Exploring the association between physical activity and cognitive function among people living with dementia

Abstract

Background

Physical activity preserves cognitive function in people without dementia, but the relationship between physical activity and cognitive domains among people living with dementia is unclear.

Objective

The objective of this study was to explore the association between physical activity and cognition domains among people living with dementia.

Methods

Participants living with dementia in residential care facilities (complete case analysis: n = 24/42) completed a battery of cognitive tests (global cognition: Montreal Cognitive Assessment; executive function: Trail-Making Test, Digit Span Forward Test; perception and orientation: Benton Judgement of Line Orientation Test; language: Boston Naming Test; learning and memory: Rey Auditory Verbal Learning Test; complex attention: Digit Symbol Substitution Test). Participants wore an actigraphy monitor on their non-dominant wrist over seven days. We conducted a linear regression for total physical activity (independent variable) with race (white/black), fall risk (Morse Fall Scale), and the number of comorbidities (Functional Comorbidities Index) as covariates, and cognitive tests as variables of interest.

Results

Participants were primarily male (75%), white (87.5%), and 50%had unspecified dementia (Alzheimer’s disease: 33%). Greater physical activity was associated with poorer global cognition, better executive function, and better learning and memory (p_s < 0.05). Physical activity was not related to visuospatial perception, language, or complex attention.

Conclusions

Physical activity may preserve executive function and learning and memory among people living with dementia. Wandering is more common in later stages of dementia, which may explain greater physical activity observed with lower global cognition. Regularly assessing physical activity may be useful in screening and monitoring cognitive changes.

Keywords

Accelerometry actigraphy Alzheimer’s disease cognition cognitive domains dementia physical activity

Introduction

Dementia is a major public health concern due to the rising number of cases among the aging population.^1,2 In 2019, the global healthcare expenditure of dementia was $1.3 trillion, which is projected to dramatically increase in the coming years.¹ The main reason for this increase in healthcare use is that people living with dementia experience poorer health outcomes and greater healthcare disparities than those without dementia.^3–6 For instance, people living with dementia experience poorer physical function,³ behavioral and psychological symptoms,⁴ poorer quality of life,⁴ and reduced access to healthcare⁵ than those without dementia. There is also a lack of evidence to suggest that therapeutic interventions effectively reduce falls among people living with dementia.⁶ Therefore, there is an imminent need to alleviate the individual and economic impact of dementia.

The diagnosis of dementia is often based on symptoms and abnormality of imaging, which typically do not occur until later stages of dementia.² Early detection and treatment of asymptomatic dementia is a public health priority because undiscovered or delayed diagnoses impact caregivers, as well as the functional independence and quality of life of the person living with dementia.^7,8 Identifying objective measures to detect and monitor cognitive and physical decline in daily living environments among people living with dementia should be a frontline priority.

One objective and sensitive measure of cognitive decline that is gaining attention is monitoring physical activity levels.⁹ A growing body of literature indicates that there is a reduced risk for age-related cognitive decline and dementia in physically active people.^10,11 Most of the research to date has examined how physical activity and exercise affect cognition in people without dementia, and they seem to have differential effects on specific cognitive domains.^12–18 The six cognitive domains include executive function, perceptual-motor function, language, learning and memory, complex attention, and social cognition, with global cognition encapsulating each cognitive domain.¹⁹ Empirical evidence suggests that global cognition, executive function, complex attention, perception and orientation, and learning and memory are related to physical activity and structured exercise among cognitively intact older adults and those with mild cognitive impairment.^12–17,20 Studies examining the relationship between physical activity and the language as well as social cognition domains are limited but do not seem to support an association.^14,18 While more research is needed to better understand how physical activity relates to specific domains of cognition among healthy older adults and those with mild cognitive impairment, there is even less research examining this relationship among people living with dementia.

It appears that global cognition and executive function may be related to structured exercise or physical activity among people living with dementia, but findings conflicting. A recent meta-analysis found a small but meaningful effect of structured exercise on global cognition; however, exercise did not improve any other cognitive domains among people living with dementia.²¹ Another recent meta-analysis found that structured exercise had a small but meaningful effect on executive function, with planning as a significant moderator.²² Less research has examined unstructured physical activity but has revealed a link between greater physical activity and better executive function among people living with Alzheimer’s disease.²³ However, physical activity was quantified using the Physical Activity Scale for the Elderly questionnaire, rather than objectively measured physical activity.²³ Conversely, others have found that standard neuropsychological tests were not significant predictors of physical activity using actigraphy among people living with dementia.⁹ Accordingly, further research is needed to resolve these discrepancies and better understand the relationship between physical activity and global cognition and its specific cognitive domains to provide insight into potential avenues for early detection and rehabilitation. To fill this knowledge gap, the purpose of this study was to examine the relationship between continuous home monitoring of physical activity and cognitive domains among people living with dementia in residential care facilities.

