Evaluation of Cognitive and Physical Function Among Older Adults by Their Physical Activity: A Cross-Sectional Kasama Study,Japan

Abstract

Background:

The amyloid-β_1-42 (Aβ₄₂) level is a biomarker that is widely used to evaluate individual cognitive dysfunction early in neurodegenerative diseases, as well as differentiate between normal cognitive function, mild cognitive impairment, Alzheimer’s disease, and vascular cognitive impairment.

Objective:

Our cross-sectional study evaluated the association between daily exercise and physical and cognitive function and Aβ₄₂ levels among a subsample of 325 older adults from the Kasama Study.

Methods:

Participants (age: 74.5 [range 65–90] years) were classified into three exercise groups: the dual-task (DEG, n = 128), single-task (SEG, n = 122), and non-exercise (NEG, n = 75) groups. The main outcomes were the plasma Aβ₄₂ levels and the scores of the five cognitive (5-COG) tests and five cognition-related physical function (5-PHYS) tests.

Results:

The Aβ₄₂ levels and 5-COG and 5-PHYS scores were higher in the SEG and DEG than in the NEG. The Aβ₄₂ levels were higher in the DEG than in the NEG (p = 0.008).

Conclusions:

Physical activities such as regular exercise may benefit older adults, improving their cognitive and physical function.

Keywords

Alzheimer’s disease amyloid-β cognitive function dual-task exercise physical function single-task exercise

INTRODUCTION

The Japanese economy achieved remarkable expansion after World War II. The Japanese Government took advantage of this momentum to enhance social security, including the provision of medical and long-term care insurance and a national pension. In 2019, life expectancy in Japan was the highest in the world, at 84.3 years [1]. As a result of longer life expectancy and declining birthrate, in 2021, 30% of the population of Japan were older adults (≥65 years of age), with the social security system in danger of collapsing. A concern of the “super-aging” Japanese society is the prevalence of dementia, which rises exponentially after the age of 65 years, with predictions that one in five people in Japan will have dementia by 2025 [2]. The other concern is the increasing prevalence of “aged care,” wherein older adults are caring for their even older family members, a trend which will persist considering the population demographics of Japan. The concept of a “healthy lifespan” has become a major goal for the Japanese Government, with increased public awareness of the importance of healthy lifestyles, including the association between physical activity (PA) and Alzheimer’s disease (AD).

Recent studies have revealed an association between AD and the deposition of extracellular senile plaques, primarily consisting of amyloid-β (Aβ), with Aβ_1-42 (Aβ₄₂) peptides in particular [3, 4], with pathological changes in AD manifesting decades before the appearance of clinical symptoms. Thus, Aβ₄₂ is a major biomarker that is widely used to evaluate individual cognitive dysfunction early in neurodegenerative diseases as well as to differentiate between normal cognitive function, mild cognitive impairment (MCI), AD, and vascular cognitive impairment [5 –7]. Recently, a minimally invasive and low-cost tool was developed to detect AD-related conditions in the preclinical stages of AD using plasma Aβ₄₂ levels [8 –11]. Careful tracking of changes in human Aβ₄₂ may, therefore, help elucidate the process from MCI to the onset of AD. Based on these findings and hypothesis, we launched the “Kasama project” in 2009. This is a mid-size, longitudinal study of individuals aged ≥65 years having different lifestyle backgrounds, with the purpose of investigating the association between physical and cognitive function for the delay or prevention of MCI and AD [12].

In its global recommendations on PA for health, the World Health Organization reported that PA interventions may have a positive influence on brain health [13]. Compared to physically inactive people, physically active people seem less likely to develop cognitive decline, all-cause dementia, vascular dementia, and AD [14 –17]. In particular, our previous studies have shown that PA, such as a dual-task (DT) exercises, improves both cognitive and physical functions [18, 19]. Therefore, investigating whether PA can modify the Aβ levels and if lower levels are associated with the delay and prevention of MCI and AD in older adults is necessary. Herein, we report on our local large-scale monitoring survey, in which we compared the plasma Aβ levels and cognitive function (attention, memory, visual space function, and abstract reasoning) between physically active (those performing single-task [ST] and DT exercises) and inactive people.

MATERIALS AND Methods

Study design and participants

We have been conducting our cross-sectional population-based survey annually since 2009 in the city of Kasama, Japan [12]. In this study, we enrolled a random sample of 325 of the 623 participants who completed the Kasama Study health check in 2019. These 325 participants were aged ≥65 years, did not require long-term care [20], and agreed to undergo a blood test to measure their plasma Aβ₄₂ levels. Individuals aged ≥91 years and those with a diagnosis of dementia of any type were excluded. After screening, 325 participants were included in the study and classified into the following three groups, based on their level of exercise (Fig. 1): the DT exercise group (DEG), including individuals who regularly practiced square-stepping exercise (SSE) at least once a week for >1 year; the ST exercise group (SEG), including individuals who performed daily exercise, such as walking, general fitness exercise, golf, and dance [21], for ≥30 min continuously, at least twice a week for >1 year (Supplementary Figure 1); and the non-exercise group (NEG), including individuals who did not exercise.

Fig. 1

The selection of participants from the cross-sectional Kasama Study and allocation of the 325 participants enrolled into the three exercise group.

