Abstract
In the context of a globally aging population, exploring interventions that counteract age-related cognitive decline and cerebral structural alterations is paramount. Among various strategies, physical exercise (PE) emerges as a prevalent activity routinely incorporated in many individuals’ lives. This systematic review and meta-analysis aims to elucidate the impact of PE on white matter (WM) integrity and cognitive function in older adults. Data from 581 participants, 312 in the PE intervention group, and 269 in the control group were extracted from nine randomized controlled trials (RCTs) retrieved from databases including PubMed, Embase, Web of Science, and the Cochrane Library. The results indicated a significant improvement in white matter (WM) integrity in individuals engaged in PE, as evidenced by enhanced fractional anisotropy (FA) scores (SMD = 0.4, 95% confidence interval (CI) [0.05, 0.75], P = 0.024). The GRADE assessment revealed a moderate risk. However, no significant associations were found between PE and other metrics such as radial diffusivity (RD), mean diffusivity (MD), white matter volume (WMV), hippocampal volume (HV), and cognitive functions (executive function [EF], memory, processing speed). In conclusion, our study emphasizes the potential neurostructural and cognitive functional benefits of physical exercise for the brain health of older adults.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11357-023-01033-8.
Keywords: Physical exercise, Brain white matter integrity, Cognitive function, Meta-analysis
Introduction
The global increase in the elderly population brings to the forefront issues related to cognitive decline and brain structure degeneration, which particularly affect gray and white matter (WM). These changes are linked to a spectrum of adverse outcomes, including cognitive impairments and neurodegenerative diseases such as Alzheimer’s and age-related macular degeneration [1, 2]. Aging affects the brain significantly, impacting its structure and functions. WM, which consists mainly of neural fibers, is crucial for connecting and transmitting signals across different brain regions. As we age, WM integrity declines, leading to slower information processing and reduced brain connectivity. This decline can disrupt brain coordination and increase the risk of neurological disorders [3]. Research has established a strong link between WM degradation and cognitive decline, which impact memory, executive function, and attention. Damage in specific brain regions correlates with particular cognitive deficits, leading to conditions ranging from mild cognitive impairment to dementia. For instance, deterioration in the frontal lobe is primarily associated with deficits in executive functions, whereas damage to the parietal lobe predominantly affects visuospatial abilities [4–6]. This scenario presents significant challenges for healthcare systems and the quality of life of seniors, emphasizing the need for interventions to maintain cognitive health and WM integrity [7].
Physical exercise (PE) has been identified as a key non-pharmacological intervention. Besides its accessibility and cost-effectiveness, PE offers various health benefits and is known to improve brain structure and function [5, 8–10]. Neuroimaging studies show that PE enhances WM integrity by promoting blood vessel growth and enhancing myelin strength [11–13]. Techniques like diffusion tensor imaging (DTI) are used to examine WM integrity, measuring aspects like fractional anisotropy (FA), radial diffusivity (RD), mean diffusivity (MD), and WM volume (WMV). Evidence shows that regular PE enhances brain health by improving nerve cell adaptability and blood flow, alongside stimulating the release of brain-supporting chemicals [14–19]. Activities like aerobic exercise are shown to improve brain blood flow, support the development of new nerve cells and connections, and enhance cognitive functions such as attention, memory, and executive skills [20–22]. Different types of exercise, including resistance training and proprioceptive exercises, also offer brain benefits, though their specific effects require further research [23, 24]. Overall, PE benefits brain and cognitive health directly and indirectly through its positive effects on heart and blood vessel health [25].
While many studies have shown that PE can benefit cognitive performance and brain health in older adults [20, 26], inconsistent findings were reported regarding its specific effects on WM integrity and cognitive function [27]. Some research has showed positive links between exercise and factors like FA and WMV, but other studies report no significant or even negative correlations [27, 28]. Additionally, the impact of PE on cognitive skills, such as executive function, memory, and processing speed, varies among different studies, as its effect on the volume of the hippocampus [11]. These discrepancies highlight the need for a systematic review and meta-analysis to understand the impact of PE better and identify the most effective exercise types for cognitive and brain health in older adults.