Methods

Study design

This is a cross-sectional, descriptive, correlational study using the baseline data collected from our randomized controlled trial aimed to examine the influence of exercise on executive function and other health outcomes among people living with dementia in residential care facilities.²⁴ Randomization to these groups occurred after the baseline assessment, and assessors were blinded to group assignment.

Study setting

Participants were locally recruited from one nursing home and one assisted living facility. These residential care facilities accommodated space for the assessments and access to medical files.

Ethics approval and consent/assent to participate

We contacted legally authorized representatives of eligible residents, and they provided hand-written informed consent in-person, via email, or by mail. Once informed consent was obtained, we obtained hand-written assent from the people living with dementia. All protocols were approved by the Institutional Review Board at Augusta University.

Eligibility criteria

We included participants if they: 1) were aged 55 years and older; 2) resided in a residential care facility; 3) had any type of dementia confirmed by medical records and/or a physician; 4) could read, write, and speak English with acceptable visual and auditory acuity; 5) were able to walk 3 meters with or without the assistance of another person; 6) had a legally authorized representative who can provide informed consent; 7) were able to provide assent, 8) were able to understand and follow instructions, and 9) had a life expectancy of ≥12 months as estimated by a physician or registered nurse. We excluded those: 1) with mild cognitive impairment; 2) who were not able to follow instructions; 3) with a severe psychiatric condition; 4) with a progressive neurological disease other than dementia (i.e., neurological disease, such as Parkinson’s disease, that is mild and stable was not an exclusion); 5) with delirium; 6) with an acute medical condition; 7) with a medical condition precluding exercise (e.g., unstable cardiac disease); 8) with recent surgery affecting mobility; 9) who were enrolled in another research study; 10) with severe blindness; 11) with severe aphasia such that they could not communicate; or 12) receiving hospice care.

Procedures

Demographics

To describe study participants and control for confounding factors, we collected demographic variables, such as age, sex, race, medication details, dementia type, and time since dementia onset from participants’ charts. The selected clinical variables were comorbidity and fall risk. Comorbidity was assessed using the Functional Comorbidity Index (FCI), which includes 18 medical conditions. It has excellent inter-rater reliability and has predictive power for long-term physical health and health-related quality of life.^25,26 Fall risk was assessed by the Morse Fall Scale (MSF)— a 6-item measure consisting of history of falling, secondary diagnosis, ambulatory aids, intravenous therapy, gait, and mental status. A score of 0–24 indicates no risk, 25–30 indicates low risk, and ≥51 indicates high risk, with a maximum score of 125 points. This assessment is an established and prompt method to assess fall risk in health systems.²⁷ The scale has high predictive validity for falls.^28,29

Cognitive assessments

Multiple cognitive measures were used to assess global cognition and individual domains of cognition (Table 1).¹⁹ We measured global cognition using the Montreal Cognitive Assessment (MoCA). The MoCA is a screening tool for cognitive impairment and measures executive function, short-term memory recall, visuospatial abilities, attention, concentration and working memory, language, and orientation to time and place.³⁰ When employing a threshold of ≤4 points, the MoCA test exhibits a sensitivity of 84.4%and specificity of 91.9%(area under the curve: 0.92) for detecting severe dementia, while a range between 5 to 8 points indicates sensitivity (86.3%) and specificity (93.3%; area under the curve: 0.95) for detecting moderate dementia.³¹

Table 1.

Neurocognitive domains, cognitive tests, scoring, and their interpretation.