Notably, the SSE, which includes both physical and cognitive tasks, uses a multidisciplinary approach to stimulate brain activity and thereby improve cognitive and physical functions [22]. In brief, the SSE is performed on a thin felt mat (250×100 cm) divided into 40 small squares (25×25 cm). The exercise technique includes forward, backward, lateral, and oblique steps, making step patterns progressively more complex. In this study, participants were required to step in the length direction (250 or 200 cm) without treading on the lines making up the squares. A total of 196 step patterns were observed and categorized from beginner to advanced.

Statement of ethics

This study was approved by the Ethics Committee of the University of Tsukuba (No. Tai 019-57). The authors confirm that trials for this intervention are registered with the University Hospital Medical Information Network Clinical Trial Registry (UMIN000032740). Participants were invited to participate by mailed letters and provided informed consent to participate in the study.

Plasma Aβ₄₂ analysis

Blood sampling was performed between 7 am and 9 am, with each participant fasting for at least 12 h. The sample was collected from the median cubital vein. The blood sample was left at room temperature for 30 min using the EDTA 2 K vacuum blood collection period until it was completely coagulated, followed by centrifugation at 3,000 rpm for 10 min. This plasma was stored at –80°C until measurement.

Plasma Aβ₄₂ levels were quantified using a sandwich-type enzyme-linked immunosorbent assay (ELISA). The ELISA kit (Human/Rat β Amyloid (42) ELISA Kit Wako (290-62601); Fujifilm, Tokyo, Japan) consists of the monoclonal antibody BNT77, epitope for Aβ (11–28), and monoclonal antibody BC05 to detect the C-terminal of Aβ₄₂. The sample (plasma) was prepared in the wells of the sample blank with a standard diluent; 100 μL of this sample was added to each well of the same lot of a 96-well ELISA plate for immobilization and refrigerated. The antigen was adsorbed onto each well after storage at 4°C for 8 h. The antigen was removed by suction, and 300 μL of washing solution was added to each well for washing. This cleaning procedure was repeated four times. Subsequently, 100 μL of the labeled antibody was added to each well, and the mixture was stored in a refrigerator (4°C) for 1 h. After washing four times, 100 μL of 3,3,5,5-tetramethylbenzidine solution was added to each well, and the mixture was incubated in the dark at room temperature for 30 min. The reaction was stopped by adding 100 μL of the reaction stop solution to each well. The absorbance of the sample, standard, and sample blank at 450 nm was measured using a microplate reader (Varioskan LUX multimode microplate reader; Thermo Fisher Scientific Inc., Waltham, MA, USA). The absorbance values for the six calibrations were used to calculate the antibody concentrations (0, 0.3, 2, 5, 10, and 20 pmol/L) using the derived calibration equations. The plasma Aβ₄₂ curve was linear in the range of 0–20 pmol/L (r² = 0.9999) with ELISA (Supplementary Figure 2).

Cognitive function evaluation by the five cognitive ability tests

Five cognitive function tests, commonly used to assess cognitive performance among older adults with normal cognition or mild cognitive impairments [23], were included, as follows: attention, memory, visuospatial function, language, abstract reasoning, and the total five cognitive (5-COG) score. Higher scores are indicative of higher cognitive abilities for each component. The reliability and validity of these tests have previously been confirmed [24, 25]. This cognitive assessment was conducted in a group setting (maximum 25 participants) by an examiner with the use of a projector. The mean length of the 5-COG examination was 35 minutes. This 5-COG test eliminated the intervention of subjective factors from the participants.

The test comprises the following five cognitive ability components:

attention is measured by executing parallel tasks and changing the order in the places where “top,” “middle,” and “bottom” are written as a character position references (score range: 0–40 points)

a cued recall test to measure memory ability, in which 32 words are memorized in categories (score range: 0–32 points)

a clock drawing test that involves drawing the clock face and measuring the visual space function (score range: 0–7 points)

an animal name listing test that measures language ability, in which as many animal names as possible are written down in 2 min (score range: 0–40 points)

an analogy test that measures abstract reasoning ability in which the broader term for two words must be given; for example, “ruby” and “diamond” would lead to “jewel” (score range: 0–16 points)

Psychological status

Psychological status was measured using the 15-item Japanese Geriatric Depression Scale (GDS-15) [26]. This is a self-report evaluation comprising 15 items, with 10 items confirming depression if the answers are positive, while the remaining five items confirming depression if the answers are negative. Normal scores range from 0 to 4 points, depending on age, education, and complaints. Scores of 5–8, 9–11, and 12–15 points indicate mild, moderate, and severe depression, respectively.

PA scale

The Japanese version of the Physical Activity Scale for the Elderly (PASE) [27] was used to assess PA variables. The PASE is a 12-item self-report questionnaire that measures the average number of hours spent in leisure time per day and household and work-related PA over a 7-day period. Leisure-time PA includes walking (for recreation and transportation); light-, moderate-, and heavy-intensity recreational activities; and muscle strength training. Household PA includes light and heavy housework, home repair, lawn work or yard care, outdoor gardening, and caring for another person. Work-related PA includes paid and voluntary work. These items are weighted based on the intensity of each activity, and the PASE (total PA) score is the sum of the 12 weighted items. In addition to the total PA score, we calculated a score for each PA type (leisure-time, household, and work-related PA).

Physical function evaluation

Five cognition-related physical function tests were evaluated: one-leg balance with eyes open [28], time to complete five repetitions of sit-to-stand [29], timed up-and-go [30, 31], 5-m habitual walk time [32], and 48-peg-moving task [33].

