

Reference	Study design	Study sample	Creatine protocol	Cognitive task(s) and outcome(s)	Positive effect of creatine on cognition?
Alves et al (2013)45	Randomized controlled trial	N = 56 60–80 y M = 66.8 y 100% F	1. Supplemented 4 × 5 g/d (5 d) followed by 5 g/d (24 wks) 2. Dietary recall	1. Mini Mental State Examination, cognitive function/impairment 2. Stroop Test, selective attention, and interference 3. Trail-Making Test Part A, executive functions and motor control 4. Digit Span Test, short-term memory 5. Delayed Recall Test, memory recall	No
Machado et al (2022)47	Cross-sectional	N = 27 67.4–71.1 y 100% F	Dietary recall	Eriksen Flanker Task, selective attention and interference	Yes
Machado et al (2023)46	Cross-sectional	N = 45 67.2–70.4 y 76% F	Dietary recall	1. Mini Mental State Examination, cognitive function/impairment 2. Eriksen Flanker Task, selective attention and interference	Yes
McMorris et al (2007)49	Intervention	N = 32 76.4 ± 8.4 y 50% F	Supplemented 4 × 5 g/d (1 wk)	1. Random Number Generation Task, executive function 2. Number Recall Test (forward and backward), short-term and working memory 3. Spatial Recall Test (forward and backward), visuospatial working memory 4. Long-Term Memory Test, long-term memory	Yes
Oliveira et al (2023)48	Cross-sectional	N = 42 67.2–70.6 y 76% F	Dietary recall	1. Mini Mental State Examination, cognitive function/impairment 2. Corsi Block-Tapping Task (forward and backward), visuospatial short-term memory	Yes
Ostojic et al (2021)50	Cross-sectional	N = 1340 71.4 ± 7.8 y 52% F	Dietary recall	1. WAIS III Digit Symbol Substitution Test, cognitive function/impairment	Yes

F, female; M, mean.

Figure 1.

PRISMA Flow Diagram

Article and Participant Characteristics

The included articles were published between 2007 and 2023. Four out of the six (66.7%) studies have authors affiliated with Brazil, ⅙ (16.7%) with the United States, ⅙ (16.7%) with New Zealand, ⅙ (16.7%) with the United Kingdom, ⅙ (16.7%) with Poland, ⅙ (16.7%) with Canada, and ⅙ (16.7%) with Serbia. There was a total of 1542 participants (55.7% female) across the studies, with sample size ranging from 27 to 1340 participants. Two studies (33.3%) exclusively recruited older women,^45,47 and the remaining studies (66.7%) examined community-dwelling older adults.^46,48–50 The mean age of participants within the six studies ranged from 66.8 to 76.4 years. Ethnicity was only reported in one of the six included studies, where the participants disproportionately identified as Non-Hispanic white (63.7%).⁵⁰

Study Design and Outcomes

Two (33.3%) studies conducted double-blinded interventions,^45,49 one of which was a randomized controlled trial (RCT)⁴⁵; in both intervention studies, participants were supplemented with creatine monohydrate. The other four studies (66.6%) were cross-sectional, examining the relationship between creatine and cognition using dietary recall.^46–48,50 Alves et al⁴⁵ randomly assigned participants into one of four groups: (1) placebo, (2) creatine supplementation, (3) placebo with strength training, or (4) creatine supplementation with strength training. Creatine supplementation groups received 4 × 5 g/day for five days followed by 5 g/day for 24 weeks. The placebo group received 4 × 5 g/day of dextrose for five days followed by 5 g/day for the remainder of the trial. Comparatively, McMorris et al⁴⁹ divided participants into two groups: (1) two-week placebo, and (2) one-week placebo, followed by one week creatine. The placebo group ingested a carbohydrate energy supplement 4 × 5g/day, and the creatine group consumed 4 × 5g/day of the carbohydrate energy supplement for one week followed by 4 × 5 g/day of creatine for the second week.

