{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T11:59:44Z","timestamp":1792497584236,"version":"4.5.0"},"reference-count":69,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"8","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circ: Cardiovascular Quality and Outcomes"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:sec>\n            <jats:title>BACKGROUND:<\/jats:title>\n            <jats:p>Sleep and physical activity (PA) are important lifestyle-related behaviors that impact cardiometabolic health. This study investigated the joint associations of daily step count and sleep patterns (regularity and duration) with cardiometabolic biomarkers in adults.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>METHODS:<\/jats:title>\n            <jats:p>\n              We conducted a cross-sectional study using pooled data from the Prospective PA, Sitting, and Sleep Consortium, comprising 6 cohorts across Europe and Australia with thigh-worn accelerometry data collected between 2011 and 2021. The sleep regularity index, a metric that quantifies day-to-day sleep consistency, sleep duration (h\/d), and steps (per day), was derived from the accelerometer data and categorized based on tertiles and sleep duration guidelines. We used multivariate generalized linear models to examine joint associations of sleep patterns and total daily step count with individual cardiometabolic biomarkers, including body mass index, waist circumference, total cholesterol, HDL (high-density lipoprotein) cholesterol, triglycerides, HbA1c (glycated hemoglobin), and a composite cardiometabolic health score (mean of the 6 standardized biomarker\n              <jats:italic toggle=\"yes\">Z<\/jats:italic>\n              scores).\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS:<\/jats:title>\n            <jats:p>\n              The sample included 11\u2009903 adults with a mean\u00b1SD age of 54.7\u00b19.5 years, 54.9% female, a sleep regularity index of 78.7\u00b110.4, and 10\u2009206.4\u00b13442.2 daily steps. Lower PA (&lt;8475 steps\/d) combined with either lower sleep regularity (sleep regularity index &lt;75.9) or short sleep duration (&lt;7 h\/d) was associated with the least favorable composite cardiometabolic health. The corresponding\n              <jats:italic toggle=\"yes\">Z<\/jats:italic>\n              scores (95% CI) were 0.34 (0.30\u20130.38) and 0.26 (0.22\u20130.31) compared with those with optimal sleep (sleep regularity index &gt;84.5 or 7\u20138 h\/d) and high step count (&gt;11\u2009553 steps\/d). The combination of low sleep regularity and low daily steps was associated with higher body mass index (2.92 [2.61\u20133.24] kg\/m\n              <jats:sup>2<\/jats:sup>\n              ), waist circumference (8.58 [7.78\u20139.38] cm), total cholesterol (0.15 [0.07\u20130.23] mmol\/L), and lower HDL levels (0.17 [0.14\u20130.2] mmol\/L), regardless of sleep duration. The combination of short sleep and low step count had the strongest unfavorable associations for body mass index (2.31 [1.98\u20132.65] kg\/m\n              <jats:sup>2<\/jats:sup>\n              ) and waist circumference (7.01 [6.15\u20137.87] cm).\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSIONS:<\/jats:title>\n            <jats:p>Our findings suggest that the potential deleterious associations of irregular or insufficient sleep with cardiometabolic health outcomes may be exaggerated by lower daily PA. Investigation of the prospective joint association of sleep patterns and PA with cardiometabolic health may be warranted.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/circoutcomes.124.011873","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T09:00:14Z","timestamp":1753347614000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":12,"title":["Device-Measured Sleep Characteristics, Daily Step Count, and Cardiometabolic Health Markers: Findings From the Prospective Physical Activity, Sitting, and Sleep (ProPASS) Consortium"],"prefix":"10.1161","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4631-1978","authenticated-orcid":true,"given":"Wenxin","family":"Bian","sequence":"first","affiliation":[{"name":"Mackenzie Wearables Research Hub, Charles Perkins Centre (W.B., M.N.A., R.K.B., N.A.K., E.S.), The University of Sydney, NSW, Australia."},{"name":"Faculty of Medicine and 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