Neurocognitive Domain	Cognitive Test	Scoring	Subdomain of Cognition
Global Cognition	Montreal Cognitive Assessment	Greater scores correspond to greater global cognition (0–30 points).	N/A
Executive function	Trail-Making Test Part B	Trail A indicates processing speed.	Flexibility
	minus Part A	Trail B indicates ability for cognitive flexibility to mentally set-shift. Smaller differences in the time to completion between Trail A and Trail B indicate better cognitive flexibility (seconds).
	Verbal Forward Digit Span Test	Greater scores exhibit better working memory and attention span (0–14 points).	Working Memory
Perceptual-motor function	Benton Judgement of Line Orientation	Greater scores correspond to greater visuospatial perception and judgment abilities (0–15 points).	Visual perception
Language	Boston Naming Test	Greater scores represent greater word retrieval and expressive language abilities (0–15 points).	Object Naming
Learning and memory	Rey Auditory Verbal Learning	Greater scores reflect better verbal learning and memory abilities (0–15 points).	Free Recall
Complex attention	Digit Symbol Substitution	Greater number of items correctly coded are associated with better processing speed (0–90 symbols).	Processing Speed

The oral Trail-Making Test B minus A was used to assess the executive function domain, specifically the sub-domain of set-shifting.^32,33 For Part A, we asked participants to count numbers aloud in sequential order, starting at 1 and ending at 25. For Part B, participants orally switched back and forth from numbers to letters (the numbers extend from 1 to 13, and the letters from A to L. The amount of time (in seconds) for participants to complete these tasks was recorded. To index set shifting, the completion time difference between Part B and Part A was calculated. The written Trail-Making Test Part B minus Part A demonstrated good construct validity, as it was significantly correlated with other measures of executive function (e.g., Backwards Digit Span: r = –0.42, p < 0.05) among healthy older adults.³⁴ The oral Trail-Making Test is accessible for those with physical limitations.³⁵ The oral Trail-Making Test Part B minus Part A has accurately discriminated between people living with dementia, mild cognitive impairment, and cognitively intact older adults (χ², = 23.1, p < 0.001).³⁵ Additionally, we assessed executive function using the verbal Digit Span Forward Task, which measures working memory.³⁶ This task involved presenting a series of random digits (from 1 to 9). Afterwards, participants were asked to verbally repeat the list in the same order. If successful, they were provided a longer number sequence and the total number of correct trials, and the longest correct trial was recorded afterward. The verbal Digit Span Forward Task showed good construct validity, because it was significantly correlated with other measures of executive function (e.g., backwards digit span: r = 0.47, p < 0.05) among healthy older adults.³⁴ It also displayed good internal consistency (e.g., 0.77) in healthy young adults.^36,37

Perceptual motor function was assessed using the Benton Judgement of Line Orientation Test.³⁸ Participants were presented with 15 pairs of lines. Participants judged the angle of both lines with respect to the reference line angle, and the total scores ranged from 0 to 15. The Benton Judgement of Line Orientation Test showed high internal consistency (r = 0.83) and good test-retest reliability (r = 0.74) in healthy individuals aged 16–70 years.³⁹

Language skills, specifically object naming and word retrieval, were assessed with the Boston Naming Test.^40,41 We asked participants to verbalize the names of 15 printed objects on a piece of paper. The total score ranged from 0 to 15. The 15-item Boston Naming Test has been sensitive (0.70 to 0.77) and specific (0.86 to 0.91) to discriminate between those with mild Alzheimer’s disease relative to cognitively intact older adults,⁴² and has good internal consistency in healthy older adults (r = 0.63 to 0.86).⁴³

Learning and memory was assessed using the Rey Auditory Verbal Learning Test (RVLT).⁴⁴ We read a list of 15 words aloud five times, and asked participants to recall as many words as they could remember. The total number of words recalled on the fifth trial was recorded. The RVLT has good convergent validity with another measure of learning and memory (Hopkins Verbal Learning Test; r = 0.49, p < 0.001), and accurately discriminated between older adults with mild cognitive impairment and subjective cognitive decline (Cohen’s d: 0.94).⁴⁵

Complex attention was measured using the Digit Symbol Substitution Test (DSST).⁴⁶ The DSST measures processing speed and consists of nine-digit-symbol pairs.⁴⁷ We asked participants to fill in as many corresponding symbols for the given digits within 90 seconds. Performance was measured by the number of correct symbols; a greater number of symbols indicated better performance. The DSST has been sensitive to discriminate between people living with Alzheimer’s disease relative to cognitively intact older adults (Cohen’s d: –1.76, p < 0.01),⁴⁸ and has high test-retest reliability (r = 0.93) in healthy adults aged 19 to 82 years.⁴⁹