Of the four dietary recall studies included, three utilized a five-day dietary recall survey to estimate daily creatine intake,^46–48 applying the methodology described by Balsom and colleagues.⁵¹ The remaining study by Ostojic et al⁵⁰ employed a 24-hour, in-person dietary recall interview (midnight-to-midnight). All four studies grouped participants into cohorts based on estimated creatine intake and assessed cognitive task performance across these cohorts. There was notable variability in how creatine intake thresholds were defined across the studies. For instance, some studies categorized participants into high- vs low-intake groups using a threshold of 1.0 g/day,^46,47 while others used 0.382 g/day as the cut-off.⁴⁸ In contrast, Ostojic et al⁵⁰ stratified participants into quartiles: 0.00–0.40 g/day (1st quartile; mean ± SD = 0.13 ± 0.14 g), 0.41–0.94 g (2nd quartile; 0.68 ± 0.15 g), 0.95–1.57 g (3rd quartile; 1.21 ± 0.18 g), and 1.58–10.83 g (4th quartile; 2.45 ± 0.99 g).

Four (66.6%) studies measured general cognitive function/impairment using the Mini Mental State Examination^44,46,48 or the WAIS III Digit Symbol Substitution Test.⁴⁹ Three (50%) studies assessed selective attention and interference using the Eriksen Flanker Task^45,46 or Stroop task.⁴⁴ Executive function was examined as an outcome in 2 (33.3%) studies^44,47 and memory in three (50%) studies.^44,47,48

Creatine and Cognition Findings

Five of six (83.3%) studies reported a positive effect of creatine on cognition,^46–50 including all four of the cross-sectional studies. Two studies found that the higher creatine intake groups responded faster and more accurately in the incongruent conditions of the Eriksen Flanker Task.^46,47 Oliveira and colleagues⁴⁸ found that dietary creatine intake is positively associated with visuospatial short-term memory, where participants consuming greater than the median of 0.382 g/day displayed significantly higher forward and backward Corsi scores. Further, Ostojic et al⁵⁰ reported a significant positive correlation between creatine intake and Digit Symbol Substitution Test scores, with participants consuming more than 0.95 g/day displaying higher scores. For the intervention studies, McMorris et al⁴⁹ reported a positive effect of creatine supplementation on forwards number recall, spatial recall (both forwards and backwards), and long-term memory, but not random number generation or backwards number recall. Only one study, the RCT by Alves and colleagues,⁴⁵ reported no effect of creatine supplementation on cognitive function. Notably, none of the studies that examined global cognition using the Mini Mental State Examination reported an association^46,48 or change⁴⁵ with creatine supplementation.

Quality Assessment

Table 3 ^{41 , 45–50} presents the results of the quality assessment for each study included in the review. The overall methodological quality of the included studies was as follows: one study achieved “good” quality,⁴⁵ two “fair” quality,^49,50 and three “poor” quality.^46–48 No studies achieved an “excellent” quality classification.

Table 3.

Quality Assessment of Each Included Study Using a Modified Version of the Downs and Black (1998) Checklist⁴¹