One-leg balance with eyes open

In measuring one-leg balance with eyes open, we recorded the time for which participants could stand on one leg up to a maximum of 60 s to evaluate static balance. Participants were allowed to choose the lifted leg.

Five-time sit-to-stand movement test

Participants were asked to sit on a chair with their arms folded over their chests and then to stand up and sit down five times as fast as possible. Pipe chairs were used for the measurements.

Timed up-and-go test

According to the modified method [2], we recorded the time taken to complete the task, with the shorter time of two trials used for analysis. Two types of pipe chairs and armchairs were used for the measurements. Participants who could not walk were provided with their walking aids.

5-m habitual walk

Participants walked at their typical speed on an 11-m straight course. We recorded the time taken to complete the task (3–8 m), with the shorter time of two trials used for analysis.

48-Peg-moving task

The peg-moving task evaluates hand dexterity (TKK1306, Takei Scientific Instruments Co. Ltd., Niigata, Japan). Participants were asked to move two pegs simultaneously from the distal board to the proximal board using both hands as quickly as possible. We recorded the time required for participants to finish moving 48 pegs.

DT exercise (SSE)

The SSE, which includes both physical and cognitive tasks, uses a multidisciplinary approach to stimulate brain activity, thereby improving cognitive and physical functions [34]. In brief, SSE is performed on a thin felt mat (250×100 cm) divided into 40 small squares (25×25 cm). The exercise includes forward, backward, lateral, and oblique steps, making step patterns progressively more complex. Participants were required to step in the length direction (250 or 200 cm) without treading on lines delineating the squares. The 196 step patterns were categorized from beginner to advanced levels. In every trial, each SSE mat was divided into small groups of four to five, and the intervention was carried out in each group. After a 10-min warm-up of breathing and flexibility exercises for the upper and lower body, a 60-min SSE followed. The program ended with a 5-min cool down with breathing and stretching exercises. After 6 months of intervention, two mats were connected (500×100 cm), and the difficulty level was increased.

Statistical analyses

All analyses were performed using SPSS (version 26, IBM Corp., Armonk, NY, USA), with significance set at a p-value of <0.05. The normality of data distribution was evaluated using the Shapiro–Wilk test. Continuous variables were reported as means (ranges), and categorical variables are reported as counts and proportions. The chi-square test was used to evaluate between-group differences for categorical variables, and an analysis of variance (ANOVA) was used to evaluate the association among continuous variables, namely plasma Aβ₄₂ levels and cognitive and physical function test scores.

RESULTS

Participants

The mean (range) age and body mass index (BMI) of the participants in each of the three groups were as follows: DEG, 73.8 (range, 65–88) years and 23.1 (range, 15.8–30.6) kg/m²; SEG, 74.4 (range, 65–88) years and 22.4 (range, 14.9–31.5) kg/m²; and NEG, 75.4 (range, 65–90) years and 23.7 (range, 17.9–31.1) kg/m², respectively (Table 1, Supplementary Figure 3). Although there was a significant between-group difference in BMI, all participants were within the Japanese reference range of BMI per age (18.5–25 kg/m²). There was a higher proportion of women than men in all groups, and in the DEG in particular (p < 0.001), which is consistent with the higher proportion of women in Japan who participate in athletic activities (Supplementary Figure 4): DEG, 79.7%; SEG, 59.0%; and NEG, 58.7%. The groups were balanced in all other characteristics (Supplementary Figures 5 and 6).

Table 1

Characteristics of participants by group

	DEG (n = 128)		SEG (n = 122)		NEG (n = 75)		p
	Range	Mean (SD)	Range	Mean (SD)	Range	Mean (SD)
Age (y)	65–88	73.8 (5.0)	65–88	74.4 (4.8)	65–90	75.4 (5.4)	0.112^†
Height (cm)	137.3–175.8	154.4 (7.6)	136.9–176.2	156.5 (7.9)	131.9–173.5	155.7 (9.1)	0.119^†
Body weight (kg)	38.9–81.7	54.8 (8.5)	32.4–84.5	54.9 (9.8)	40.0–87.0	57.6 (10.0)	0.080^†
Body mass index (kg/m2)	15.8–30.6	23.1 (2.8)	14.9–31.5	22.4 (3.0)	17.9–31.1	23.7 (3.0)	0.006^†
Education (y)	9–22	12.1 (2.4)	6–20	12.2 (2.1)	9–22	12.0 (2.4)	0.825^†
Women (n (%))	102 (79.7)		72 (59.0)		44 (58.7)		<0.001^a
Syatolic blood pressure (mmHg)	94–183	141.4 (17.1)	92–204	139.6 (18.4)	102–183	138.5 (18.1)	0.504^†
Diastolic blood pressure (mmHg)	57–116	80.6 (11.0)	52–105	78.4 (10.6)	49–102	79.5 (10.9)	0.278^†
Heart Rate (bpm)	47–115	76.8 (12.0)	52–108	74.8 (11.2)	51–111	78.1 (12.7)	0.170^†
Alcohol consumption (n, %)							0.113^a
Never	85 (66.4)		69 (56.5)		45 (60.0)
Few days a month	13 (10.2)		8 (6.6)		10 (13.3)
Once or more a week	30 (23.4)		45 (36.9)		20 (26.7)
Current smoker	3 (2.3)		2 (1.6)		4 (5.3)		0.277^a
Take a Medicine
Antihypertensive (n (%))	64 (50.0)		50 (41.0)		37 (49.3)		0.289^a
Cholesterol (n (%))	30 (23.4)		23 (18.9)		18 (24.0)		0.579^a
Diabetes (n (%))	14 (10.9)		14 (11.5)		9 (12.0)		0.966^a
Cerebrovascular (n (%))	7 (5.5)		11 (9.0)		8 (10.7)		0.355^a
Blood viscous reducer (n (%))	3 (2.3)		7 (6.3)		3 (4.0)		0.394^a

^†Each value is presented as the mean±standard deviation. The p-value for between-group differences was calculated using ^†an analysis of variance for continuous variables and ^athe chi-squared (χ²) tests for categorical variables. DEG, dual-task exercise group; SEG, single-task exercise group; NEG, non-exercise group.

