| Literature DB >> 31736798 |
Stephen F Smagula1,2, Swathi Gujral1,3, Chandler S Capps4, Robert T Krafty4.
Abstract
Background: Rest-activity rhythm (RAR) disruption may be a risk factor for dementia that can be objectively measured with wearable accelerometers. It is possible that risk monitoring and preventive interventions could be developed targeting RARs. To evaluate whether current evidence supports these applications, we systematically reviewed published studies linking RARs with dementia, its course, and mechanisms.Entities:
Keywords: actigraphy; cerebrovascular disease; dementia; neurodegeneration; rest-activity rhythms; sleep-wake rhythms
Year: 2019 PMID: 31736798 PMCID: PMC6832024 DOI: 10.3389/fpsyt.2019.00778
Source DB: PubMed Journal: Front Psychiatry ISSN: 1664-0640 Impact factor: 4.157
Figure 1Commonly used rest-activity rhythm (RAR) measures. The top row represents high values on the given metric and the bottom row represents low values. From left to right: note stability, measured as nonparametric inter-daily stability, indicates how much the typical 24-h profile varies from day to day; fragmentation, measured as nonparametric intra-daily variability, indicates the frequency and extent of transitions in activity levels; 24-h model fit, from an extended cosine model (see line) pseudo-F statistic, indicates how well the data fits to a 24-h model; amplitude, derived from an extended cosine model, indicates rhythm height. More details on these common metrics are provided in the reviewed articles and elsewhere, e.g., see the study by Smagula (2).
Figure 2Number of articles identified by year and study design.
Figure 3Search process and article selection.
Summary of evidence relating RAR and cognitive measures.
| Studies comparing RARs by cognitive status | Study examining associations of RARs with cognitive test performance | ||
|---|---|---|---|
| Cross-sectional studies | Stability (IS) | 5/6 studies reported associations ( | 1/2 studies: Luik et al. ( |
| Fragmentation (IV) | 4/6 studies reported associations ( | 2/2 studies: Luik et al. ( | |
| Goodness of fit measures (R2, pseudo-F, or 24-h autocorrelation coefficient) | 3/3 studies reported associations ( | Gehrman et al. ( | |
| Amplitude (cosine-based model or nonparametric) | 5/5 studies reported associations ( | ||
| Longitudinal studies | Goodness of fit measures (pseudo-F) | 2/2 ( | Walsh et al. ( |
| Amplitude (cosine-based model) | Walsh et al. ( |
Summary of evidence relating RAR and neurobiological measures.
| Stability (IS) | Lower IS was associated with: |
| Fragmentation (IV) | Higher IV was associated with: |
| Goodness of fit measures (pseudo-F) | Better fit was associated with better memory performance, and this association was statistically mediated by hyperactivation in the hippocampus ( |
| Amplitude (cosine-based model or nonparametric) | Lower amplitude was associated with lower medial temporal lobe volume, but this association was attenuated when adjusting for age ( |
Summary of light interventions targeting RARs.
| Intervention | Effects on: | |||
|---|---|---|---|---|
| Stability (IS) | Fragmentation (IV) | Goodness of fit | Amplitude | |
| Morning bright light | No intervention effects in the study by Dowling et al. ( | Dowling et al. ( | 0/4 studies observed intervention effects ( | 0/3 studies ( |
| Morning bright light + Melatonin | No effects ( | Positive effects light+melatonin ( | ||
| Afternoon | No effect ( | No effect ( | ||
| Evening bright light | 2/2 studies showed significant pre-post improvements ( | 0/2 studies showed effects ( | ||
| Daytime (unattended) bright light | Improvements but only in patients with intact vision ( | |||
An early report noted that unattended daytime bright light had beneficial.