This study aimed to assess the benefits of PE on WM integrity and its relationship with cognitive and brain structure metrics in older adults. By reviewing and integrating existing research, we seek to guide future research and the development of interventions to enhance cognitive abilities and brain health in older adults.
Material and methods
The present meta-analysis, registered with the PROSPERO reference number #CRD42023418744, follows the reporting guidelines of the PRISMA checklist [29].
The methods and analytical procedures employed in this study adhere to the recommendations and requirements outlined in the international guidance document, “The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration.”
Literature screening
A systematic search was conducted on articles from the inception of each database until January 2022 in seven databases, including Embase, Web of Science (WOS), Cochrane Library, PubMed, CNKI, Wanfang, and VIP. The search strategy, including the search terms, dates, and process, is detailed in Supplementary materials S1-Search strategy. The reference lists of relevant articles and reviews were also screened to obtain additional studies.
To ensure data quality, only primary studies were considered, and secondary sources like commentaries, editorials, and book chapters were excluded. The lead investigator independently performed title, abstract, and full-text screening on two separate occasions, resolving any discrepancies through discussion or with input from a third author. Search keywords in Chinese included “physical exercise,” “cognitive function,” and “white matter of the brain,” while in English, they were “Exercise,” “White matter,” and “Cognition.” A free-text search employed “Exercise” and “Physical” as primary English terms, resulting in the identification of 1885 potentially eligible articles for our meta-analysis.
Inclusion and exclusion criteria
Inclusion criteria
The literature was included based on the evidence-based medicine PICOS frame, which primarily considered five factors: population, intervention, comparison, outcomes, and study design.
Randomized controlled trials (RCTs) meeting the following criteria were included:
Participants: older adults with an average age of 60 years or above.
Interventions: The intervention group received physical exercise as the primary intervention, while the control group received no intervention (blank control) or alternative interventions (active control, etc.).
There were no restrictions on the type of physical exercise, duration, intensity, frequency, or cognitive function assessment method.
The study must report at least one result related to brain WM and cognitive function.
Outcome measures: FA (fractional anisotropy), HC (hippocampus), MD (mean diffusivity), RD (radial diffusivity), WMV (white matter volume), working memory, and processing speed.
Study type: Only RCTs were eligible for inclusion.
Studies could be in English or Chinese.
Exclusion criteria
The following types of articles were excluded from this study:
In vitro experiments (animal experiments), reviews, conference abstracts, letters, guidelines, case reports, pathological mechanisms, non-research diseases, etc.
Articles that could not be accessed in full text.
Duplicate articles; articles analyzed multiple times were counted as duplicates.
Articles with low quality or serious design flaws.
Articles whose outcome measurements were inconsistent with those specified in the inclusion criteria.
Data extraction
To enhance the reliability of the screening process and minimize subjective bias, two reviewers independently conducted data extraction and input. Using the EndNote software, we managed the literature, excluding duplicate articles or those that did not align with the inclusion criteria. Following initial and full-text screening, articles deemed suitable were meticulously reviewed to ascertain their relevance for this meta-analysis.
We utilized standardized forms to extract pertinent information from the literature, capturing details such as author names, gender ratios, publication year, region, study design, sample size, exercise duration, exercise type, and outcome measures. Moreover, for each eligible study, we gathered foundational participant details, specifics of both intervention and control conditions, tools used for cognitive assessment, and data essential for effect size computations. Any discrepancies in the data extraction process between the reviewers were resolved through discussions or by consulting with the entire team of authors.
Risk of bias assessment
The risk of bias in the included studies was independently assessed using the seven domains from the Cochrane 2011 risk of bias tool for randomized controlled trials (RCTs). These domains encompass random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other potential sources of bias.