	Alves et al 2013 45	Machado et al 2022 47	Machado et al 2023 46	McMorris et al 2007 49	Oliveira et al 2023 48	Ostojic et al 2021 50
Reporting
1. Is the hypothesis/aim/objective of the study clearly described?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
2. Are the main outcomes to be measured clearly described in the Introduction or Methods section?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
3. Are the characteristics of the subjects included in the study clearly described?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
4. Are the interventions of interest clearly described?	Yes (1)	N/A	N/A	Yes (1)	N/A	N/A
5. Are the distributions of principal confounders in each group of subjects to be compared clearly described?	Yes (2)	Partially (1)	Partially (1)	Partially (1)	Partially (1)	Yes (2)
6. Are the main findings of the study clearly described?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
7. Does the study provide estimates of the random variability in the data for the main outcomes?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
8. Have all important adverse events that may be a consequence of the intervention been reported?	Yes (1)	N/A	N/A	No (0)	N/A	N/A
9. Have the characteristics of subjects lost to follow-up been described?	Yes (1)	No (0)	No (0)	Yes (1)	No (0)	No (0)
10. Have actual probability values been reported (eg, .035 rather than <.05) for the main outcomes except where the probability value is <.001?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
Section total	11/11	7/9	7/9	9/11	7/9	8/9
External validity
11. Were the subjects asked to participate in the study representative of the entire population from which they were recruited?	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Yes (1)
12. Were those subjects who were prepared to participate representative of the entire population from which they were recruited?	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Yes (1)
13. Were the staff, places, and facilities where the patients were treated, representative of the treatment the majority of patients receive?	No (0)	N/A	N/A	Yes (1)	N/A	N/A
Section total	0/3	0/2	0/2	1/3	0/2	2/2
Internal validity—bias
14. Was an attempt made to blind study subjects to the intervention they received	Yes (1)	N/A	N/A	Yes (1)	N/A	N/A
15. Was an attempt made to blind those measuring the main outcomes of the intervention?	Yes (1)	N/A	N/A	Yes (1)	N/A	N/A
16. If any of the results of the study were based on “data dredging,” was this made clear?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
17. In trials and cohort studies, do the analyses adjust for different lengths of follow-up, or in case–control studies, is the time period between the intervention and outcome the same for cases and controls?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
18. Were the statistical tests used to assess the main outcomes appropriate?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
19. Was compliance with the intervention/s reliable?	Yes (1)	N/A	N/A	Unable to determine (0)	N/A	N/A
20. Were the main outcome measures used accurate (valid and reliable)?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
Section total	7/7	4/4	4/4	6/7	4/4	4/4
Internal validity—confounding (selection bias)
21. Were the subjects in different groups or were they recruited from the same population?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Yes (1)
22. Were study subjects in different groups or were they recruited over the same period?	Yes (1)	Yes (1)	Yes (1)	Yes (1)	Unable to determine (0)	Yes (1)
23. Were study subjects randomized to intervention groups?	Yes (1)	N/A	N/A	No (0)	N/A	N/A
24. Was the randomized intervention assignment concealed from both patients and health-care staff until recruitment was complete and irrevocable?	Yes (1)	N/A	N/A	Unable to determine (0)	N/A	N/A
25. Was there adequate adjustment for confounding in the analyses from which the main findings were drawn?	Yes (1)	No (0)	No (0)	Yes (1)	No (0)	Yes (1)
26. Were losses of subjects to follow-up considered?	Yes (1)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)
Section total	6/6	2/4	2/4	5/6	1/4	3/4
Power
27. Did the study have sufficient power to detect a clinically important effect, where the probability value for a difference being due to chance is <5%?	Yes (1)	Yes (1)	Yes (1)	Unable to determine (0)	Unable to determine (0)	Unable to determine (0)
Overall total	25/28	14/20	14/20	19/28	12/20	17/20
Overall quality classification	Good	Poor	Poor	Fair	Poor	Fair

N/A, not applicable.

DISCUSSION

This systematic review is the first to comprehensively examine creatine supplementation and/or estimations of dietary creatine intake in relation to cognition assessed as an outcome in older adult populations. Six articles were included in this review, with a large majority of studies reporting a positive association between creatine and cognition, particularly in the domains of memory and attention. However, the heterogeneity in study design across articles limits the strength and quality of the evidence, demonstrating the need for further research on this topic.

The main finding of a positive relationship between creatine and cognition aligns with findings from other recent systematic reviews. Xu and colleagues³⁹ reported that creatine supplementation significantly improves memory, attention, and processing speed. Surprisingly, however, subgroup analyses suggested that creatine supplementation was most beneficial on cognition in adults 18–60 years of age, compared with adults 60 years or older. Conversely, another review by Prokopidis et al³⁸ demonstrated that creatine supplementation improves memory performance in older adults (66–76 years), while no differences following supplementation were observed in young adults (11–31 years). These opposing findings may be explained by the differences in the inclusion/exclusion criteria of these reviews and the limited number of studies involving older adult participants overall. For instance, the Xu review only included three studies involving older adults (out of 13), while the Prokopidis review included two studies (out of 10). Additionally, one of the three studies involving older adults in the Xu review examined creatine with coenzyme q10 combination therapy on mild cognitive impairment in Parkinson’s disease,⁵² making it difficult to examine the underlying effects of creatine exclusively. These contradictory findings paired with the positive findings of the current review highlight the need for further clinical studies to explore the mechanistic effects of creatine on cognition in older adults.

The earlier literature has suggested that creatine supplementation may have a more significant effect on cognition in older, diseased, and stressed individuals than in younger, unstressed ones.^23,53,54 Differences in cognitive responses to creatine supplementation may stem from factors associated with aging, including declines in muscle and brain creatine levels, reduced physical activity, and lower dietary creatine intake.²¹ Additionally, changes in creatine transport efficiency and brain metabolism with aging and disease could influence how creatine affects cognitive function, potentially reducing its impact compared with that in younger adults.²¹ It has also been suggested that older adults may require additional energy to complete cognitive tasks, compared with younger individuals,⁵⁵ and this extra energy demand could be met through creatine supplementation.

