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Open AccessArticle

Are all Sedentary Behaviors Equal? An Examination of Sedentary Behavior and Associations with Indicators of Disease Risk Factors in Women

1
School of Sport, Exercise, and Nutrition, Massey University, 4442 Palmerston North, New Zealand
2
Kinesiology Department, Seattle University, Seattle, WA 98122, USA
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(8), 2643; https://doi.org/10.3390/ijerph17082643
Received: 7 March 2020 / Revised: 6 April 2020 / Accepted: 6 April 2020 / Published: 12 April 2020
(This article belongs to the Special Issue Wearable Technology and Health)
Sedentary behavior increases risk for non-communicable diseases; associations may differ within different contexts (e.g., leisure time, occupational). This study examined associations between different types of sedentary behavior and disease risk factors in women, using objectively measured accelerometer-derived sedentary data. A validation study (n = 20 women) classified sedentary behavior into four categories: lying down; sitting (non-active); sitting (active); standing. A cross-sectional study (n = 348 women) examined associations between these classifications and disease risk factors (body composition, metabolic, inflammatory, blood lipid variables). Participants spent an average of 7 h 42 min per day in sedentary behavior; 58% of that time was classified as non-active sitting and 26% as active sitting. Non-active sitting showed significant (p ≤ 0.001) positive correlations with BMI (r = 0.244), body fat percent (r = 0.216), body mass (r = 0.236), fat mass (r = 0.241), leptin (r = 0.237), and negative correlations with HDL-cholesterol (r = −0.117, p = 0.031). Conversely, active sitting was significantly (p ≤ 0.001) negatively correlated with BMI (r = −0.300), body fat percent (r = −0.249), body mass (r = −0.305), fat mass (r = −0.320), leptin (r = −0.259), and positively correlated with HDL-cholesterol (r = 0.115, p = 0.035). In summary, sedentary behavior can be stratified using objectively measured accelerometer-derived activity data. Subsequently, different types of sedentary behaviors may differentially influence disease risk factors. Public health initiatives should account for sedentary classifications when developing sedentary behavior recommendations. View Full-Text
Keywords: sedentary behavior; accelerometry; disease risk factors sedentary behavior; accelerometry; disease risk factors
MDPI and ACS Style

Beale, C.; Rauff, E.L.; O’Brien, W.J.; Shultz, S.P.; Fink, P.W.; Kruger, R. Are all Sedentary Behaviors Equal? An Examination of Sedentary Behavior and Associations with Indicators of Disease Risk Factors in Women. Int. J. Environ. Res. Public Health 2020, 17, 2643.

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