{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T03:44:26Z","timestamp":1790653466392,"version":"4.1.0"},"posted":{"date-parts":[[2024,1,22]]},"group-title":"Neurology","reference-count":55,"publisher":"openRxiv","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,1,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Importance<\/jats:title>\n                  <jats:p>Wrist-worn activity monitors provide biomarkers of health by non-obtrusively measuring the timing and amount of rest and physical activity (rest-activity rhythms, RARs). The morphology and robustness of RARs vary by age, gender, and sociodemographic factors, and are perturbed in various chronic illnesses. However, these are cross-sectionally derived associations from recordings lasting 4-10 days, providing little insights into how RARs vary with time.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To describe how RAR parameters can vary or evolve with time (\u223cmonths).<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Design, Setting and Participants<\/jats:title>\n                  <jats:p>48 very long actograms (\u201cVLAs\u201d, \u226590 days in duration) were identified from subjects enrolled in the STAGES (Stanford Technology, Analytics and Genomics in Sleep) study, a prospective cross-sectional, multisite assessment of individuals &gt; 13 years of age that required diagnostic polysomnography to address a sleep complaint. A single 3-year long VLA (author GD) is also described.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Exposures\/Intervention<\/jats:title>\n                  <jats:p>None planned.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Main Outcomes and Measures<\/jats:title>\n                  <jats:p>For each VLA, we assessed the following parameters in 14-day windows: circadian\/ultradian spectrum, pseudo-F statistic (\u201cF\u201d), cosinor amplitude, intradaily variability, interdaily stability, acrophase and estimates of \u201csleep\u201d and non-wearing.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    Included STAGES subjects (n = 48, 30 female) had a median age of 51, BMI of 29.4kg\/m\n                    <jats:sup>2<\/jats:sup>\n                    , Epworth Sleepiness Scale score (ESS) of 10\/24 and a median recording duration of 120 days. We observed marked within-subject undulations in all six RAR parameters, with many subjects displaying ultradian rhythms of activity that waxed and waned in intensity. When appraised at the group level (nomothetic), averaged RAR parameters remained remarkably stable over a \u223c4 month recording period. Cohort-level deficits in average RAR robustness associated with unemployment or high BMI (&gt;29.4) also remained stable over time.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions and Relevance<\/jats:title>\n                  <jats:p>Through an exemplary set of months-long wrist actigraphy recordings, this study quantitatively depicts the longitudinal stability and dynamic range of human rest-activity rhythms. We propose that continuous and long-term actigraphy may have broad potential as a holistic, transdiagnostic and ecologically valid monitoring biomarker of changes in chronobiological health. Prospective recordings from willing subjects will be necessary to precisely define contexts of use.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2024.01.22.24301243","type":"posted-content","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T18:27:52Z","timestamp":1705948072000},"source":"Crossref","is-referenced-by-count":2,"title":["Stability and Volatility of Human Rest-Activity Rhythms: Insights from Very Long Actograms (VLAs)"],"prefix":"10.64898","author":[{"given":"Nandani","family":"Adhyapak","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark A.","family":"Abboud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pallavi S.K.","family":"Rao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ananya","family":"Kar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel","family":"Mignot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gianluigi","family":"Delucca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen F.","family":"Smagula","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vaishnav","family":"Krishnan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2024012422200677000_2024.01.22.24301243v1.1","unstructured":"In: BEST (Biomarkers, EndpointS, and other Tools) Resource (FDA-NIH Joint Leadership Council). 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