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. 2023 Nov 9;46(2):2755–2764. doi: 10.1007/s11357-023-00971-7

Aerobic exercise training effects on hippocampal volume in healthy older individuals: a meta-analysis of randomized controlled trials

Guilherme Moraes Balbim 1,2,3, Nárlon Cássio Boa Sorte Silva 1,2,3, Lisanne ten Brinke 1,2,3, Ryan S Falck 1,2,3,4, Tibor Hortobágyi 5,6,7,8, Urs Granacher 9, Kirk I Erickson 10,11, Rebeca Hernández-Gamboa 1,2,3, Teresa Liu-Ambrose 1,2,3,✉
PMCID: PMC10828456  PMID: 37943486

Abstract

We conducted a meta-analysis of randomized controlled trials investigating the effects of aerobic exercise training (AET) lasting ≥ 4 weeks on hippocampal volume and cardiorespiratory fitness (CRF) in cognitively unimpaired, healthy older individuals. Random-effects robust variance estimation models were used to test differences between AET and controls, while meta-regressions tested associations between CRF and hippocampal volume changes. We included eight studies (N = 554) delivering fully supervised AET for 3 to 12 months (M = 7.8, SD = 4.5) with an average AET volume of 129.85 min/week (SD = 45.5) at moderate-to-vigorous intensity. There were no significant effects of AET on hippocampal volume (SMD = 0.10, 95% CI − 0.01 to 0.21, p = 0.073), but AET moderately improved CRF (SMD = 0.30, 95% CI 0.12 to 0.48, p = 0.005). Improvement in CRF was not associated with changes in hippocampal volume (bSE = 0.05, SE = 0.51, p = 0.923). From the limited number of studies, AET does not seem to impact hippocampal volume in cognitively unimpaired, healthy older individuals. Notable methodological limitations across investigations might mask the lack of effects.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11357-023-00971-7.

Keywords: Meta-analysis, Aerobic exercise, Hippocampus, Older individuals

Introduction

Hippocampal atrophy and cognitive decline are common consequences of aging [1–4]. The decline in hippocampal volume is observed mainly in adults over the age of 50 [2, 3], with steeper declines over the age of 63 and at a greater rate (1.0 to 1.4% per year) than other neighbouring grey matter structures and total grey matter [4–7]. Several parallel cellular and molecular mechanisms in the ageing process are thought to explain hippocampus volume loss, including an increase in neuroinflammation, reduced trophic support, oxidative damage, cellular senescence, and misfolded protein aggregation [4, 8, 9]. These age-related alterations can also impair regenerative and protective effects present in early life [9–12], thereby leading to greater neuronal loss and decline in hippocampal-dependent cognitive functioning in late life [8, 12]. In the presence of other neurodegenerative processes (e.g. β-amyloid and tau pathology), hippocampal atrophy increases vulnerability to neurological conditions associated with cognitive impairment and dementia [13, 14].

Non-pharmacological interventions such as aerobic exercise training (AET) are thought to counteract hippocampal atrophy via experience-dependent neuroplastic adaptions [8, 15], which can ultimately promote hippocampal-dependent cognitive functioning [8, 15]. Adult neurogenesis is one of the main experience-dependent neuroplastic adaptions in the hippocampus [12, 16, 17]. The first evidence of adult neurogenesis in the mammalian brain appeared in 1965 [18]. Altman and Das [18] described ground-breaking findings that neurons in the dentate gyrus of the hippocampus in rats were still forming weeks after birth. Progress in the field demonstrated that external environmental factors could modulate hippocampal postnatal neurogenesis [19, 20]. Van Praag et al. [20] showed that voluntary AET, as a form of environmental enrichment, could enhance hippocampal neurogenesis and improve long-term potentiation and learning in mice [20]. The neuroplastic adaptations following AET were theorized to result from the upregulating effect on neurotrophins, most notably the brain-derived neurotrophic factor (BDNF) [21, 22]. Overall, these findings from the animal literature suggested that AET may be an effective strategy to counteract age-related hippocampal atrophy by promoting neurogenesis.