Plasma Aβ₄₂ levels

The mean plasma Aβ₄₂ levels were significantly different among the three groups (p = 0.008): DEG, 5.47 pmol/L; SEG, 4.37 pmol/L; and NED, 3.61 pmol/L (Table 2; Fig. 2a). On post-hoc analysis, the levels were higher in the DEG than in the NEG.

Table 2

Plasma Aβ1-42, cognitive function (five cognitive ability tests), psychological status, and physical activity by groups

	Unit	Group	n	Range	Mean (SD)	p	Post-hoc
Blood test
Plasma Aβ_1-42	pmol/L	DEG^a	128	0.02–29.12	5.47 (4.66)	0.008	c < a
		SEG^b	122	0.02–20.94	4.37 (4.05)
		NEG^c	75	0.02–15.75	3.61 (3.66)
Cognitive function (Five-cog test)
Character position referencing (attention)	score	DEG^a	128	1–40	26.1 (6.4)	0.102	–
		SEG^b	122	0–39	24.4 (7.9)
		NEG^c	75	2–39	24.2 (7.0)
Cued recall (memory)	score	DEG^a	128	6–32	21.7 (6.3)	<0.001	b, c < a
		SEG^b	122	2–32	19.1 (7.0)
		NEG^c	75	2–32	17.4 (7.0)
Clock drawing (visuospatial function)	score	DEG^a	128	2–7	6.8 (0.7)	0.051	–
		SEG^b	122	2–7	6.6 (0.9)
		NEG^c	75	5–7	6.7 (0.7)
Animal name listing (language ability)	score	DEG^a	128	6–38	20.0 (5.8)	0.001	c < a
		SEG^b	122	5–39	18.5 (5.6)
		NEG^c	75	9–36	16.9 (5.0)
Analogy (abstract reasoning ability)	score	DEG^a	128	3–16	11.9 (3.0)	0.521	–
		SEG^b	122	0–16	11.5 (3.8)
		NEG^c	75	3–16	11.4 (3.2)
Total	score	DEG^a	128	37–132	86.5 (16.6)	0.001	b, c < a
		SEG^b	122	13–124	80.0 (20.2)
		NEG^c	75	27–130	76.7 (18.2)
Psychological status and physical activity
Geriatric Depression Scale	score	DEG^a	128	0–13	2.7 (2.5)	0.003	a, b < c
		SEG^b	122	0–11	3.1 (2.6)
		NEG^c	75	0–14	4.1 (3.4)
Leisure Time Physical Activity	score	DEG^a	128	0–120.2	26.7 (22.4)	<0.001	c < a, b
		SEG^b	122	0–144.9	31.0 (28.2)
		NEG^c	75	0–107.3	13.5 (19.3)
Household Physical Activity	score	DEG^a	128	0–171	85.9 (33.4)	0.280	–
		SEG^b	122	0–171	91.3 (35.2)
		NEG^c	75	0–171	83.7 (37.8)
Occupational Physical Activity	score	DEG^a	128	0–90	7.6 (17.9)	0.356	–
		SEG^b	122	0–168	10.0 (26.3)
		NEG^c	75	0–150	12.28 (30.5)
Total Physical Activity	score	DEG^a	128	34.6–281.7	120.1 (47.2)	0.017	c < b
		SEG^b	122	11.1–368.6	131.7 (57.3)
		NEG^c	75	0–248.3	108.5 (58.0)

Values are presented as the mean (standard deviation). Lowercase letters (a, b, and c) indicate significant differences between the groups (p < 0.05) on the multiple comparisons test with Bonferroni adjustment. Physical activity: physical activity in the elderly; Geriatric Depression Scale: Normal scores range from 0 to 4 points, depending on factors, such as age, education, and complaints; scores of 5–8, 9–11, and 12–15 points indicate mild moderate, and severe depression, respectively. DEG, dual-task exercise group; SEG, single-task exercise group; NEG, non-exercise group.

Fig. 2

Violin plots of individual plasma Aβ₄₂ levels (a) and five cognitive-functional test scores (b) for each exercise group (NEG, SEG, and DEG). The maximum density of the group-specific distribution is indicated by the largest width of the violin plots. DEG, dual-task exercise group; SEG, single-task exercise group; NEG, non-exercise group.

Cognitive function

There were significant between-group differences in memory (p < 0.001), language ability (p = 0.001), and the cognitive total score (p = 0.001; Table 2; Fig. 2b). Post-hoc analyses indicated higher scores in the DEG than in the SEG and NEG, except for attention and abstract reasoning ability.

