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Can objective measures of physical activity and sleep serve as early predictors of dementia among individuals with cognitive impairment?
Orr VL, Brown K, Wilson K, Dean P, Hu S, Levendowski D, Seto E, Shutes-David A et al.. medRxiv, 2025-12-15
Topic: Brain imaging, connectivity and assessment
Background and Objectives Physical activity and sleep are potential modifiable risk factors for the development of Alzheimer’s disease and related disorders (ADRD), but few studies have objectively measured both domains in participants across the cognitive continuum. Research Design and Methods Standard clinical assessment, accelerometry, and at-home EEG sleep data were obtained from older controls (n=9) and adults who met consensus diagnostic criteria for mild cognitive impairment (MCI; n=7), Alzheimer’s disease (AD; n=10), and dementia with Lewy bodies (DLB; n=11). Given these sample sizes, descriptive statistics are presented rather than formal statistical testing. Results The MCI group had the most surprising findings—although they were cognitively similar to the control group, they were less physically active than the AD group and had the worst sleep efficiency. The DLB group had the most severe motor and neuropsychiatric symptoms, were the least physically active, spent the least amount of time in rapid eye movement (REM) sleep, and spent the highest amount of time in non-REM sleep with hypotonia (NRH). The AD group had physical activity counts that fell between the DLB and control groups; REM sleep and NRH levels that were similar to the control and MCI groups; and autonomic activation index (AAI) and sleep spindle durations that were higher than the MCI and DLB groups. Discussion and Implications These findings highlight interesting physical activity and sleep patterns between groups, but larger samples are needed to investigate how objectively measured physical activity and sleep might serve as disease-specific digital biomarkers of neurodegenerative disorders. Translational Significance This study uses wearable technologies to measure physical activity and sleep in adults with and without cognitive impairment. The study found that adults with mild cognitive impairment had physical activity and sleep patterns that resembled people with dementia despite having cognitive scores that were closer to cognitively healthy controls. Sleep and activity patterns were distinct when comparing participants with Alzheimer’s and dementia with Lewy bodies. Larger studies are needed to validate these findings, but mobile health devices may be an accessible way to detect early cognitive decline and help differentiate dementia subtypes, resulting in earlier, targeted clinical care.
Key findings
- Results The MCI group had the most surprising findings—although they were cognitively similar to the control group, they were less physically active than the AD group and had the worst sleep efficiency.
- Discussion and Implications These findings highlight interesting physical activity and sleep patterns between groups, but larger samples are needed to investigate how objectively measured physical activity and sleep might serve as disease-specific digital biomarkers of neurodegenerative disorders.
- Larger studies are needed to validate these findings, but mobile health devices may be an accessible way to detect early cognitive decline and help differentiate dementia subtypes, resulting in earlier, targeted clinical care.
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Study details
- Evidence strengthLow
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 19 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 12 of the 62 points we could judge it on, which is 19 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (medRxiv) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 12 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 12 of the 62 points we could judge it on is 19 out of 100. |
| Total | 19 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Orr, V. L., Brown, K., Wilson, K., Dean, P., Hu, S., Levendowski, D., et al. (2025). Can objective measures of physical activity and sleep serve as early predictors of dementia among individuals with cognitive impairment? medRxiv. https://doi.org/10.64898/2025.12.12.25342162
Vancouver
Orr VL, Brown K, Wilson K, Dean P, Hu S, Levendowski D, et al. Can objective measures of physical activity and sleep serve as early predictors of dementia among individuals with cognitive impairment? medRxiv. 2025. doi:10.64898/2025.12.12.25342162.
BibTeX
@article{orr2025-4a125473,
author = {Orr, V. L. and Brown, K. and Wilson, K. and Dean, P. and Hu, S. and Levendowski, D. and Seto, E. and Shutes-David, A. and others},
title = {{Can objective measures of physical activity and sleep serve as early predictors of dementia among individuals with cognitive impairment?}},
journal = {medRxiv},
year = {2025},
doi = {10.64898/2025.12.12.25342162},
url = {https://doi.org/10.64898/2025.12.12.25342162}
}
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