Physical activity

We measured physical activity using the ActiGraph GT3X+ accelerometer (ActiGraph, LLC, Pensacola, FL, USA). Participants wore this device on their non-dominant wrist for seven consecutive days, except when bathing or engaging in other water-based activities. We analyzed all accelerometry data using ActiLife 6.13.4. software. We included participants who wore the device for at least four days, including two weekend days, with a minimum of 10 h per day.⁵⁰ A 30 Hz sampling frequency was used for monitoring over 60-s epochs.⁵¹ The Choi 2011 criteria were applied to determine wear time validation.⁵² The Freedson 1998 adult criteria were used to determine the parameters for cut points for physical activity intensity.⁵³ We recorded the time (min) and percentage of time (%) in light, moderate, vigorous, and very vigorous activity.^54,55 Data were coded by intensity and classified into MET-values of light (1.50–2.99 METs), moderate (3.00–5.99 METs), or vigorous (> 6.00 METs). Total physical activity (MET: min week^–1) was calculated with the formula MET: min week^–1 = (1.5 x light min week^–1) + (3 x moderate min week^–1) + (6 x vigorous min week^–1). The Actigraph GT3X+Accelerometer has high internal consistency (r = 0.93 to 0.99) and good inter-instrument agreement (standard error of the measurement: 1.3 to 29.3%) over 7 days among healthy young adults.⁵⁶

Data analysis

We conducted the analysis in Stata (16.1, StataCorp LLC, College Station, TX) with a significance level of 0.05. We checked for normality and calculated descriptive statistics (means, standard deviations, percentages, and frequencies) for all variables. We calculated Pearson’s correlation coefficients to determine the relationships between cognitive domains, physical activity, and demographic and clinical factors. In order to determine the relationship between cognitive domains and physical activity, we conducted a linear regression for total physical activity (independent variable) with race (i.e., white/black), fall risk (i.e., Morse Fall Scale), and the number of comorbidities (i.e., Functional Comorbidities Index) as covariates; and MoCA, oral Trail Making Test Part B minus Part A, Forward Digit Span Test, Benton Judgement of Line Orientation Test, Boston Naming Test, RVLT, and DSST, as variables of interest.

Results

Descriptive statistics

Participant characteristics are presented in Table 2. Of the n = 42 participants living with dementia in the larger randomized controlled trial, n = 14 participants did not wear the motion watch for at least 4 days, n = 2 lost the motion watch, and n = 2 had incomplete cognitive data. Therefore, n = 24 participants living with dementia were included in this study (nursing home: n = 20; assisted living facility: n = 4).

Table 2.

Participant characteristics for people living with dementia; mean±standard deviation (range).

Variable	Participants (n = 24)
Age, y	82.3±9.9 (60 to 98)
Female Sex, n (%)	6 (25.0)
Black Race, n (%)	3 (12.5)
BMI, kg/m²	28.0±5.4 (19.2 to 36.2)
FCI, total number	4.1±2.1 (1 to 9)
Medications, total number	13.3±5.6 (5 to 28)
Morse Fall Scale, points	53.5±23.0 (15 to 90)
Dementia Type, n (%)
Alzheimer’s Disease	8 (33.3)
Vascular Dementia	2 (8.3)
Parkinson’s Disease Dementia	1 (4.2)
Alcohol Induced Dementia	1 (4.2)
Unspecified	12 (50.0)
Dementia Onset, y	4.2±6.3 (0.6 to 26.9)
MoCA, points	11.3±6.1 (0 to 19)
TMT, s	230.1±78.6 (52.8 to 290.5)
Forward Digit Span, total correct	4.7±1.7 (0 to 9)
BJLO, total correct	4.6±3.5 (0 to 10)
Boston Naming Test, total correct	10.5±3.6 (1 to 15)
RVLT, total correct	3.5±2.2 (0 to 8)
DSST, symbols completed	9.8±10.0 (0 to 32)
Mobility Device, n (%)
Wheelchair	6 (25.0)
Walker	11 (45.8)
Cane	2 (8.3)
None	5 (20.8)
Light Habitual Activity, min/week	1986.5±1035.1 (941.0 to 4389.0)
Moderate Habitual Activity, min/week	239.5±258.0 (10.0 to 1014.0)
Total Habitual Activity, METs	3698.1±1924.7 (1852.5 to 8217.0)

BMI, body mass index; FCI, Functional Comorbidity Index; MoCA, Montreal Cognitive Assessment; TMT, Trail Making Test (Part B minus A); BJLO, Benton Judgement of Line Orientation Test; RVLT, Rey Auditory Verbal Learning Test; DSST, Digit Symbol Substitution Test; MET, metabolic equivalent of task.