Review Manager 5.4 was utilized to facilitate this risk of bias assessment. The evaluation process considered biases including selection bias, performance bias, detection bias, attrition bias, reporting bias, and other potential biases. This evaluation was conducted independently by two reviewers. In cases of discrepancies between the two reviewers’ assessments, discussions were held with a third reviewer and, if necessary, the study authors, until a consensus was reached.
Statistical analysis
Stata 15.0 software was used to perform meta-analysis on the included literature and generate forest plots and funnel plots for visual analysis. While we initially intended to explore publication bias using funnel plots and Egger’s test, this assessment could not be conducted due to the limited number of studies included in our analysis. For continuous outcome measures with different measurement methods, we used standardized mean differences (SMDs) and 95% confidence intervals (95% CIs) as the effect size of the combined results. On the other hand, for continuous variables with the same measurement values, mean differences (MDs) and 95% CIs were used as the effect size of the combined results. To further elucidate, we utilized I2 and P values to assess heterogeneity. For studies with I2 < 50% and P > 0.1, indicating no significant heterogeneity, a fixed-effects model was applied to combine effect sizes. However, when I2 > 50% and P < 0.1, suggesting significant heterogeneity, the prespecified random-effects model was employed to summarize the effect size, ensuring the reliability and precision of our meta-analysis outcomes. Given the substantial heterogeneity acknowledged among the studies, as noted in our introduction, a random-effects model was our prespecified approach.
Results
Literature search process and results
The flowchart of the study screening process was shown in Fig. 1. A preliminary search yielded 1885 articles (published from June 2013 to August 2020). After duplicates were removed, 1831 articles remained. Based on titles and abstracts, 1758 papers were excluded. The remaining 73 articles underwent full-text screening, and ultimately 64 articles were excluded, leaving 9 articles that met the criteria.
Fig. 1.
PRISMA flow diagram of the study process. PRISMA, Preferred Reporting Items for Systematic review and Meta-analysis
Summarizes the basic characteristics of the included studies
A total of nine articles were included in our assessment, involving 581 old participants, with 312 in the PE intervention group and 269 in the control group. These studies focused on the impact of PE on brain WM and cognitive function in old individuals. Basic characteristics of these articles are detailed in Supplementary Table S1.
Risk of bias assessment
We evaluated the risk of bias in the included studies. The percentages of various types of bias risks (high, unclear, or low) are described as follows: random sequence generation (100% low risk), allocation concealment (0 for high risk, 55.6% for unclear risk, 44.4% for low risk), blinding of outcome assessment (0 for high risk, 22.2% for unclear risk, 77.8% for low risk), incomplete outcome (0 for high risk, 11.1% for unclear risk, 88.9% for low risk), selective outcome reporting (0 for high risk, 44.4% for unclear risk, 55.6% for low risk), and other risks of bias (0 for high risk, 100% for unclear risk, 0 for low risk). The details are shown in Fig. 2.
Fig. 2.
Risk of bias assessment diagram. A Bias risk ratio diagram. B Schematic diagram of bias risk assessment
Meta-analysis results
Fractional anisotropy (FA)
FA is a parameter of WM integrity and was reported in six independent studies. The meta-analysis results showed significant heterogeneity among the studies for FA (I2 = 56.2%, P = 0.044). A random-effects model was used to combine the effect sizes, which indicated a positive effect of exercise on older adults compared with the control group (SMD = 0.4, 95%CI [0.05, 0.75], P = 0.024) (Fig. 3A).
Fig. 3.
