Verónica Cabanas-Sánchez1,2, Irene Esteban-Cornejo3, Jairo H Migueles3, José Ramón Banegas4,5, Auxiliadora Graciani4,5, Fernando Rodríguez-Artalejo4,5,6, David Martínez-Gómez4,5,6. 1. Research Centre in Physical Activity, Health and Leisure (CIAFEL), Faculty of Sport, University of Porto, Porto, Portugal. 2. Department of Physical Education, Sport and Human Movement, Autonomous University of Madrid, Madrid, Spain. 3. PROFITH "PROmoting FITness and Health through physical activity" research group, Department of Physical and Sports Education, Faculty of Sport Sciences, University of Granada, Granada, Spain. 4. Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Madrid, Spain. 5. CIBER of Epidemiology and Public Health (CIBERESP), IdiPAZ, Madrid, Spain. 6. CEI UAM + CSIC, IMDEA Food Institute, Madrid, Spain.
Abstract
OBJECTIVES: This study aimed: (a) to provide a detailed description of sleep, sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) over the complete 24-hours period using raw acceleration data in older adults; and (b) to examine the differences in the 24-hours activity cycle by sex, age, education, and body mass index (BMI). METHODS: Population-based cohort comprising 3273 community-dwelling individuals (1739 women), aged 71.8 ± 4.5 years, participating in the Seniors-ENRICA-2 study. Participants wore a wrist-worn ActiGraph GT9X accelerometer for 7 consecutive days, and the raw signal was processed using the R-package GGIR. RESULTS: Participants reached 21.5 mg as mean acceleration over the whole day; 32.3% (7.7 h/d) of time was classified as sleep, 53.2% (12.7 h/d) as SED, 10.4% (148.6 min/d) as LPA, and 4.1% (59.0 min/d) as MVPA. No marked differences were found in sleep-related variables between socio-demographic and BMI groups. However, women showed higher LPA but lower SED and MVPA than men. Moreover, SED increased whereas LPA and MVPA decreased with age. Participants with obesity (BMI ≥ 30 kg/m2 ) accumulated more SED and less LPA and MVPA than those without obesity. As expected, adherence to physical activity recommendations varied widely (9.2%-76.6%) depending on the criterion of MVPA accumulation. CONCLUSION: Objective assessment of the 24-hour activity cycle provides extensive characterization of daily activities distribution in older adults and may inform health-promotion interventions in this population. Women, the oldest old, and those with obesity offer relevant targets of strategies to improve lifestyle patterns.
OBJECTIVES: This study aimed: (a) to provide a detailed description of sleep, sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) over the complete 24-hours period using raw acceleration data in older adults; and (b) to examine the differences in the 24-hours activity cycle by sex, age, education, and body mass index (BMI). METHODS: Population-based cohort comprising 3273 community-dwelling individuals (1739 women), aged 71.8 ± 4.5 years, participating in the Seniors-ENRICA-2 study. Participants wore a wrist-worn ActiGraph GT9X accelerometer for 7 consecutive days, and the raw signal was processed using the R-package GGIR. RESULTS:Participants reached 21.5 mg as mean acceleration over the whole day; 32.3% (7.7 h/d) of time was classified as sleep, 53.2% (12.7 h/d) as SED, 10.4% (148.6 min/d) as LPA, and 4.1% (59.0 min/d) as MVPA. No marked differences were found in sleep-related variables between socio-demographic and BMI groups. However, women showed higher LPA but lower SED and MVPA than men. Moreover, SED increased whereas LPA and MVPA decreased with age. Participants with obesity (BMI ≥ 30 kg/m2 ) accumulated more SED and less LPA and MVPA than those without obesity. As expected, adherence to physical activity recommendations varied widely (9.2%-76.6%) depending on the criterion of MVPA accumulation. CONCLUSION: Objective assessment of the 24-hour activity cycle provides extensive characterization of daily activities distribution in older adults and may inform health-promotion interventions in this population. Women, the oldest old, and those with obesity offer relevant targets of strategies to improve lifestyle patterns.
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