In 2011, Erickson et al. [23] published a seminal 12-month randomized controlled trial (RCT) providing the first evidence of hippocampal growth following AET in humans. After 12 months of AET, healthy older individuals had increased hippocampal volume measured with magnetic resonance imaging (MRI). Changes in hippocampal volume were positively associated with greater levels of serum BDNF, indicating that hippocampal growth could reflect BDNF-mediated neurogenesis induced by AET [23] as observed in animal models [20]. This interpretation was further supported by evidence postulating that hippocampus volume change measured with MRI after AET could be largely explained by hippocampal neurogenesis [17]. Despite these encouraging findings, the evidence for adult neurogenesis in the human hippocampus is still highly debated [24]. Using a comprehensive technique to detect transcriptomic and histologic signatures of neurogenesis in mammals, Franjic et al. [24] have reported that neurogenesis might be a species-specific phenomenon occurring in the hippocampus of mouse, pig, and macaque but not humans assessed at autopsy [24]. Furthermore, recent investigations have failed to show in vivo hippocampus volume growth after AET in healthy individuals [25–27], contradicting prior evidence [23].

Therefore, whether AET counteracts age-related hippocampal atrophy in healthy individuals remains to be determined. Elucidating modifiable behavioural modulators that can mitigate hippocampal atrophy and associated cognitive decline in aging is critical for promoting healthy aging. In particular, counteracting age-related hippocampal atrophy in healthy older individuals could prevent or delay the onset of cognitive impairment and dementia. To guide future research, here, we meta-analysed recently emerging data concerning the effects of AET on hippocampal volume in cognitively unimpaired, healthy older individuals. Secondary objectives included examining the effects of AET on cardiorespiratory fitness (CRF) and determining whether CRF changes were associated with changes in hippocampal volume in this population.

Materials and methods

Supplementary Material 1 contains a complete description of our methods. We performed a secondary meta-analysis of RCTs included in a previous meta-analysis [28]. The search was conducted in MEDLINE, Web of Science, and CINAHL and was limited to articles published in English between 01 January 1946 and 30 June 2022. We included studies meeting the following criteria: (1) an RCT; (2) included otherwise healthy individuals aged ≥ 50; (3) delivered AET for at least 4 weeks; (4) included at least one intervention group and one control group; (5) reported data on the effects of an AET intervention on hippocampal volume. Two authors (GMB and NCBSS) independently screened titles, abstracts and full texts and performed data extraction and methodological quality assessment using the Physiotherapy Evidence Database Scale. A third author (TH) resolved outstanding disagreements. One study [26] included two intervention arms (moderate-intensity continuous training [MICT] and high-intensity interval training [HIIT]) and reported three endpoints (12-, 36-, and 60-month post-intervention). We only included the 12-month outcomes, which were entered as separate effect sizes (ES) for each intervention arm in meta-analyses. Data from one RCT was reported across two publications [29, 30]; however, we combined the data to reflect one trial.

Data analysis

Supplementary Material 1 contains a complete description of our data analysis. Briefly, we performed meta-analyses with random-effects robust variance estimation models by weighting effect sizes to a prespecified within-study correlation of 0.8. Analyses with correlations ranging from 0.0 to 1.0 by increments of 0.2 were conducted as sensitivity analyses. T2 and I2 are reported as estimates of true heterogeneity. Leave-one-out analyses tested potential outliers. Funnel plots, Egger’s regression test and precision effect estimation with standard error tested publication bias. Meta-regression analyses tested associations between CRF and hippocampal volume changes. All analyses were conducted in R v.4.0.3. Data and analysis code are available online (https://github.com/guimbalbim/ae_hipp_vol).