There are several proposed mechanisms underlying the suggested improved cognitive function observed with increased creatine levels. Creatine supplementation raises the PCr/ATP ratio in the central nervous system, where creatine and ATP are converted into PCr and adenosine diphosphate in a reversible reaction catalyzed by creatine kinase (CK). This reaction helps sustain ATP regeneration in the brain, thereby increasing the energy supply to brain cells and supporting cognitive task performance during complex cognitive activities.⁵⁶ CK, a key enzyme in the ATP/CK/PCr pathway, exists in a brain-specific isoform (BB-CK), suggesting that creatine plays a crucial role in energy supply in the central nervous system.³⁶ During complex cognitive tasks, higher levels of brain creatine facilitate persistent regeneration of ATP in the brain, thereby augmenting cognitive task performance by increasing energy supply to brain cells.³³ In addition to energy regulation, creatine is also believed to improve cognitive function by enhancing neurotransmitter synthesis and function, increasing synaptic efficacy and plasticity, and reducing oxidative stress in synaptic vesicles.^57,58 These mechanisms provide a potential explanation for the ways by which creatine supplementation helps support cognitive function, though further research is needed to fully evaluate its impact across different populations and conditions.

Quality of Included Studies

Overall, the studies included in this review were not of high quality, as illustrated by 50% of studies achieving a “poor” quality classification. The cross-sectional studies already started at a lower maximum point potential than the intervention studies (maximum 20 vs 28 points, respectively). This was due to the lack of rigorous methods in observational designs that are typically present in interventions (e.g., in blinding and randomization), and the possibility of establishing a causal relationship in intervention studies. Therefore, the highest achievable quality classification for cross-sectional studies was “good.” Since four of the six studies in this review utilized a cross-sectional design, this impacted the quality of evidence substantially.

Reporting of key information, transparency in participant selection, inclusion of a sample size calculation, and discussion of the representativeness of each sample could have improved the quality of some of the included studies. Most studies only partially described the distribution of the principal confounders in each group of participants, and few discussed the characteristics of participants not included in the final analysis. This information is important to collect and describe when disseminating the results of research, to minimize the potential of reporting and confounding bias. Further, half of the included studies did not provide a sample size calculation to justify the number of individuals required to achieve statistical significance, so they may have been unknowingly underpowered. The external validity component of the quality assessment was also notably poor for most of the studies, because it was unclear whether the participants in the samples were representative of the populations from which they were recruited. Including this information is useful to gauge the applicability of the findings outside of each study population.

Strengths and Limitations of This Systematic Review

The strengths of this review primarily lie in its transparent methodology, meticulous quality assessment, and the inclusion of both experimental and observational studies. The transparency and rigor of this research was enhanced through following the PRISMA guidelines, where the methodology could be easily replicated by other researchers if desirable. Our comprehensive search across multiple databases also reduced the risk of publication bias and ensured to the best of our ability that all relevant literature were included. The quality appraisal using a validated checklist was a further strength, allowing us to identify and discuss potential biases in each study. Moreover, by considering both experimental and observational studies in this work, a broader perspective on the relationship between creatine and cognition in older adults was captured.

The limitations of this review are also important to acknowledge. Only studies published in English were included, which may have led to the exclusion of relevant literature published in other languages. Additionally, any relevant literature that was unpublished and not peer-reviewed (e.g., gray literature) was excluded. Further, a meta-analysis was not able to be conducted due to the variation across studies.

Limitations of the Current Evidence and Recommendations for Future Research

Most of the studies included in this review employed a cross-sectional design, limiting their ability to take into account other dietary and lifestyle factors that influence cognitive function. Potential confounding variables include other nutrients known to support cognition (e.g., omega-3 fatty acids),⁵⁹ as well as health-supporting behaviors, such as physical activity and social engagement. Given the interplay between diet and other health behaviors, the evidence from cross-sectional studies alone is insufficient for fully understanding the relationship between creatine and cognition. In addition, future research should investigate creatine levels in the context of overall dietary patterns, to explore potential interactions that may contribute to brain health.

