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

• Published in: The international journal of behavioral nutrition and physical activity 2015-06, Vol.12 (1), p.89-89, Article 89
• Main Authors: Steeves, Jeremy A, Tudor-Locke, Catrine, Murphy, Rachel A, King, George A, Fitzhugh, Eugene C, Harris, Tamara B
• Format: Article
• Language: English
• Subjects: Accelerometry; actigraphy; Adult; adults; Analysis; athletes; Classification; engineers; Exercise; farms; Female; Health aspects; Health surveys; higher education; Humans; income; Life Style; lifestyle; Male; managers; men; Middle Aged; Motor Activity; National Health and Nutrition Examination Survey; Nutrition Surveys; Occupations; physical activity; Physical fitness; scientists; Sedentary Lifestyle; Surveys; technicians; women; Work; Young Adult
• ISSN: 1479-5868; 1479-5868
• DOI: 10.1186/s12966-015-0235-z

BACKGROUND: An 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). METHODS: ActiGraph 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. RESULTS: According 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. CONCLUSIONS: Objectively 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 bet