Effects of a 20-Week Rhythmic Exercise Program on Physical Fitness, Cardiovascular Risk Markers, and Brain-Derived Neurotrophic Factor in Older Women
Article information
Abstract
PURPOSE
This study examined the effects of a 20-week rhythmic exercise program on body composition, physical fitness, cardiovascular disease–related blood variables, inflammatory cytokines, dementia-related biomarkers, and cognitive function in elderly women.
METHODS
Twenty-nine elderly women (mean age, 71±4 years) were randomly assigned to an exercise group (EX, n=14) or a control group (CON, n=15). The exercise group participated in a rhythmic exercise program for 20 weeks (three sessions per week, 60 minutes per session). Body composition, physical fitness, blood variables, and cognitive function were assessed before and after the intervention. Data were analyzed using two-way mixed-design analysis of variance (ANOVA).
RESULTS
Significant group×time interactions were observed for body weight (p=.040) and body mass index (p=.042). Physical fitness measures, including the 30-s sit-to-stand (p=.003), 2-min stationary march (p=.037), sit-and-reach (p<.001), and Figure-of-8 Walk (p=.007), also showed significant interactions. Among blood variables, after adjusting for baseline systolic and diastolic blood pressure, HDL-C (p=.006) and BDNF (p=.033) demonstrated significant interactions. DHEA-S showed a significant time effect (p<.001) without interaction. No significant interaction was found for ADAS-Cog, although within-group improvement was observed.
CONCLUSIONS
A 20-week rhythmic exercise program improved physical fitness and induced favorable changes in selected cardiovascular and dementia-related biomarkers in elderly women. While no clear between-group effect on cognitive outcomes was observed, the findings suggest a potential role of rhythmic exercise in supporting cognitive-related physiological function, warranting further investigation.
INTRODUCTION
Population aging is rapidly progressing worldwide, resulting in a substantial increase in the prevalence of dementia and imposing significant social and economic burdens [1]. Because dementia is an irreversible neurodegenerative condition once it develops, preventive strategies have become increasingly important. Consequently, non-pharmacological approaches have received growing attention [2]. Among these strategies, physical exercise has been widely recognized as a safe and cost-effective intervention for promoting physical health and cognitive well-being in older adults [3,4]. Exercise has been shown to enhance cerebral blood flow, promote neuroplasticity, and increase levels of neurotrophic factors such as brain-derived neurotrophic factor (BDNF), which may contribute to improvements in cognitive function [5,6].
The development and progression of dementia are associated with multiple physiological mechanisms, including dysregulation of lipid metabolism, oxidative stress, and neuroinflammation. Previous studies have reported that individuals with dementia tend to exhibit elevated levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C), whereas high-density lipoprotein cholesterol (HDL-C) levels are typically lower compared with cognitively healthy older adults [7]. HDL-C plays a protective role in brain health by facilitating the clearance of β-amyloid and exerting anti-inflammatory effects [8]. In addition, neuroinflammation induced by oxidative stress has been identified as a key factor contributing to neuronal damage and cognitive decline. Pro-inflammatory cytokines such as interleukin-6 (IL-6) and systemic inflammatory markers including high-sensitivity C-reactive protein (hs-CRP) have been associated with accelerated neurodegenerative processes and cognitive impairment [9]. In contrast, neuroprotective factors such as insulin-like growth factor-1 (IGF-1), BDNF, and dehydroepiandrosterone sulfate (DHEA-S) play important roles in regulating inflammatory responses, supporting neuronal survival, and maintaining synaptic plasticity [10]. Increased levels of these neurotrophic factors are associated with improved cognitive performance and reduced neuroinflammation.
Regular physical activity has been widely recommended as a nonpharmacological strategy for preventing cognitive decline in older adults. Aerobic exercises such as walking have been shown to improve cardiovascular fitness, body composition, and lipid metabolism [11,12], and aerobic capacity has been positively associated with cognitive performance and executive function [13]. However, some studies suggest that simple repetitive activities such as walking may provide limited cognitive stimulation because they involve relatively low levels of motor complexity and cognitive engagement [14]. Therefore, exercise interventions that simultaneously incorporate physical activity and cognitive stimulation may be more effective for improving cognitive function in older adults.