Psychological status and PA

There was a between-group difference in the Japanese GDS-15 score (p = 0.003) (Table 2, Supplementary Figure 7). Although the GDS score was within the normal range for all groups, the mean NEG score of 4.1 points did exceed the 0–4-point normal range. The PA total score was the highest for the SEG. Leisure (p < 0.001) and total (p = 0.017) PA was significantly different between the groups (Table 2, Supplementary Figure 8). Post-hoc analysis revealed that leisure-time PA was higher in the DEG and SEG than in the NEG, with total PA being higher in the SEG than in the NEG.

Physical function

There were between-group differences (p < 0.05) in all physical function items (Table 3, Fig. 3). Times were shorter for the DEG and SEG than for the NEG, with the exception of one-leg balance with eyes open.

Table 3

Physical function (five physical ability tests) by groups

	Unit	Group	n	Range	Mean (SD)	p	Post-hoc
One leg balance with eyes open	s	DEG^a	128	1.4–60	39.0 (20.4)	0.016	c < a
		SEG^b	122	2.0–60	36.7 (21.6)
		NEG^c	75	1.3–60	30.2 (21.2)
5-times sit-to-stand	s	DEG^a	128	3.66–10.14	6.14 (1.29)	<0.001	a < b < c, a < c
		SEG^b	122	4.33–12.06	7.03 (1.71)
		NEG^c	75	5.35–13.56	7.74 (1.65)
Timed up and go	s	DEG^a	128	4.06–10.91	5.47 (0.97)	<0.001	a, b < c
		SEG^b	122	3.71–9.92	5.61 (1.02)
		NEG^c	75	4.43–10.17	6.09 (1.14)
5-m habitual walk	s	DEG^a	128	2.45–6.21	3.48 (0.60)	0.002	a, b < c
		SEG^b	122	2.48–5.6	3.43 (0.54)
		NEG^c	75	2.25–5.81	3.73 (0.66)
48-peg moving	s	DEG^a	128	25.98–45.31	33.23 (3.72)	<0.001	a < b, c
		SEG^b	122	28.3–52.62	35.79 (4.51)
		NEG^c	75	26.97–51.62	36.49 (4.49)

Values are presented as means (standard deviations). Lowercase letters (a, b, and c) indicate significant differences between the groups (p < 0.05) on the multiple comparisons test with Bonferroni adjustment. DEG, dual-task exercise group; SEG, single-task exercise group; NEG, non-exercise group.

Fig. 3

Violin plots of individual scores for each of the five physical function tests and variant number for each exercise group (NEG, SEG, and DEG). The maximum density of the group-specific distribution is indicated by the largest width of the violin plots. DEG, dual-task exercise group; SEG, single-task exercise group; NEG, non-exercise group.

DISCUSSION

In this study, we evaluated the association between daily exercise and physical and cognitive function and Aβ₄₂ levels. Understanding the possible benefits of regular PA for plasma Aβ₄₂ levels and cognitive function, including MCI and AD, among older individuals is important within the context of Japan, considering the increasing prevalence of dementia [2]. This was our goal in implementing the Kasama Study. In our current study of a random sample of 325 individuals from the 2019 Kasama Study cohort, we demonstrate the benefits of regular exercise, with better outcomes generally obtained with DT than with ST exercises.

Recently, Aβ₄₂ level has been used as a major biomarker for the diagnosis and prediction of MCI or AD [8 –11]. Compared to other AD analysis methods, such as functional magnetic resonance imaging (fMRI), fluorodeoxyglucose (FDG)-positron emission tomography (PET), and MALDI-TOFMS, ELISA for Aβ₄₂ analysis, as a cost-effective and convenient tool for evaluating personal cognitive function, has been attracting research and clinical attention. Additionally, fMRI and FDG-PET can only help diagnose AD after the shape of the brain has been significantly deformed. However, the ELISA method is an attractive tool to know the individual level of Aβ₄₂ even before the onset of AD.

In our study, the plasma Aβ₄₂ levels were higher in the DEG and SEG than in the NEG (Table 2, Fig. 2a), and particularly higher in the DEG than in the NEG (p = 0.008). The higher levels of plasma Aβ₄₂ in the regular exercise group may indicate a reduced deposition of Aβ₄₂ in the brain. Aβ₄₂ deposition in the brain predicts AD diagnosis and disease progression, based on the JADNI PiB PET judgment [35]. This might explain the positive association between higher plasma Aβ₄₂ levels and improved/maintained cognitive function and, thus, the positive effects of regular exercise on cognitive function among older individuals. Exercise could also decrease the deposition of Aβ₄₂ in the brain, protecting against cognitive dysfunction, including MCI and AD.

The finding of higher plasma Aβ₄₂ levels and better cognitive function scores in the DEG than in the SEG underlines the potential benefit of a multicomponent program of PA, such as DT exercises, compared to ST exercises, such as walking, general fitness exercises, golfing, and dancing. These findings are consistent with those previously reported [36] and the World Health Organization recommendations for regular PA to improve physical fitness (cardiovascular system, bone, and muscle) and mental health (emotional functioning, depression, mood, cognitive functioning, and social functioning) among older adults. While the benefits of PA among healthy older adults and those with cognitive impairment, including MCI and AD, have been studied [14–17 , 37], the effectiveness of PA in the progression of MCI and AD remains unclear. In this regard, to our knowledge, this study is the first to show the possibility of reducing MCI and AD based on a quantitative increase in plasma Aβ₄₂ levels associated with regular PA. This is consistent with the findings of a previous study showing an association between PA and cognition [18, 19].

