Approaches for Assessing Circadian Rest-Activity Patterns Using Actigraphy in Cohort and Population-Based Studies

Gao, Chenlu; Haghayegh, Shahab; Wagner, Max; Cai, Ruixue; Hu, Kun; Gao, Lei; Li, Peng

doi:10.1007/s40675-023-00267-4

Cited by 10 publications

(3 citation statements)

References 58 publications

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“…Cosinor analysis was also performed to derive 2 additional measures of 24-hour activity rhythms: the amplitude (midline to peak) and acrophase (time of the peak) of the 24-hour rhythm. All RAR data analyses were performed using the eZActi2 software [ 35 , 36 ].…”

Section: Methodsmentioning

confidence: 99%

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study

Haghayegh,

Gao,

Sugg

et al. 2024

JMIR Public Health Surveill

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Background The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. Objective We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. Methods We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. Results During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non–shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. Conclusions Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

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Section: Methodsmentioning

confidence: 99%

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study

Haghayegh,

Gao,

Sugg

et al. 2024

JMIR Public Health Surveill

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“…A power‐law relationship between F( n ) and n , that is, F( n )∼ n α , indicates a fractal structure. Detailed procedures for performing the DFA and related quality control have been published elsewhere 20 , 21 , 23 , 25 , and a customized program is openly available at Zenodo. 26 , 27…”

Section: Methodsmentioning

confidence: 99%

“…elsewhere 20,21,23,25 , and a customized program is openly available at Zenodo. 26,27 The exponent α quantifies the temporal correlation.…”

Section: Fractal Analysis Of Actigraphy (α 1 and α 2 )mentioning

confidence: 99%

Delineating cognitive resilience using fractal regulation: Cross‐sectional and longitudinal evidence from the Rush Memory and Aging Project

Li,

Gao,

et al. 2024

Alzheimer's & Dementia

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INTRODUCTIONDegradation of fractal patterns in actigraphy independently predicts dementia risk. Such observations motivated the study to understand the role of fractal regulation in the context of neuropathologies.METHODSWe examined associations of fractal regulation with neuropathologies and longitudinal cognitive changes in 533 older participants who were followed annually with actigraphy and cognitive assessments until death with brain autopsy performed. Two measures for fractal patterns were extracted from actigraphy, namely, α1 (representing the fractal regulation at time scales of <90 min) and α2 (for time scales 2 to 10 h).RESULTSWe found that larger α1 was associated with lower burdens of Lewy body disease or cerebrovascular disease pathologies; both α1 and α2 were associated with cognitive decline. They explained an additional significant portion of the variance in the rate of cognitive decline above and beyond neuropathologies.DISCUSSIONFractal patterns may be used as a biomarker for cognitive resilience against dementia‐related neuropathologies.

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Cognition and Activity of Daily Living Function in people with Parkinson’s disease

Bode,

Kalbe,

Liepelt-Scarfone

2024

J Neural Transm

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The ability to perform activities of daily living (ADL) function is a multifaceted construct that reflects functionality in different daily life situations. The loss of ADL function due to cognitive impairment is the core feature for the diagnosis of Parkinson’s disease dementia (PDD). In contrast to Alzheimer’s disease, ADL impairment in PD can be compromised by various factors, including motor and non-motor aspects. This narrative review summarizes the current state of knowledge on the association of cognition and ADL function in people with PD and introduces the concept of “cognitive ADL” impairment for those problems in everyday life that are associated with cognitive deterioration as their primary cause. Assessment of cognitive ADL impairment is challenging because self-ratings, informant-ratings, and performance-based assessments seldomly differentiate between “cognitive” and “motor” aspects of ADL. ADL function in PD is related to multiple cognitive domains, with attention, executive function, and memory being particularly relevant. Cognitive ADL impairment is characterized by behavioral anomalies such as trial-and-error behavior or task step omissions, and is associated with lower engagement in everyday behaviors, as suggested by physical activity levels and prolonged sedentary behavior. First evidence shows that physical and multi-domain interventions may improve ADL function, in general, but the evidence is confounded by motor aspects. Large multicenter randomized controlled trials with cognitive ADL function as primary outcome are needed to investigate which pharmacological and non-pharmacological interventions can effectively prevent or delay deterioration of cognitive ADL function, and ultimately the progression and conversion to PDD.

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Approaches for Assessing Circadian Rest-Activity Patterns Using Actigraphy in Cohort and Population-Based Studies

Cited by 10 publications

References 58 publications

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study

Delineating cognitive resilience using fractal regulation: Cross‐sectional and longitudinal evidence from the Rush Memory and Aging Project

Cognition and Activity of Daily Living Function in people with Parkinson’s disease

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