Rhythmic exercise, which integrates coordinated body movements performed in synchrony with music, represents a promising form of cognitive–motor training. This type of exercise requires continuous motor coordination, timing control, and attentional engagement, thereby providing both physical and cognitive stimulation. Previous studies have demonstrated that rhythmic or dance-based exercise can significantly improve cognitive performance in individuals with mild cognitive impairment (MCI) [15-18]. Furthermore, dance-based interventions have been shown to increase BDNF levels, which are closely associated with neuroplasticity and learning processes [19,20]. Music-based movement activities have also been reported to enhance brain activation and emotional engagement, potentially contributing to improved cognitive function [21]. However, relatively few studies have simultaneously examined the effects of rhythmic exercise on dementia-related blood biomarkers, inflammatory cytokines, and cognitive function in older adults. In particular, evidence regarding the combined physiological and cognitive benefits of rhythmic exercise in elderly women remains limited. Compared with traditional aerobic or resistance exercise, rhythmic exercise may provide additional benefits by simultaneously engaging motor coordination, timing, balance, and sustained attention through synchronized movement with music. These multimodal characteristics may be particularly relevant for older adults, as declines in motor function and coordination are closely linked to sarcopenia and increased risk of cognitive impairment [22] and dementia [23,24]. Furthermore, age-related declines in physical function, often characterized by sarcopenia-like motor dysfunction, have been identified as important contributors to the development and progression of cognitive impairment and dementia [23,24]. Therefore, exercise interventions that improve both physical and cognitive function may play a critical role in mitigating the interconnected pathways between sarcopenia and cognitive decline.
Therefore, the purpose of this study was to investigate the effects of a 20-week rhythmic exercise program on cognitive function and dementia- related physiological markers, including blood biomarkers, inflammatory cytokines, body composition, and physical fitness, in elderly women. Based on these considerations, we hypothesized that the 20- week rhythmic exercise program would improve physical fitness, cardiovascular disease–related blood variables, and dementia-related biomarkers, and may also have potential beneficial effects on cognitive function in elderly women.
METHODS
1. Participants
Participants were community-dwelling older women with a mean age of approximately 71 years. Recruitment was conducted through posters displayed in public community facilities and announcements posted on local online platforms. Individuals who expressed interest in the study were screened according to predefined inclusion and exclusion criteria. The inclusion criteria were as follows: (1) engagement in less than 150 min per week of moderate-intensity aerobic exercise (3–6 METs) or less than 60 min per week of vigorous-intensity aerobic exercise (>6 METs) during the previous six months; (2) absence of regular resistance training performed at least twice per week with 10–15 repetitions per session; and (3) the ability to safely perform moderate-to-vigorous physical activity. The exclusion criteria were (1) visual, auditory, or communication impairments that could interfere with testing procedures; (2) limited literacy that could affect comprehension of instructions; and (3) concurrent participation in another intervention study. Prior to enrollment, all participants received a detailed explanation of the study objectives, procedures, and potential risks, and written informed consent was obtained from all participants before participation.
Participants were randomly assigned to either the exercise group or the control group using a computer-generated randomization sequence to minimize allocation bias. Randomization was performed by an investigator who was not involved in the outcome assessment procedures. The required sample size was estimated using G*Power software (version 3.1, Heinrich-Heine-Universität Düsseldorf, Germany). The calculation was based on a repeated-measures ANOVA design with an assumed medium-to-large effect size (η²= 0.25), a significance level (α) of 0.05, and statistical power (1−β) of 0.85. The analysis indicated that a minimum of 26 participants would be required to detect a statistically significant group×time interaction. Considering a potential dropout rate of approximately 10–15%, a total of 30 participants were initially recruited. During the intervention period, one participant withdrew for personal reasons. Consequently, a total of 29 participants completed the study and were included in the final analysis (exercise group, n=14; control group, n=15). The study protocol was approved by the Institutional Review Board of the Korea Institute of Sport Science (IRB No. KISS–23016–2307–04) and was conducted in accordance with the Declaration of Helsinki.