Meta-analysis results. A Meta-analysis results for the effect of exercise intervention on FA in the WM of older adults. B Meta-analysis results for the effect of exercise intervention on RD in the WM of older adults. C Meta-analysis results for the effect of exercise intervention on MD in the WM of older adults. D Meta-analysis results for the effect of exercise intervention on WMV in older adults. Note: Weights are from random effects analysis
Radial diffusivity (RD)
RD is a measure of diffusion perpendicular to the principal fiber direction and is often interpreted as an indicator of myelin integrity. RD was evaluated in three independent studies. The meta-analysis result showed significant heterogeneity among the studies (I2 = 70%, P = 0.036), and a random-effects model was used to combine the effect sizes, which indicated no statistically significant effect of exercise intervention on RD in older adults compared with the control group (SMD = − 0.26, 95%CI [− 0.84, 0.32], P = 0.126) (Fig. 3B).
Mean diffusivity (MD)
MD was discussed in two independent studies as a measure of water diffusion within brain tissue, usually interpreted as an indicator of cell integrity. The meta-analysis result showed significant heterogeneity among the studies (I2 = 75.3%, P = 0.044), and a random-effects model was used to combine the effect sizes, which indicated no statistically significant effect of exercise intervention on MD in older adults compared with the control group (SMD = − 0.29, 95%CI [− 1.07, 0.49], P = 0.463) (Fig. 3C).
White matter volume (WMV)
WMV in three independent studies was examined. The meta-analysis results showed no significant heterogeneity among the studies (I2 = 0%, P = 0.877), indicating high consistency and comparability between these studies. Due to the lack of heterogeneity, a fixed-effects model was used for the meta-analysis, which showed no statistically significant effect of exercise intervention on older adults compared with the control group (SMD = 0.15, 95%CI [− 0.16, 0.45], P = 0.343) (Fig. 3D).
Hippocampus (HC)
HC volume was discussed in three independent studies as an important indicator of memory function. The meta-analysis results showed no significant heterogeneity among the studies (I2 = 0%, P = 0.428), indicating high consistency and comparability between these studies. A fixed-effects model was used for the meta-analysis, which showed no statistically significant effect of exercise intervention on older adults compared with the control group (SMD = 0.25, 95%CI [− 0.10, 0.61], P = 0.164) (Fig. 4A).
Fig. 4.
Meta-analysis results. A Meta-analysis results for the effect of exercise intervention on HC in older adults. B Meta-analysis results for the effect of exercise intervention on executive function in older adults. C Meta-analysis results for the effect of exercise intervention on memory in older adults. D Meta-analysis results for the effect of exercise intervention on processing speed in older adults. Note: Weights are from random effects analysis
Executive function
Executive function was reported in five studies. The meta-analysis results showed significant heterogeneity among the studies (I2 = 93.2%, P < 0.001). A random-effects model was used to combine the effect sizes, which indicated no statistically significant difference in executive function between older adults who exercised and the control group (SMD = − 0.44, 95%CI [− 1.38, 0.50], P = 0.361) (Fig. 4B).
Memory
A total of six studies reported on memory function, and the meta-analysis showed significant heterogeneity among them (I2 = 86.8%, P < 0.001). Therefore, a random-effects model was used for the meta-analysis, which indicated no significant difference in memory function between older adults who participated in physical activities and the control group (SMD = − 0.33, 95%CI [− 0.95, 0.28], P = 0.284) (Fig. 4C).
Processing speed
Three studies reported on cognitive processing speed, and the meta-analysis showed significant heterogeneity among them (I2 = 93.1%, P < 0.001). Therefore, a random-effects model was used for the meta-analysis, which indicated no significant difference in cognitive processing speed between older adults who participated in physical activities and the control group (SMD = − 0.18, 95%CI [− 1.30, 0.93], P = 0.748) (Fig. 4D).
Sensitivity analysis and grade
Sensitivity analyses were conducted for multiple metrics, including FA, RD, MD, WMV, HV, EF, memory, and processing speed. The consistent results indicated stable findings across all metrics, with no significant influence from individual studies (WMV, HV, EF, memory, and processing speed). The consistent results indicated stable findings across all metrics, with no significant influence from individual studies (Supplementary Figures S1 for FA, S2 for RD, S3 for MD, S4 for EF, S5 for memory, and S6 for processing speed).