In the five cognitive test that we used, individuals who regularly exercised (DEG and SEG) had remarkably higher scores for all items than did those in the NEG. Exercise was particularly beneficial for memory and language ability, which reflect the function of the frontal region of the brain for memory and language function. In general, cognitive function is closely associated with physical function. SSE, which includes movement, appears to be an important component of DT exercise to enhance the activation of the frontal, temporal, parietal, and occipital lobes and thus exert a greater benefit for cognitive function than ST exercise (Fig. 1). This is consistent with the findings from previous studies [18 , 39]. Thus, cognitive-motor DT exercise is an emerging modality for health and cognitivebenefits.

In terms of the psychological status, the GDS-15 scores were remarkably lower in the NEG than in the DEG and SEG. PA can effectively ameliorate mental health among older adults and the social interaction in PA likely contributes to this mental health benefit of PA. We also found that leisure-time PA had a positive effect on mental health (p < 0.001) because it is enjoyable.

Concerning physical function, performance scores were specifically higher in the DEG and SEG than in the NEG for movement tasks having a cognitive component. As an example, the timed up-and-go test includes a measure of both mobility and risk of falling, being strongly associated with cognitive capacity [40]. The other tests we used in our assessment also have an association with cognitive capacity: the one-leg balance with eyes open [28], sit-to-stand [29], and 5-m walk [32] tests. Similarly, performance in the peg-board test, which measures manual dexterity [41 –43], was also faster in the DEG than in the SEG and NEG (p < 0.001). This might reflect the benefit of PA for higher brain activation levels, resulting in faster peg number recognition (cognition) and movement. The group of physical function tests that we used could complement each other and are practical to use.

Our findings suggest that regular PA among older adults benefits physical and cognitive function. Although our findings are novel and promising, the results of the obtained phenomenon (plasma Aβ₄₂, 5-COG test scores, psychological status, PA, and physical function) are not direct evidence for the mechanism of the cognitive change and whole brain function changes. Thus, the findings of this study have to be seen in light of some limitations. Future research is warranted to clarify the mechanisms underlying the interaction between the PA and Aβ₄₂ levels in the human brain, quantified by fMRI/FDG-PET. Moreover, a quantitative method to measure plasma Aβ₄₂ levels by MALDI-TOFMS is needed to cross-check the results with ELISA and gather strong evidence for understanding cognitive function changes. Therefore, we plan to continue evaluating the changes in all physical function items in the follow-up periods of the Kasama Study every 2 years.

The results of this study confirmed that cognitive-motor DT exercise is effective; however, this effect was not limited to exercise, it may also impact human lifestyle, food intake, and health status (mental health). In the future, it is necessary to verify DT exercise effects by considering human lifestyle, food intake, and health status (mental health). Furthermore, it will be necessary to verify the synergistic effects of multidomain interventions integrated with lifestyle habits.

To the best of our knowledge, this was the first study to evaluate the relationship between PA, cognitive function, and plasma Aβ₄₂ levels among older adults. We identified that regular PA and DT and ST exercises are beneficial for plasma Aβ₄₂, cognitive function, mental health, and physical ability compared to inactivity. Therefore, PA habits, particularly DT exercise, can be beneficial for cognitive function and mental health among older individuals. Thus, the promotion of regular exercise might have a central role in health promotion in the super-aging society in Japan. Future research should include longitudinal studies of exercise and blood (or brain) amyloid levels to perform intervention trials with the amyloid level as the primary outcome measure.

Footnotes

ACKNOWLEDGMENTS

The authors acknowledge the participants, their families, and all staff who assisted in this study for their dedication, cooperation, and perseverance.

FUNDING

This study was supported by JSPS KAKENHI Grant Number 18K17958 and JST Grant Number JPMJPF2017.

CONFLICT OF INTEREST

The authors have no conflict of interest to report.

DATA AVAILABILITY

The data will be made available upon reasonable request.

The supplementary material is available in the electronic version of this article: .

References

World Health Organization (2021) World health statistics 2021: monitoring health for the SDGs, sustainable development goals https://www.who.int/publications/i/item/9789240027053.

Cabinet Office (2017) Health and Welfare of the Elderly, Annual Report on the Aging Society: 2017 . Government of Japan. https://www8.cao.go.jp/kourei/english/annualreport/2017/2017pdf_e.html.

Pesini

, Pérez-Grijalba

, Monleón

, Boada

, Tárraga

, Martínez-Lage

, San-José

, Sarasa

(2012) Reliable measurements of the β-amyloid pool in blood could help in the early diagnosis of AD. Int J Alzheimers Dis 2012, 604141.

Shanthi

, Krishnan

, Rani

(2015) A systematic review and meta-analysis of plasma amyloid 1-42 and tau as biomarkers for Alzheimer’s disease. SAGE Open Med 3, 2050312115598250.

Park

, Seo

, Kim

, Jeon

, Lee

, Oh

, Kim

, Choe

, Lee

, Shin

, Kim

, Noh

, Cho

, Yoon

, Kim

, Ye

, Ewers

, Weiner

, Lee

, Werring

, Na

(2014) Effects of cerebrovascular disease and amyloid beta burden on cognition in subjects with subcortical vascular cognitive impairment. Neurobiol Aging 35, 254–260.