2. Intervention
Participants assigned to the exercise group participated in a 20-week rhythmic exercise training program performed three times per week for a total of 60 sessions. During the first week, participants were familiarized with the basic movement patterns and the use of a wireless heart rate monitoring device. Each exercise session lasted approximately 60 minutes, consisting of a 10-minute warm-up, a 35-minute main exercise phase, and a 15-minute cool-down period. The warm-up consisted primarily of dynamic stretching exercises to prepare the musculoskeletal system for subsequent activity. The main exercise component involved rhythmic aerobic step movements combined with agility and coordination drills designed for older adults. These exercises incorporated coordinated step patterns, directional changes, and rhythm-based movement sequences performed in synchronization with music. Coordination training included ladder drills and multidirectional movement patterns designed to improve agility and motor coordination. The cool-down phase included finger-based brain coordination exercises and static stretching to promote recovery and improve flexibility. All sessions were accompanied by music with predetermined beats per minute (BPM) to facilitate rhythmic synchronization and maintain a consistent exercise tempo. Exercise intensity was progressively increased throughout the intervention period. Target heart rate zones were set at 60–65% of HRmax during weeks 1–5, 65–70% during weeks 6–10, 70–75% during weeks 11–15, and 80–85% during weeks 16–20. Maximum heart rate (HRmax) was estimated using the age-predicted formula (HRmax=220 − age), which is widely used in exercise studies; however, it may have limitations in accurately estimating individual HRmax values, particularly in older adults. Heart rate was continuously monitored during each session using a wireless heart rate monitoring device to ensure that participants exercised within the prescribed intensity range. Exercise intensity and training load were monitored by recording heart rate responses and estimated energy expenditure during each session. Because each session included warm-up, main exercise, and cool-down phases, mean heart rate values represent the average across the entire session, whereas peak heart rate reflects the highest intensity achieved during the main exercise phase. All exercise sessions were supervised by a certified exercise specialist to ensure participant safety and adherence to the standardized protocol. Exercise adherence was monitored by recording attendance at each training session. No adverse events related to the exercise intervention were reported during the study period. The detailed structure of the rhythmic exercise program is presented in Table 1. Participants assigned to the control group were instructed to maintain their usual daily activities throughout the study period and were asked to refrain from initiating any structured exercise programs during the intervention.
Structure of the 20-week rhythmic exercise training program
3. Outcomes and measurements
All participants visited the laboratory before and after the 20-week intervention period for outcome assessments. To minimize external influences on physiological measurements, participants were instructed to refrain from alcohol consumption, caffeine intake, and vigorous physical activity beginning the day prior to testing and were required to maintain an overnight fast of at least 12 hours before laboratory visits. All measurements were conducted in the morning at 08:00 under standardized laboratory conditions. After arrival, participants rested in a seated position for approximately 30 minutes to stabilize physiological responses before the assessments were initiated. Following the resting period, measurements were performed in a standardized order including venous blood sampling, body composition assessment, blood pressure measurement, physical fitness testing, and cognitive function evaluation.
Body composition was assessed using a bioelectrical impedance analyzer (InBody 620; Biospace Co., Seoul, Korea) together with an automatic stadiometer (BSM 370; Biospace Co., Seoul, Korea). Height, body weight, body fat percentage, and skeletal muscle mass were recorded, and body mass index (BMI) was calculated as body weight divided by height squared (kg/m²). Resting blood pressure was measured using an automated sphygmomanometer (BPBIO 320S; InBody Co., Seoul, Korea), and measurements were obtained twice at 5-minute intervals, with the mean value used for analysis. Physical fitness was evaluated using standardized procedures derived from the National Fitness Award 100 program in Korea. The assessments included relative grip strength, the 30-second sit-to-stand test, the 2-minute stationary march test, the sit-and-reach test, the Timed Up-and-Go test, and the Figure-of-8 Walk test. These tests collectively evaluated muscular strength, lower-body endurance, cardiorespiratory endurance, flexibility, balance, and agility. All physical fitness assessments were conducted by trained evaluators following standardized testing procedures. Venous blood samples were collected from the antecubital vein following the resting stabilization period. Blood samples were centrifuged to separate serum and plasma, which were subsequently stored at −80°C until biochemical analyses were performed. The analyzed blood variables included cardiovascular disease-related markers (total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol), inflammatory markers (interleukin-6, high-sensitivity C-reactive protein, and albumin), and dementia-related biomarkers (insulin-like growth factor-1, brain-derived neurotrophic factor, and dehydroepiandrosterone sulfate). Cognitive function was assessed using the 13-item Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-Cog 13), with total scores ranging from 0 to 85 and lower scores indicating better cognitive performance. Outcome assessments were conducted by investigators who were blinded to group allocation whenever possible.
