• Preventive medicine · Jul 2019

    Intensity and temporal patterns of physical activity and cardiovascular disease risk in midlife.

    • Maisa Niemelä, Maarit Kangas, Vahid Farrahi, Antti Kiviniemi, Anna-Maiju Leinonen, Riikka Ahola, Katri Puukka, Juha Auvinen, Raija Korpelainen, and Timo Jämsä.
    • Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland; Infotech, University of Oulu, Oulu, Finland; Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, Finland. Electronic address: maisa.niemela@oulu.fi.
    • Prev Med. 2019 Jul 1; 124: 33-41.

    AbstractPhysical activity (PA) and sedentary time (SED) are associated with the risk of cardiovascular disease (CVD), but the temporal patterns of these behaviors most beneficial for cardiovascular health remain unknown. We aimed to identify the intensity and temporal patterns of PA and SED measured continuously by an accelerometer and their relationship with CVD risk. At the age of 46 years, 4582 members (1916 men; 2666 women) of the Northern Finland Birth Cohort 1966 study underwent continuous measurement of PA with Polar Active (Polar Electro, Finland) accelerometers for one week. X-means clustering was applied based on 10 min average MET (metabolic equivalent) values during the measurement period. Ten-year risk of CVD was estimated using the Framingham risk model. Most of the participants had low risk for CVD. Four distinct PA clusters were identified that were well differentiable by the intensity and temporal patterns of activity (inactive, evening active, moderately active, very active). A significant difference in 10-year CVD risk across the clusters was found in men (p = 0.028) and women (p < 0.001). Higher levels of HDL cholesterol were found in more active clusters compared to less active clusters (p < 0.001) in both genders. In women total cholesterol was lower in the moderately active cluster compared to the inactive and evening active clusters (p = 0.001). Four distinct PA clusters were recognized based on accelerometer data and X-means clustering. A significant difference in CVD risk across the clusters was found in both genders. These results can be used in developing and promoting CVD prevention strategies.Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

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