Classification of occupational activity categories using accelerometry: NHANES 2003–2004

International Journal of Behavioral Nutrition and Physical Activity

Research

Eugene C. Fitzhugh¹  George A. King²  Jeremy A. Steeves³  Rachel A. Murphy⁴  Tamara B. Harris⁴  Catrine Tudor-Locke⁵ 

[1] Department of Kinesiology, Recreation, and Sports Studies, University of Tennessee, Knoxville, TN, USA;Department of Kinesiology, University of Texas, El Paso, TX, USA;Department of Kinesiology, University of Wisconsin-Milwaukee, 2400 E Hartford Avenue, 53201, Milwaukee, WI, USA;Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD, USA;Walking Behavior Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA;

关键词: Occupational activity;    Accelerometer;    Work;    Employment;    Classification;    Cross-sectional;   

DOI  :  10.1186/s12966-015-0235-z

 received in 2014-12-11, accepted in 2015-05-01,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundAn individual’s occupational activity (OA) may contribute significantly to daily physical activity (PA) and sedentary behavior (SB). However, there is little consensus about which occupational categories involve high OA or low OA, and the majority of categories are unclassifiable with current methods. The purpose of this study was to present population estimates of accelerometer-derived PA and SB variables for adults (n = 1112, 20–60 years) working the 40 occupational categories collected during the 2003–2004 National Health and Nutrition Examination Survey (NHANES).MethodsActiGraph accelerometer-derived total activity counts/day (TAC), activity counts/minute, and proportion of wear time spent in moderate-to-vigorous PA [MVPA], lifestyle, and light PA organized by occupational category were ranked in ascending order and SB was ranked in descending order. Summing the ranks of the six accelerometer-derived variables generated a summary score for each occupational category, which was re-ranked in ascending order. Higher rankings indicated higher levels of OA, lower rankings indicated lower levels of OA. Tertiles of the summary score were used to establish three mutually exclusive accelerometer-determined OA groupings: high OA, intermediate OA, and low OA.ResultsAccording to their summary score, ‘farm and nursery workers’ were classified as high OA and ‘secretaries, stenographers, and typists’ were classified as low OA. Consistent with previous research, some low OA occupational categories (e.g., ‘engineers, architects, and scientists’, ‘technicians and related support occupations’, ‘management related occupations’, ‘executives, administrators, and managers’, ‘protective services’, and ‘writers, artists, entertainers, and athletes’) associated with higher education and income had relatively greater amounts of MVPA compared to other low OA occupational categories, likely due to the greater percentage of men in those occupations and/or the influence of higher levels of leisure time PA. Men had more TAC, activity counts/minute and time in MVPA, but similar proportions of SB compared to women in all three OA groupings.ConclusionsObjectively measured PA allowed for a more precise estimate of the amount of PA and SB associated with different occupations and facilitated systematic classification of the 40 different occupational categories into three distinct OA groupings. This information provides new opportunities to explore the relationship between OA and health outcomes.

【 授权许可】

CC BY   
© Steeves et al. 2015