The two intervention studies included in this systematic review, conducted by Alves et al⁴⁵ and McMorris et al,⁴⁹ reported conflicting results. The methods used within these studies varied widely, with one being an RCT of 24 weeks and the other being an intervention without explicit mention of randomization and only seven days of creatine supplementation. Similarly, the cognitive tasks and outcomes assessed in each study differed, making it difficult to compare the study results. As such, there is a need for high-quality and long-term clinical trials with consistent protocols and assessments to continue exploring the relationship between creatine and cognition in older adults in order to establish stronger inferences regarding cause and effect.

Another limitation of the current evidence is the lack of objective measurement of creatine concentrations in the body and brain. It is unclear whether the supplementation protocols were sufficient to increase the creatine levels in the intervention studies, and whether creatine concentrations differed in accordance with subjective dietary intake recall in the cross-sectional studies. Future work should consider objectively measuring creatine levels through human biomarkers (e.g., cerebrospinal fluid, blood) and neuroimaging techniques, for example, to gain direct insight into these concentrations. Examining creatine metabolites in the brain and how they relate to specific brain regions could provide further understanding on the association between creatine and cognitive performance in older adults.

Another point to note is that both interventions included in this review utilized an absolute (vs relative) dosing strategy—in other words, participants consumed a set amount of creatine per day regardless of body weight. To visualize this, an absolute dosing strategy would entail a 100-pound individual and a 200-pound individual consuming the same amount of creatine throughout the intervention. According to Candow and colleagues,²⁸ it appears that both absolute and relative dosing strategies are beneficial for increasing concentrations of creatine in the brain, but the existing literature on this topic lacks strong insight from studies with older adult participants. It remains unclear what the optimal dosage and duration of supplementation would be for benefiting brain function. Therefore, future research should consider implementing and exploring the impacts of a relative dosing creatine strategy in older adult populations. Since creatine levels are likely to decline with age,²¹ and since the brain may require higher doses of creatine than other energy demanding tissues,²⁸ employing a relative dosing strategy tailored to each individual (vs a one size fits all approach) may provide a more favourable environment for improved cognitive functioning and brain health in older adults, especially in those with higher body weight. In addition to dosing, various other factors that influence creatine concentrations (e.g., dietary intake, physical activity levels, sex, muscle mass) should also be considered in future studies examining creatine in this population.

Lastly, the findings of this systematic review only included samples of generally healthy community-dwelling older adults, apart from Machado et al⁴⁷ who examined overweight (BMI ≥ 25.0 kg/m²) women over 60 years of age. Building on findings from Xu and colleagues,³⁹ that individuals in a diseased state are likely to experience more cognitive benefits following creatine supplementation than healthy controls, future research should aim to investigate more clinical populations, such as individuals with cognitive impairment.

CONCLUSION

Creatine is widely recognized for its role in enhancing muscle mass and strength, yet its potential cognitive benefits among older adults remain underexplored. This systematic review suggests a positive association between creatine and cognition, particularly in memory and attention. However, with only six studies included, the evidence in this population proves to be sparse, highlighting the need for high-quality trials with both healthy and clinical older adult populations. Future research should also incorporate methods for objectively measuring creatine concentrations, and consider factors that influence creatine metabolism, such as diet, body weight, muscle mass, and physical activity.

Author Contributions

S.M.: Conceptualization, validation, formal analysis, investigation, data curation, writing—original draft, writing—review and editing, visualization, supervision, project administration, and funding acquisition; A.K.: Investigation, data curation, writing—original draft, and writing—review and editing; J.W.: Investigation, data curation, visualization, and writing—original draft; L.B.: Investigation, and writing—original draft; L.S.N.: Validation, writing—review and editing, supervision, and funding acquisition.

Supplementary Material

Supplementary Material is available at Nutrition Reviews online.

Funding

This research was supported by funding from the Natural Sciences and Engineering Research Council of Canada provided to L.S.N. [RGPIN-2016–05052] and S.M. [CGSD-589628–2024]. This research was undertaken, in part, thanks to funding from the Canada Research Chairs Program to L.S.N.

Conflicts of Interest

None declared.

Data Availability

The data underlying this article will be shared on reasonable request to the corresponding author.