Kim

, Yang

, Kwon

, Kim

, Lee

, Chun

, Kim

, Jung

, Chin

, Kim

, Woo

, Choe

, Lee

, Kim

, Lee

, Weiner

, Na

, Seo

(2016) Relative impact of amyloid-β, lacunes, and downstream imaging markers on cognitive trajectories. Brain 139, 2516–2527.

Kim

, Im

, Kwon

, Lee

, Kim

, Jung

, Cho

, Ye

, Noh

, Kim

, Ko

, Kim

, Choe

, Lee

, Kim

, Lee

, Ewers

, Weiner

, Na

, Seo

(2015) Clinical effect of white matter network disruption related to amyloid and small vessel disease. Neurology 85, 63–70.

Molinuevo

, Ayton

, Batrla

, Bednar

, Bittner

, Cummings

, Fagan

, Hampel

, Mielke

, Mikulskis

, O’Bryant

, Scheltens

, Sevigny

, Shaw

, Soares

, Tong

, Trojanowski

, Zetterberg

, Blennow

(2018) Current state of Alzheimer’s fluid biomarkers. Acta Neuropathol 136, 821–853.

Hampel

, O’Bryant

, Molinuevo

, Zetterberg

, Masters

, Lista

, Kiddle

, Batrla

, Blennow

(2018) Blood-based biomarkers for Alzheimer disease: Mapping the road to the clinic. Nat Rev Neurol 14, 639–652.

10.

O’Bryant

, Mielke

, Rissman

, Lista

, Vanderstichele

, Zetterberg

, Lewczuk

, Posner

, Hall

, Johnson

, Fong

, Luthman

, Jeromin

, Batrla-Utermann

, Villarreal

, Britton

, Snyder

, Henriksen

, Grammas

, Gupta

, Martins

, Hampel

(2017) Blood-based biomarkers in Alzheimer disease: Current state of the science and a novel collaborative paradigm for advancing from discovery to clinic. Alzheimers Dement 13, 45–58.

11.

Nakamura

, Kaneko

, Villemagne

, Kato

, Doecke

, Doré

, Fowler

, Li

, Martins

, Rowe

, Tomita

, Matsuzaki

, Ishii

, Arahata

, Iwamoto

, Ito

, Tanaka

, Masters

, Yanagisawa

(2018) High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature 554, 249–254.

12.

Okura

, Tsuji

, Tsunoda

, Kitano

, Yoon

, Saghazadeh

, Soma

, Yoon

, Kim

, Jindo

, Shen

, Abe

, Sato

, Kunika

, Fujii

, Sugahara

, Yano

, Mitsuishi

(2017) Study protocol and overview of the Kasama Study: Creating a comprehensive, community-based system for preventive nursing care and supporting successful aging. J Sports Med Phys Fitness 6, 49–57.

13.

World Health Organization (2019) Risk reduction of cognitive decline and dementia: WHO guidelines Accessed on January 1 2019. https://www.who.int/publications/i/item/9789241550543.

14.

Gallaway

, Miyake

, Buchowski

, Shimada

, Yoshitake

, Kim

, Hongu

(2017) Physical activity: A viable way to reduce the risks of mild cognitive impairment, Alzheimer’s disease, and vascular dementia in older adults. Brain Sci 7, 22.

15.

Hamer

, Chida

(2009) Physical activity and risk of neurodegenerative disease: A systematic review of prospective evidence. Psychol Med 39, 3–11.

16.

Sofi

, Valecchi

, Bacci

, Abbate

, Gensini

, Casini

, Macchi

(2011) Physical activity and risk of cognitive decline: A meta-analysis of prospective studies. J Intern Med 269, 107–117.

17.

Stephen

, Hongisto

, Solomon

, Lönnroos

(2017) Physical activity and Alzheimer’s disease: A systematic review. J Gerontol A Biol Sci Med Sci 72, 733–739.

18.

Yoon

, Isoda

, Okura

(2020) Evaluation of beneficial effect of a dual-task exercise based on Japanese transitional games in older adults: A pilot study. Aging (Albany NY) 12, 18957–18969.

19.

Yoon

, Isoda

, Ueda

, Okura

(2022) Cognitive and physical benefits of a game-like dual-task exercise among the oldest nursing home residents in Japan. Alzheimers Dement (N Y) 8, e12276.

20.

Fujii

, Seol

, Joho

, Liu

, Inoue

, Nagata

, Okura

(2021) Associations between exercising in a group and physical and cognitive functions in community-dwelling older adults: A cross-sectional study using data from the Kasama Study. J Phys Ther Sci 33, 15–21.

21.

Ministry of Health Law (2018), Health Japan 21 .

22.

Shigematsu

, Okura

(2006) A novel exercise for improving lower-extremity functional fitness in the elderly. Aging Clin Exp Res 18, 242–248.

23.

Yatomi

, Asada

(2006) A mass cognitive test for the elderly: Development of Five Cog Test. Psychogeriatrics 6, A58.

24.

Sugiyama

, Mutsuo

, Sakuma

, Fumiko

, Kae

, Chiaki

, Hiroki

, Tsuyoshi

, Naomi

, Haruyasu

, Yoshinori

, Ryutaro

, Shuichi

(2015) Reliability and validity of the Five Cognitive Test in the context of detecting older people with mild cognitive impairment living in the community. Rhonen Seishin Igaku Zasshi 26, 183–195.

25.

Hanaoka

, Muraki

, Ede

, Yasuhara

, Okamura

(2018) Effects of olfactory stimulation on reminiscence practice in community-dwelling elderly individuals. Psychogeriatrics 18, 283–291.