4. Statistical analysis
All statistical analyses were performed using IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics are presented as mean±standard deviation (SD), and the normality of data distribution was assessed using the Shapiro–Wilk test. Baseline differences between the exercise and control groups were examined using independent samples t-tests. To evaluate the effects of the intervention, a two-way mixed-design analysis of variance (ANOVA) was conducted with group (exercise vs. control) as the between-subject factor and time (pre vs. post) as the within-subject factor. Additionally, to account for baseline differences in systolic and diastolic blood pressure, additional analyses were performed using repeated-measures ANCOVA, with baseline SBP and DBP included as covariates for cardiovascular-related outcomes. When significant interaction or main effects were observed, Bonferroni-adjusted post hoc comparisons were performed to control for multiple comparisons. Body composition and physical fitness variables were defined as primary outcomes, whereas cardiovascular, inflammatory, dementia-related biomarkers, and cognitive outcomes were considered secondary exploratory outcomes. Effect sizes were calculated using partial eta squared (η²) to determine the magnitude of the intervention effects. Statistical significance was set at p<.05.
RESULTS
1. Participant flow and baseline characteristics
A total of 30 participants were enrolled and randomly assigned to either the exercise group or the control group. During the intervention period, one participant withdrew from the exercise group for personal reasons. Consequently, 29 participants completed the study and were included in the final analysis (exercise group, n=14; control group, n=15) (Fig. 1).
Participant recruitment, randomization, follow-up, and analysis flow diagram. A total of 30 participants were assessed for eligibility and randomly assigned to either the intervention group or the control group (n=15 each). During the intervention period, one participant in the intervention group withdrew for personal reasons. Consequently, 29 participants completed the study and were included in the final analysis (intervention group, n=14; control group, n=15).
Baseline characteristics of the participants are presented in Table 2. Overall, the exercise and control groups were comparable at baseline. No significant between-group differences were observed in age, years of education, body composition variables, or skeletal muscle mass. However, systolic blood pressure and diastolic blood pressure were significantly higher in the exercise group than in the control group at baseline (both p <.05). However, systolic blood pressure and diastolic blood pressure were significantly higher in the exercise group than in the control group at baseline (both p <.05). Accordingly, additional analyses were performed using repeated-measures ANCOVA, with baseline systolic and diastolic blood pressure included as covariates for cardiovascular-related outcomes.
Baseline characteristics of participants
2. Intervention fidelity
Exercise intensity and caloric expenditure during the 20-week rhythmic exercise program are presented in Table 3. Exercise intensity progressively increased across the intervention period. Mean heart rate responses increased from 65% of HRmax during weeks 1–5 to 71% of HRmax during weeks 11–20, whereas peak heart rate responses ranged from 85% to 87% of HRmax throughout the intervention period. While mean heart rate values reflect the average intensity across the entire session, peak heart rate values indicate that participants reached higher target intensities during the main exercise phase. Caloric expenditure also increased progressively from 154 kcal during weeks 1–5 to 214 kcal during weeks 16–20.
Exercise intensity and caloric expenditure during the 20-week rhythmic exercise program
3. Effects of the intervention
Changes in primary and secondary outcomes before and after the intervention are presented in Table 4, and selected outcomes are illustrated in Figs. 2–4.
Changes in primary and secondary outcomes before and after the 20-week rhythmic exercise intervention
Changes in HDL-C levels in the intervention (EX) and control (CON) groups before and after the 20-week intervention. Values are presented as mean ±SD. HDL-C, high-density lipoprotein cholesterol. **p<.01 indicate significant within-group difference between pre- and post-intervention. ##p<.01 indicate significant group×time interaction.