Participants were 82.3 (9.9) years, and primarily male (75%) and white (87.5%). The clinical data indicate that 50.0%of participants had unspecified dementia, followed by 33.0%of dementia caused by Alzheimer’s disease. Most participants used an assistive device (79.2%) compared to no assistive device (20.8%). All participants had comorbidities (range: 1–9) and took multiple medications (range: 5–28). No participants engaged in any vigorous or very vigorous physical activity (0 min/week).

The association between cognitive domains and physical activity

The overall regression model for physical activity was statistically significant (R² = 0.71, F_(10,13) = 3.25, RMSE = 1369, p < 0.05; Table 3). After adjusting for black race, fall risk, and comorbidities, greater physical activity was significantly associated with poorer global cognition (MoCA: β= –329.75, p = 0.002), better executive function performance (Trail-Making Test Part B minus Part A; β= –12.95, p = 0.045; Verbal Forward Digit Span Test: β= 699.29, p = 0.02), and better learning and memory performance (RVLT: β= 769.1, p = 0.004). Physical activity was not significantly associated with other domains of cognition (i.e., visuospatial perception, language, and complex attention). Figure 1 depicts our conceptual model of the relationship between physical activity, cognitive domains, and demographic and clinical factors.

Table 3.

Cognitive domains linked to physical activity among people living with dementia in residential care facilities (n = 24).

						95%CI
Outcome	Unstandardized β	Standardized β	SE	t-value	p-value	Lower	Upper
Constant	4275.99	–––	2317.75	1.84	0.09	–731.21	9283.19
Black Race	1010.79	0.18	1173.28	0.86	0.41	–1523.93	3545.50
Morse Fall Scale	–37.89	–0.45	17.72	–2.14	0.052	–76.17	0.39
FCI	456.21	0.50	228.14	2.00	0.07	–36.66	949.08
MoCA^∧	–329.75	–1.05	88.03	–3.75	0.002*	–519.92	–139.58
TMT	–12.95	–0.53	5.83	–2.22	0.045*	–25.54	–0.36
Forward Digit Span^∧	699.29	0.60	255.01	2.74	0.02*	148.38	1250.21
BJLO^∧	42.43	0.08	130.48	0.33	0.75	–239.45	324.32
Boston Naming Test^∧	–47.65	–0.09	193.76	–0.25	0.81	–466.24	370.93
RVLT^∧	769.10	0.90	219.96	3.50	0.004*	293.91	1244.28
DSST^∧	–54.14	–0.28	47.28	–1.15	0.27	–156.28	48.00

F_(10,13) = 3.25, R² = 0.71, RMSE = 1369, p < 0.05. Covariates included Race, Morse Fall Scale, and FCI. FCI, Functional Comorbidity Index; MoCA, Montreal Cognitive Assessment; TMT, Trail Making Test (Part B minus Part A); BJLO, Benton Judgement of Line Orientation Test; RVLT, Rey Auditory Verbal Learning Test; DSST, Digit Symbol Substitution Test; RMSE, root mean square error. ^∧Higher score indicates better performance.

Figure 1.

Conceptual model depicting the relationship between cognitive domains, demographic and clinical factors, and physical activity.

Discussion

Main findings

To our knowledge, this was the first study that has added empirical evidence about the relationship between physical activity and cognitive domains among people living with dementia in residential care facilities. We found that greater physical activity was linked to more impaired global cognition. We further found that physical activity was associated with specific cognitive domains, including better executive function as well as learning and memory. On the other hand, we did not detect an association between physical activity and visuospatial perception, language, or complex attention.

Cognitive domains linked to physical activity

This exploratory study builds upon previous work conducted in people without dementia,^12–18 and provides new insight that despite greater cognitive decline, there is still a significant relationship between physical activity and specific cognitive domains among people living with dementia. Previous work has reported that wandering is more common among those with moderate to severe dementia, especially Alzheimer’s disease, compared to mild dementia.⁵⁷ It is possible that a greater incidence of wandering may explain the relationship between greater physical activity and poorer global cognitive function. Thus, our results call for further studies to develop effective interventions to prevent and manage the adverse consequences of wandering in residential care facilities.