Results

We included eight parent trials and one secondary outcome article (Fig. 1). Studies included 30–120 participants (Ntotal = 554), aged 68.1 years (SD = 4.6), and 58.6% (SD = 9.1%) females. Methodological quality was poor in one [31], fair in three [23, 32, 33], good in four [26, 27, 29, 34], and excellent in one trial [25]. Hippocampal volume outcomes included total, right and left, body, tail and head (Fig. 2). Interventions were fully supervised, lasting 3 [27, 29, 32, 34] to 12 months [23, 25, 26, 31]. AET session duration (median = 44, IQR = 11 min/session) and frequency (median = 3, IQR = 0 session/week) were similar between studies. Weekly AET volume ranged from 70 to 220 min (median = 128, IQR = 62), and total AET volume ranged from 18 to 138 h (median = 55, IQR = 77). AET intensity varied from moderate to vigorous, with prescription using target heart rate [23, 25, 26, 32, 33], target workload derived from direct CRF assessment [34], or indirectly via age-predicted maximum heart rate [27] and rate of perceived exertion [29]. Studies monitored AET intensity adherence based on the rate of perceived exertion [26, 29], heart rate [25, 27] and self-report logs and heart rate [23]. Only one study reported adherence data [29].

Fig. 1.

Fig. 1

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Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram

Fig. 2.

Fig. 2

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Forest plots for individual and pooled effect sizes (A, B) for hippocampal volume and cardiorespiratory fitness and assessment of and asymmetry of effect sizes (C, D). Abbreviations: HIIT high-intensity interval training; MICT moderate-intensity continuous training

Seventeen hippocampal volume ES from eight studies had a standardized mean difference (SMD) range of − 0.11 to 0.27. The meta-analytic summary effect indicated no significant effects of AET on hippocampal volume (SMD = 0.10, 95% CI − 0.01 to 0.21, p = 0.073, Fig. 2A), with no observed heterogeneity between the studies (I2 = 0%, T2 = 0%), and no asymmetry of ES (bSE =  − 27.52, SE = 29.14, p = 0.411, Fig. 2C). The association between the squared standard error and ES was not statistically significant (bSE =  − 2,445.18, SE = 5,656.26, p = 0.706). For CRF, we calculated 10 ES with SMD ranging from 0.05 to 1.21. The meta-analytic summary effect indicated significant effects (SMD = 0.30, 95% CI 0.12 to 0.48, p = 0.005, Fig. 2B) and low observed heterogeneity between the studies (I2 = 11.48%, T2 = 0.01%). Asymmetry was pronounced, with large standard errors demonstrating larger ES (bSE = 179.77, SE = 47.04, p = 0.040, Fig. 2D). The association between the squared standard error and ES was statistically significant (bSE = 35,673.06, SE = 36,78.06, p = 0.025), and the intercept was noticeably less than the summary ES for CRF outcomes (SMD = 0.18 versus 0.30), suggesting that the true ES for CRF might be smaller than the overall summary.

Meta-regression analyses revealed no associations between changes in CRF and changes in hippocampal volume (bSE = 0.03, SE = 0.49, p = 0.946). Sensitivity analyses altering the within-study correlation from 0.0 to 1.0 had no substantial impact on the summary effect on either outcome. Leave-one-out analysis suggested that similar results could be obtained after excluding any single study. No single ES disproportionally influenced the summary effects (hippocampal volume: ∆SMDmin =  − 0.03, ∆SMDmax = 0.02, CRF: ∆SMDmin =  − 0.05, ∆SMDmax = 0.04).

Discussion

In this meta-analysis, AET had no significant effects on hippocampal volume in cognitively unimpaired, healthy older individuals. We observed a significant effect on CRF favouring AET, suggesting AET fidelity across studies. This indicates that overall, the AET interventions provided sufficient stimuli to elicit cardiorespiratory physiological but not hippocampal adaptions. Nonetheless, this could be due to the differential length of exposure (i.e. intervention duration) needed to elicit changes in CRF compared with hippocampal volume. Our meta-regression did not show associations of improvements in CRF with changes in hippocampal volume. A significant limitation is that the overall number of studies included was restricted to RCTs reporting hippocampal volume as an outcome (n = 9), which may bias the associations between CRF and hippocampal volume changes.