Changes in BDNF levels in the intervention (EX) and control (CON) groups before and after the 20-week intervention. Values are presented as mean±SD. BDNF, brain-derived neurotrophic factor. *p<.05 indicates a significant within-group difference between pre- and post-intervention. #p<.05 indicates a significant group×time interaction.
Changes in ADAS-Cog scores in the intervention (EX) and control (CON) groups before and after the 20-week intervention. Values are presented as mean±SD. Lower ADAS-Cog scores indicate better cognitive function. A significant main effect of time was observed (p=.004), whereas the group×time interaction was not significant (p=.531). ***p<.001 indicates a significant within-group difference between pre- and post-intervention in the intervention group.
For body composition, significant group×time interactions were observed for body weight (p =.040) and body mass index (BMI) (p =.042). Post hoc comparisons indicated that the control group showed significant increases in both body weight and BMI during the 20-week period, whereas no significant changes were observed in the exercise group. No significant interaction effects were found for percent body fat (p =.576) or skeletal muscle mass (p =.113).
For physical fitness variables, significant group×time interactions were observed for the 30-s sit-to-stand test (p =.003), the 2-min stationary march test (p =.037), the sit-and-reach test (p<.001), and the Figure-of-8 Walk test (p =.007). These results indicate significant improvements in lower-body muscular endurance, cardiorespiratory endurance, flexibility, and agility in the exercise group compared with the control group. No significant interaction effects were observed for relative grip strength (p =.840) or the Timed Up-and-Go test (p =.074), although significant main effects of time (p =.043) and group (p =.011) were observed for the Timed Up-and-Go test.
For cardiovascular disease–related blood variables, after adjusting for baseline systolic and diastolic blood pressure, no significant group×time interaction was observed for total cholesterol (TC) (p =.180). TC levels showed a decreasing trend in the exercise group; however, the between-group difference over time was not statistically significant after adjustment. In contrast, a significant group×time interaction remained for high-density lipoprotein cholesterol (HDL-C) (p =.006), with HDL-C levels increasing in the exercise group while remaining relatively unchanged in the control group. No significant interaction effects were observed for triglycerides (TG) (p =.540) or low-density lipoprotein cholesterol (LDL-C) (p =.760).
For inflammatory markers, no significant group×time interactions were observed for interleukin-6 (IL-6) (p =.296), high-sensitivity C-reactive protein (hs-CRP) (p =.366), or albumin (p =.103).
For dementia-related blood biomarkers, a significant group×time interaction was observed for brain-derived neurotrophic factor (BDNF) (p =.033). Post hoc analysis indicated that BDNF levels increased in the exercise group after the intervention, whereas no significant change was observed in the control group (Fig. 3). No significant interaction effects were found for insulin-like growth factor-1 (IGF-1) (p =.420). Dehydroepiandrosterone sulfate (DHEA-S) did not show a significant group×time interaction (p =.252), although a significant main effect of time was observed (p<.001).
For cognitive function, a significant main effect of time was observed for ADAS-Cog scores (p=.004), whereas no significant main effect of group (p=.713) or group×time interaction (p=.531) was found. Post hoc comparisons indicated that ADAS-Cog scores significantly decreased in the exercise group following the intervention (p<.001), whereas no significant change was observed in the control group (p=.225) (Fig. 4).
DISCUSSION
The present study investigated the effects of a 20-week rhythmic exercise program combining coordinated aerobic movements with concurrent cognitive tasks on body composition, physical fitness, cardiovascular disease–related blood variables, inflammatory cytokines, dementiarelated blood biomarkers, and cognitive function in elderly women. The main findings of this study were that rhythmic exercise significantly improved several components of physical fitness and induced favorable changes in selected cardiovascular and neurobiological markers, particularly high-density lipoprotein cholesterol (HDL-C), and brain-derived neurotrophic factor (BDNF). In addition, although no significant group ×time interaction was observed for cognitive function, the exercise group demonstrated a significant within-group improvement in ADAS-Cog scores following the intervention. In contrast, inflammatory cytokines did not show significant changes.