26.

Burke

, Roccaforte

, Wengel

(1991) The short form of the Geriatric Depression Scale: A comparison with the 30-item form. J Geriatr Psychiatry Neurol 4, 173–178.

27.

Hagiwara

, Ito

, Sawai

, Kazuma

(2008) Validity and reliability of the Physical Activity Scale for the Elderly (PASE) in Japanese elderly people. Geriatr Gerontol Int 8, 143–151.

28.

Rolland

, Abellan van Kan

, Nourhashemi

, Andrieu

, Cantet

, Guyonnet-Gillette

, Vellas

(2009) An abnormal “one-leg balance” test predicts cognitive decline during Alzheimer’s disease. J Alzheimers Dis 16, 525–531.

29.

Bullain

, Corrada

, Shah

, Mozaffar

, Panzenboeck

, Kawas

(2013) Poor physical performance and dementia in the oldest old: The 90+ study. JAMA Neurol 70, 107–113.

30.

Ibrahim

, Singh

DKA

, Shahar

(2017) ‘Timed Up and Go’ test: Age, gender and cognitive impairment stratified normative values of older adults. PLoS One 12, e0185641.

31.

Pondal

, del Ser

(2008) Normative data and determinants for the timed “up and go” test in a population-based sample of elderly individuals without gait disturbances. J Geriatr Phys Ther 31, 57–63.

32.

Chou

, Nishita

, Nakagawa

, Tange

, Tomida

, Shimokata

, Otsuka

, Chen

, Arai

(2019) Role of gait speed and grip strength in predicting 10-year cognitive decline among community-dwelling older people. BMC Geriatr 19, 186.

33.

Yoon

, Himori

(2012) The relationship between pegboard test and P300 in older adults [in Japanese]. Japan Soc Exerc Sports Physiol 19, 13–21.

34.

da Silva

, Iop

RDR

, de Oliveira

, Boll

, de Alvarenga

JGS

, Gutierres Filho

PJB

, de Melo

LMAB

, Xavier

, da Silva

(2018) Effects of physical exercise programs on cognitive function in Parkinson’s disease patients: A systematic review of randomized controlled trials of the last 10 years. PLoS One 13, e0193113.

35.

Shiino

, Shirakashi

, Ishida

, Tanigaki

, Japanese Alzheimer’s Disease Neuroimaging Initiative (2021) Machine learning of brain structural biomarkers for Alzheimer’s disease (AD) diagnosis, prediction of disease progression, and amyloid beta deposition in the Japanese population. Alzheimers Dement (Amst) 13, e12246.

36.

Srinivas

, Vimalan

, Padmanabhan

, Gulyás

(2021) An overview on cognitive function enhancement through physical exercises. Brain Sci 11, 1289.

37.

Rovio

, Spulber

, Nieminen

, Niskanen

, Winblad

, Tuomilehto

, Nissinen

, Soininen

, Kivipelto

(2010) The effect of midlife physical activity on structural brain changes in the elderly. Neurobiol Aging 31, 1927–1936.

38.

Falbo

, Condello

, Capranica

, Forte

, Pesce

(2016) Effects of physical-cognitive dual task training on executive function and gait performance in older adults: A randomized controlled trial. Biomed Res Int 2016, 5812092.

39.

Tait

, Duckham

, Milte

, Main

, Daly

(2017) Influence of sequential vs. simultaneous dual-task exercise training on cognitive function in older adults. Front Aging Neurosci 9, 368.

40.

Alexandre

, Meira

, Rico

, Mizuta

(2012) Accuracy of Timed Up and Go Test for screening risk of falls among community-dwelling elderly. Rev Bras Fisioter 16, 381–388.

41.

Kellor

, Frost

, Silberberg

, Iversen

, Cummings

(1971) Hand strength and dexterity. Am J Occup Ther 25, 77–83.

42.

Abe

, Jindo

, Soma

, Tsunoda

, Kitano

, Yoon

, Okura

(2015) Validity and reliability of the “Trail Making Peg” test as a performance measurement for evaluating the cognitive function [in Japanese]. Nihon Ronen Igakkai Zasshi 52, 71–78.

43.

Tomohoro

, Ji-yeong

(2015) A novel performance test for evaluating cognitive function in older adults: Trail making peg test. Japan Soc Test Meas Health Phys Educ 14, 59–68.

Evaluation of Cognitive and Physical Function Among Older Adults by Their Physical Activity: A Cross-Sectional Kasama Study,Japan

Abstract

Background:

Objective:

Methods:

Results:

Conclusions:

Keywords

INTRODUCTION

MATERIALS AND Methods

Study design and participants

Statement of ethics

Plasma Aβ42 analysis

Cognitive function evaluation by the five cognitive ability tests

Psychological status

PA scale

Physical function evaluation

One-leg balance with eyes open

Five-time sit-to-stand movement test

Timed up-and-go test

5-m habitual walk

48-Peg-moving task

DT exercise (SSE)

Statistical analyses

RESULTS

Participants

Plasma Aβ42 levels

Cognitive function

Psychological status and PA

Physical function

DISCUSSION

Footnotes

ACKNOWLEDGMENTS

FUNDING

CONFLICT OF INTEREST

DATA AVAILABILITY

References

Plasma Aβ₄₂ analysis

Plasma Aβ₄₂ levels