A previous meta-analysis by Wilckens et al. [35] showed a positive effect of exercise interventions on hippocampal volume. The authors reported that interventions lasting longer than 6 months resulted in greater hippocampal volume changes [35] and that exercise preserved hippocampal volume while it atrophied in controls [35]. While the findings by Wilckens et al. [35] seem to disagree with ours, it is essential to highlight that the authors applied a broader inclusion criteria for exercise interventions (e.g. AET, resistance training) and target population (e.g. young adults, people living with cognitive impairment, schizophrenia or depression). Of note, while examining healthy individuals separately, Wilckens et al. [35] did not find significant effects of exercise on hippocampal volume, thus corroborating our findings.

As suggested by Wilckens et al. [35], the length of intervention may be an important factor influencing exercise effects on the human hippocampus. Interestingly, of the four studies lasting longer than 6 months [23, 25, 26, 31], only one showed a positive effect of AET on hippocampal volume [23]. Notably, Erickson et al. [23] reported a 1–2% increase in hippocampal volume following 12 months of AET, whereas Tarumi et al. [25] reported 1.9% atrophy. Two other studies showed no differences after 12 months [26, 31]. Other aspects of exercise prescription parameters may also influence AET effects on hippocampal volume [35]. Although AET intervention session duration and frequency were similar across studies in our meta-analyses, exercise intensity was not uniformly prescribed (i.e. direct and indirect methods used to determine intensity). Similarly, it is unclear whether adherence to exercise prescription parameters, physical fitness levels before study commencement, and intervention delivery (e.g. group vs individual) would influence AET effects on hippocampal volume. Due to the limited number of studies available, we could not analyze the impact of these factors on hippocampal volume in cognitively unimpaired, healthy older individuals.

The lack of RCTs designed to assess the effects of AET on hippocampal volume is notable. Of the nine studies included, only one had hippocampal volume as its primary outcome; it was also the only study to demonstrate a positive effect of AET on hippocampal volume [23]. All remaining studies had hippocampal volume as a secondary outcome [25–27, 29, 31–34]. Variability in the techniques used to quantify hippocampal volume is also a notable factor that could have influenced our findings. The use of different software packages such as FreeSurfer [25, 26], FSL [23] or SPM [34] to preprocess MRI volumetric data could limit sensitivity to detect significant measurable change. Relatedly, automated hippocampal segmentation from MRI data often overestimates hippocampus size compared with manual segmentation [36]. This overestimation likely reflects the inclusion of non-hippocampal tissue that may not show neuroplastic effects (e.g. growth) in response to AET effects [4], which is substantiated by evidence from animal models indicating that neurogenesis, a process almost exclusively confined to the hippocampus [12, 37, 38], could be the major contributor to AET-induced hippocampal volume growth measured with MRI [17].

Although not investigated in our meta-analysis, several mechanisms have been proposed to explain the pathways through which AET supports hippocampal growth, primarily shown in animal models (e.g. mice and rats). The evidence converges for the role of physical exercise (especially in the form of AET) in inducing increases in neurotrophic factors and modulating hippocampal plasticity [20, 39–48]. Other potential mechanisms involve AET-caused activation of the Sirtuin1 enzyme and related pathways, which regulate cellular and molecular events promoting brain structure’s protective effects [49–51]. The most well-studied of these mechanisms is the AET-promoting role in the expression of BDNF [20, 39–48]. Other suggested neurotrophic factors are increases in circulating insulin-like growth factor 1 (IGF-1) [52] and peripheral vascular endothelial growth factor (VEGF) [53]. In humans, prior research hypothesized and investigated the role of these neurotrophic factors in exercise-related changes in hippocampal volume [23, 32, 54–56]; nonetheless, the evidence is still not as converging as in animal models. A caveat to evidence in humans may be that the effects of physical exercise on these neurotrophic factors are possibly fast and transient [48, 57] and not detectable by current techniques.