Aging is characterized by progressive declines in skeletal muscle mass and physical function accompanied by increases in body fat and metabolic dysregulation, a condition commonly referred to as sarcopenia [25,26]. These changes contribute to reduced mobility, increased risk of falls, and deterioration in overall health status among older adults. In the present study, body weight and BMI showed significant group×time interactions. Although the exercise group did not demonstrate significant reductions over time, the control group exhibited significant increases in both variables during the 20-week period. These findings suggest that rhythmic exercise may help attenuate age-related increases in body weight and BMI in elderly women. However, skeletal muscle mass did not change significantly following the intervention. This finding is consistent with previous systematic reviews indicating that dance-based exercise interventions improve functional fitness but may not produce substantial changes in body composition without sufficient resistance training stimulus or dietary modification [27].
Physical fitness is a key determinant of healthy aging and includes components such as cardiorespiratory endurance, muscular strength, flexibility, balance, and coordination [28]. In the present study, rhythmic exercise significantly improved several physical fitness variables, including sit-to-stand performance, the 2-min stationary march, sit-and-reach flexibility, and the Figure-of-8 walk test. Timed Up-and-Go performance also improved within the exercise group. These findings indicate that rhythmic exercise effectively enhanced lower-body muscular endurance, aerobic capacity, flexibility, agility, and coordination. Previous studies have similarly reported that dance-based exercise programs improve functional mobility and physical performance in older adults [29-31]. Because rhythmic exercise requires coordinated body movements, balance control, directional changes, and synchronization with musical tempo, it may provide broader functional stimulation than traditional repetitive aerobic exercise. Importantly, these improvements in functional fitness may reflect enhancements in sarcopenia-related motor function, which has been increasingly recognized as a key factor associated with cognitive decline and dementia [25-27]. Improvements in mobility, coordination, and lower-body function may contribute to maintaining independence and reducing the risk of neurodegenerative progression. In this context, rhythmic exercise may exert beneficial effects not only on physical performance but also on the underlying pathways linking sarcopenia and cognitive impairment, through integrated motor and cognitive stimulation.
Age-related deterioration in lipid metabolism contributes to the development of cardiovascular diseases and is also associated with an increased risk of cognitive decline and dementia [32,33]. In the present study, TC showed a decreasing trend in the exercise group; however, no significant group×time interaction was observed after adjusting for baseline systolic and diastolic blood pressure. Previous meta-analyses have reported that aerobic exercise can improve lipid profiles in older adults by reducing total cholesterol, triglycerides, and low-density lipoprotein levels while increasing high-density lipoprotein levels [34,35]. These findings suggest that rhythmic exercise may contribute to reducing cardiovascular risk factors in elderly women.
HDL-C also demonstrated a significant group×time interaction and increased significantly only in the exercise group. HDL-C has been reported to exert neuroprotective effects through mechanisms including modulation of β-amyloid metabolism and anti-inflammatory activity in the brain [36]. In addition, epidemiological studies have suggested that lower HDL-C levels are associated with an increased risk of dementia and cerebrovascular disease [37]. Therefore, the increase in HDL-C observed in the present study may have important implications for both cardiovascular and cognitive health. Previous studies have also reported that dance-based and aerobic exercise interventions can induce beneficial metabolic adaptations and improve cardiovascular risk profiles in older adults [38]. Importantly, these findings were consistent even after adjusting for baseline differences in systolic and diastolic blood pressure.
In contrast, TG and LDL-C did not show significant interaction effects. Previous studies have suggested that improvements in these lipid markers are more likely to occur when exercise interventions are accompanied by substantial weight loss, longer intervention durations, or dietary modification [35,38]. Because dietary intake and lifestyle behaviors were not strictly controlled in the present study, these factors may have limited the magnitude of lipid profile improvements.
Chronic low-grade inflammation is widely recognized as a key contributor to vascular dysfunction, neurodegeneration, and age-related disease progression [39,40]. However, IL-6, hs-CRP, and albumin did not show significant changes following the intervention in the present study. Similar findings have been reported in previous systematic reviews and meta-analyses examining the effects of exercise interventions on inflammatory markers in older adults, where changes in biomarkers such as IL-6 and CRP were inconsistent and influenced by factors such as exercise modality, intervention duration, and baseline inflammatory status [41,42]. In the present study, the absence of significant changes in inflammatory markers may be related to several factors. Although peak exercise intensity reached relatively high levels, the average exercise intensity remained within the moderate range. In addition, participants were generally healthy older adults without elevated baseline inflammatory status, which may have limited the potential for observable reductions. Furthermore, it is possible that longer intervention durations or sustained higher exercise intensity may be required to induce significant changes in inflammatory biomarkers.