Greater physical activity may have been linked to better executive function, as well as learning and memory because it may act as a protective factor. For instance, moderate to vigorous physical activity has been protective of executive function and learning and memory in cognitively intact older adults and those with mild cognitive impairment.¹² Our study also supports previous work indicating that physical activity may combat cognitive decline in executive function,²³ and adds that it may also preserve learning and memory among people living with dementia, but further work is needed in larger samples. Our sample engaged in little moderate and no vigorous physical activity, yet total physical activity was still protective of executive function and learning and memory cognitive domains. Previous studies reported the role of physical activity in preserving learning and memory by promoting neurogenesis,⁵⁸ augmenting synaptic plasticity,⁵⁸ reducing oxidative stress,⁵⁹ and slowing down neurological degeneration in the progression of aging and dementia.⁶⁰ Executive function and learning and memory have been the most sensitive cognitive domains to changes in mobility patterns.⁶¹ We also found a trend for a greater risk for falls with reduced physical activity engagement in our sample of people living with dementia. Thus, future studies examining intrinsic and external factors that affect physical activity may provide novel targets for non-pharmacologic interventions in this population living in residential care facilities.

Cognitive domains with an unclear link to physical activity

We found no relationship between physical activity and language, which confirms previous work in older adults without dementia.¹⁴ Conversely, our study did not confirm previous literature indicating a relationship between structured exercise and complex attention among older adults with mild cognitive impairment,¹⁶ or tango and perceptual-motor function among people with Parkinson’s disease.²⁰ It is possible that the type and intensity of physical activity engagement has differential effects on cognitive function. It is also possible that the relationship between physical activity and cognitive function changes with significant cognitive decline. Further research is needed to determine whether the relationship between physical activity and complex attention and perceptual-motor function still holds for people living with dementia.

Implications

This study has implications for continuous home monitoring of actigraphy as a regular screening and monitoring tool of cognitive function among people living with dementia. Wearable technology can be used to improve the accuracy and precision of physical activity by providing objective and person-centered care in urban, rural, and underserved areas. Actigraphy seems to be sensitive to cognitive changes. Clinicians can use actigraphy for targeted interventions to prevent cognitive decline or mitigate further impairment among people living with dementia.

Limitations and future directions

There are several limitations to this study. We used a small convenience sample for this exploratory cross-sectional study; future larger studies with a wide range of socioeconomic backgrounds and clinical characteristics are needed to confirm our findings. We hypothesized that physical activity influenced cognitive function, but it is possible that executive function as well as learning and memory play a critical role in physical activity as indicated in our conceptual model in Figure 1. Longitudinal studies and interventional clinical trials are underway to better understand this dynamic relationship.²⁴ It is also possible that other factors may contribute to the relationship between physical activity and cognitive function that were not included in the analysis, such as social cognition, which we did not measure. The level of detail in the medical records may have differed between the nursing home and assisted living facility, and this variability may have influenced the measures that were pulled from the charts, such as the Functional Comorbidity Index and the time since dementia onset.

The potential effects of varying degrees of activity intensity were largely unrecognized due to the predominance of light activity within the participants. Some participated in moderate activity, but none performed vigorous or highly vigorous activity. The dose-dependent effects may have resulted in varying degrees of change in executive function, learning and memory, global cognition, or within another cognitive domain. While actigraphy has overestimated physical activity in aging populations,⁶² our data seems to fall within normative ranges.⁶³ The frequency and type of recreational activities offered at the nursing home and assisted living facility may have differed and affected physical activity levels. We did not collect subjective physical activity data to corroborate the objective physical activity data, as the participants living with dementia may have had limited recall of their physical activity, and it was not feasible for residential care facility staff to report. A large proportion of participants did not wear the actigraphy monitor on their wrist for at least 4 days (n = 18/42), for reasons such as forgetting to wear it, disinterest, or the care staff forgetting to put it back on after bathing. Therefore, wrist-worn actigraphy may only be feasible for some people living with dementia.

Conclusion

Among people living with dementia in residential care facilities, greater physical activity was linked with poorer global cognition, which may be explained because wandering is more common in later stages of dementia. Greater physical activity was also associated with better executive function as well as learning and memory; thus, physical activity may be a protective factor. More research is needed to better understand the dynamic relationship between physical activity and cognitive domains among people living with dementia.

Footnotes

Acknowledgments

The authors have no acknowledgments to report.

Funding

This study is funded by the Intramural Grants Program at Augusta University to DAJ (IGPCT00028) and YD (IGPP00033). These funding agencies did not play a role in study design.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The data supporting the findings of this study are available within the article.

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