Lastly, it is plausible that hippocampal growth after AET follows the expansion–renormalization model for neuroplastic changes in humans [10, 58]. This model postulates that volumetric brain changes induced by AET could result from an initial increase in grey matter structure reflecting processes like neurogenesis, synaptic plasticity and glial cell proliferation [10, 58]. However, this initial growth would be followed by a selection period to eliminate unnecessary or inefficient surplus (e.g. elimination of dendritic branches, axonal projections and synaptic connections), leading to a renormalization of gray matter structure either partially or entirely to baseline levels as observable with MRI [10, 58]. This tissue renormalization would accompany continued improvement or maintenance of cognitive functioning, considering that the neuroplastic adaptions would reflect tissue efficiency [10, 58]. Although this model offers some support for our findings, it is unclear whether the lack of hippocampal volume change in our meta-analysis reflects tissue renormalization, as we did not assess the effects of AET on hippocampal-dependent cognitive functioning. The timescale for expansion, selection and renormalization of hippocampal tissue following AET in healthy individuals is also not understood. We included studies with AET interventions spanning 3 to 12 months, with one study showing hippocampal growth only at 12 months [23]. Future work is needed to elucidate whether the expansion–renormalization model indeed explains hippocampal volumetric changes after AET in healthy individuals.

Concluding remarks

Given the importance of the hippocampus to healthy cognitive aging, and the mounting evidence of the benefits of AET to brain and cognitive health in older individuals [59–61], research on the effects of AET on hippocampal structure and function is still a worthwhile and exciting research avenue. Overall, the biologically still plausible favourable effects of AET on hippocampal volume in cognitively unimpaired, healthy older individuals might be masked by methodological variability and limitations that future studies must address. In the studies included in our meta-analysis, there was considerable variability regarding the length of AET intervention, weekly and total AET volume, and AET intensity prescription, monitoring and adherence. Key methodological shortcomings of these studies included insufficient power to detect meaningful changes in hippocampal volume and lack of harmonization of hippocampal volume quantification methods across investigations. It is also plausible that hippocampal growth after AET may follow an expansion, selection and renormalization model, the timescale of which remains incompletely understood. Future research should be dedicated to addressing these limitations to elucidate the long-term impact of AET on hippocampal volumetric changes and its relevance to cognitive function and dementia risk in healthy older individuals.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 67 KB) (66.8KB, docx)

Acknowledgements

The authors thank Sabina Gillsund and Narcisa Hannerz from the Karolinska Institutet Library for their help with literature searches.

Author contribution

TH, UG and TLA designed the primary research. GMB, NCBSS and TLA designed the current research. GMB, NCBSS and TH performed the research. GMB and NCBSS analysed and interpreted the data. GMB, NCBSS, LTB, RSF, TH, UG, KIE, RH-G and TLA wrote the paper.

Funding

GMB and NCBSS are jointly funded by the Michael Smith Health Research BC and the Canadian Institutes of Health Research. NCBSS is supported by the Canadians for Leading Edge Alzheimer’s Research. RSF is funded by the Michael Smith Health Research BC. TLA is a Canada Research Chair (Tier I) in Healthy Aging. TH is supported by the Deltaplan Dementie (ZonMW: Memorabel 733050303) and a Healthy Ageing seed grant (CDO17.0023–2017–2–316) from the University Medical Center Groningen.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declarations

Competing Interests

The authors declare no competing interests.

Disclaimer

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Footnotes

Guilherme Moraes Balbim and Nárlon Cássio Boa Sorte Silva contributed equality to this work.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

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Supplementary Materials

Supplementary file1 (DOCX 67 KB) (66.8KB, docx)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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