Regarding the risk level, a moderate risk was observed for FA, RD, MD, EF, HV, and processing speed, while WMV and memory were considered to have a high risk (Supplementary Table S2-Grade rating).
Discussion
In an era of increased human longevity and prevalence of age-related diseases, especially neurodegenerative conditions, it becomes imperative to explore effective strategies to mitigate the impacts of aging. The traditional interventions for cognitive issues brought about by aging include dietary regulation, medication, cognitive training, social activities, maintaining good sleep habits, stress reduction, lifelong learning, avoiding alcohol and tobacco, and chronic disease management [12, 13, 27]. However, these traditional methods have certain application limitations to varying degrees, such as specialized knowledge, supporting equipment, and work constraints.
This study primarily focuses on PE, a method that is not bound by time or location and can be routinely practiced by individuals, to investigate the effects of PE on brain structure and cognitive function in older adults. Aging is often associated with WM degradation and potential cognitive decline. Our analysis of nine randomized controlled trials suggests that PE may play a role in supporting WM integrity, crucial for neural communication and cognitive performance [30–34]. These findings are in line with previous research that has highlighted superior cognitive functions, including memory, attention, and processing speed [11, 19, 30, 35] in older adults actively engaged in physical activities compared to their sedentary peers [20, 21, 30].
Different types of exercise were involved in the included studies, and the basic characteristics of exercise types are presented in Supplementary Table S3. This table outlines the diversity of exercise interventions, detailing their type, frequency, duration, and intensity. These factors may affect the efficacy of PE in improving WM integrity and cognitive functions. For instance, aerobic exercises, beneficial for cardiovascular health, may affect brain health differently compared to strength or flexibility exercises [35–37]. Different exercise intensities and durations play a crucial role in assessing their impact. This suggests the need for further research to identify the most effective types of exercise and regimens for older adults, taking factors into account such as feasibility of implementation, physical limitations, and specific health goals. Our systematic review underscores the vital role of regular PE in combating cognitive decline, positioning it as a feasible non-pharmacological intervention for promoting the mental health of older adults. Public health campaigns should emphasize the importance of PE for this population group. Our data suggest that moderate PE not only enhances overall health in older adults but also contributes to the maintenance of brain structure. Future research steps should include determining the optimal exercise types, duration, and intensity specifically tailored to older adults, as well as exploring synergistic benefits of PE and other interventions.
In summary, our study suggests PE as an important element in maintaining and potentially improving cognitive health and brain structure in older adults. The evidence from our meta-analysis and the RCTs reviewed suggest its significance in preserving WM integrity and overall brain health. Although further investigation is needed to understand the nuances of different exercise types and their specific impacts, the overarching implication is clear. A deeper understanding of the impact of PE on older adults is crucial for enhancing their quality of life and reducing societal healthcare burdens.
Conclusion
This systematic review and meta-analysis explores the critical importance of interventions for cognitive decline and brain structural changes in older adults. The study involved 581 participants across nine RCTs and indicates a correlation between PE and improved WM integrity, evidenced by increased FA scores. However, we found that PE did not significantly impact other evaluated metrics, such as RD, MD, WMV, HV, and cognitive functions. These findings indicate the complexity of the relationship between PE and brain health. Personalized exercise programs, tailored to the individual needs and capabilities of older adults, may offer more nuanced benefits in addressing age-related cognitive decline and contributing to overall brain health. Future research should continue to explore this complex interplay, aiming to optimize physical exercise interventions for the aging population.
Supplementary information
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Author contributions
Conceptualization: W.Z., A.C. Methodology: W.Z. Formal analysis and investigation: W.Z. Writing original draft preparation: W.Z. Writing review and editing: W.Z. Funding acquisition: A.C. Resources: A.C. Supervision: A.C., C.Z. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the National Natural Science Foundation of China
(32171040,32371105).
Declarations
Consent for publication
Not applicable.
Conflict of interest
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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