Among the dementia-related biomarkers, IGF-1 did not show significant changes. IGF-1 is a neurotrophic factor involved in neuronal survival, synaptogenesis, neurogenesis, and synaptic plasticity and has been implicated in cognitive function and brain health [43,44]. However, circulating IGF-1 responses to exercise appear to vary according to participant characteristics, exercise modality, and intervention context, and recent evidence suggests that significant increases are not consistently observed across studies [45,46]. Therefore, the absence of significant changes in IGF-1 in the present study may reflect the heterogeneous nature of exercise-induced IGF-1 responses.
In contrast, BDNF showed a significant group×time interaction and increased significantly only in the exercise group. BDNF is a key neurotrophic factor involved in neuronal survival, synaptic plasticity, learning, and memory processes [47,48]. Previous studies have demonstrated that physical activity and dance-based exercise interventions can increase circulating BDNF levels in older adults [49]. Because BDNF levels decline with aging and are associated with reduced neuroplasticity, the increase observed in the present study suggests that rhythmic exercise may help counteract age-related neurobiological decline.
Cognitive decline in older adults has been associated with reductions in cerebral blood flow and synaptic function, particularly within hippocampal networks involved in memory processes [50]. Although ADAS-Cog scores did not show a significant group×time interaction in the present study, the exercise group demonstrated a within-group improvement following the intervention. However, this finding should be interpreted with caution, as within-group changes alone do not provide sufficient evidence of intervention efficacy. While improvements in physical fitness and increased neurotrophic factors were observed, these results do not allow for a definitive conclusion regarding the effect of rhythmic exercise on cognitive function. Given that sarcopenia-related motor dysfunction has been identified as a predictor of dementia, the observed improvements in functional fitness may suggest a potential link between physical and cognitive health; however, further studies are needed to clarify this relationship.
In addition, the sample size calculation in the present study was based on a relatively large assumed effect size (η²= 0.25), which may have resulted in limited statistical power to detect smaller effects. Therefore, the absence of significant between-group differences in cognitive changes and the non-significant findings for certain biomarkers should be interpreted with caution, as the study may have been underpowered to detect subtle intervention effects.
CONCLUSION
In conclusion, the 20-week rhythmic exercise program improved several components of physical fitness and produced favorable changes in selected cardiovascular and dementia-related biomarkers, particularly HDL-C and BDNF, in elderly women. No significant group×time interaction was observed for ADAS-Cog scores, indicating that the intervention did not demonstrate a clear between-group effect on cognitive function. However, the observed within-group improvements, together with favorable changes in neurobiological markers, may suggest a potential role of rhythmic exercise in supporting cognitive-related physiological processes. Inflammatory cytokines did not change significantly following the intervention. Overall, these findings suggest that rhythmic exercise may represent a practical multimodal intervention for promoting physical health and may contribute to dementia-related physiological function. In particular, the integration of coordinated movement, rhythmic synchronization, and cognitive engagement may offer additional advantages over conventional exercise modalities, especially in addressing physical aspects of aging, while potential cognitive benefits warrant further investigation.
Notes
ACKNOWLEDGMENTS
This study was supported in part by the Korea Institute of Sport Science (KISS) under Grant No. KISS-202305-EF-039-01.
CONFLICT OF INTEREST
The authors declare no financial or commercial conflicts of interest.
AUTHOR CONTRIBUTIONS
Conceptualization: DA Kim, S Yoon; Data curation: DA Kim; Formal analysis: DA Kim, S Yoon; Funding acquisition: H Song; Methodology: DA Kim, H Song, S Yoon; Project administration: S Yoon; Visualization: DA Kim; Writing – original draft: DA Kim; Writing – review & editing: H Song, S Yoon.