Device-Measured Sleep Characteristics, Daily Step Count, and Cardiometabolic Health Markers: Findings From the Prospective Physical Activity, Sitting, and Sleep (ProPASS) Consortium

Bian, W ORCID: 0009-0008-4631-1978, Ahmadi, MN ORCID: 0000-0002-3115-338X, Biswas, RK ORCID: 0000-0003-4294-6323, Blodgett, JM ORCID: 0000-0001-7684-3571, Atkin, AJ ORCID: 0000-0002-3819-3448, Chan, HW ORCID: 0000-0003-1545-0488, Del Pozo Cruz, B ORCID: 0000-0003-3944-2212, Suorsa, K ORCID: 0000-0002-3520-8069, Bakker, EA ORCID: 0000-0003-3899-471X, Pulsford, RM ORCID: 0000-0001-6880-7597, Mielke, GI ORCID: 0000-0002-3043-2715, Johansson, PJ ORCID: 0000-0001-9354-6704, Hettiarachchi, P ORCID: 0000-0003-1377-1923, Koemel, NA ORCID: 0000-0002-5463-6894, Thijssen, DHJ ORCID: 0000-0002-7707-5567, Stenholm, S ORCID: 0000-0001-7560-0930, Mishra, GD ORCID: 0000-0001-9610-5904, Teixeira-Pinto, A ORCID: 0000-0002-9389-2516, Rangul, V ORCID: 0000-0001-8863-0557, Sherar, LB ORCID: 0000-0002-9942-5433 et al (2025) Device-Measured Sleep Characteristics, Daily Step Count, and Cardiometabolic Health Markers: Findings From the Prospective Physical Activity, Sitting, and Sleep (ProPASS) Consortium. Circulation Cardiovascular Quality and Outcomes, 18 (8). e011873. ISSN 1941-7713

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Abstract

BACKGROUND: 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. METHODS: 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 Z scores). RESULTS: The sample included 11 903 adults with a mean±SD age of 54.7±9.5 years, 54.9% female, a sleep regularity index of 78.7±10.4, and 10 206.4±3442.2 daily steps. Lower PA (<8475 steps/d) combined with either lower sleep regularity (sleep regularity index <75.9) or short sleep duration (<7 h/d) was associated with the least favorable composite cardiometabolic health. The corresponding Z scores (95% CI) were 0.34 (0.30-0.38) and 0.26 (0.22-0.31) compared with those with optimal sleep (sleep regularity index >84.5 or 7-8 h/d) and high step count (>11 553 steps/d). The combination of low sleep regularity and low daily steps was associated with higher body mass index (2.92 [2.61-3.24] kg/m2), waist circumference (8.58 [7.78-9.38] cm), total cholesterol (0.15 [0.07-0.23] mmol/L), and lower HDL levels (0.17 [0.14-0.2] 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 [1.98-2.65] kg/m2) and waist circumference (7.01 [6.15-7.87] cm). CONCLUSIONS: 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.

Item Type:	Article
Uncontrolled Keywords:	ProPASS Collaboration; Humans; Exercise; Risk Assessment; Prospective Studies; Cross-Sectional Studies; Sleep; Time Factors; Adult; Aged; Middle Aged; Australia; Europe; Female; Male; Actigraphy; Accelerometry; Biomarkers; Fitness Trackers; Sitting Position; Cardiometabolic Risk Factors; accelerometry; cardiometabolic risk factors; cardiovascular diseases; epidemiology; exercise; public health; sleep duration; Humans; Female; Male; Middle Aged; Cross-Sectional Studies; Sleep; Prospective Studies; Exercise; Australia; Adult; Time Factors; Europe; Aged; Cardiometabolic Risk Factors; Fitness Trackers; Accelerometry; Biomarkers; Risk Assessment; Actigraphy; Sitting Position; 32 Biomedical and Clinical Sciences; 4206 Public Health; 42 Health Sciences; 3202 Clinical Sciences; Obesity; Clinical Research; Physical Activity; Behavioral and Social Science; Sleep Research; Prevention; Nutrition; Cardiovascular; Cardiovascular; 3 Good Health and Well Being; Humans; Female; Male; Middle Aged; Cross-Sectional Studies; Sleep; Prospective Studies; Exercise; Australia; Adult; Time Factors; Europe; Aged; Cardiometabolic Risk Factors; Fitness Trackers; Accelerometry; Biomarkers; Risk Assessment; Actigraphy; Sitting Position; 1102 Cardiorespiratory Medicine and Haematology; 1117 Public Health and Health Services; Cardiovascular System & Hematology; 3201 Cardiovascular medicine and haematology; 4206 Public health
Subjects:	B Philosophy. Psychology. Religion > BF Psychology R Medicine > RC Internal medicine > RC1200 Sports Medicine
Divisions:	Sport and Exercise Sciences
Publisher:	Wolters Kluwer Health on behalf of the American Heart Association
Date of acceptance:	2 July 2025
Date of first compliant Open Access:	21 October 2025
Date Deposited:	21 Oct 2025 08:45
Last Modified:	21 Oct 2025 09:00
DOI or ID number:	10.1161/circoutcomes.124.011873
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27388

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