Linking the American Time Use Survey (ATUS) and the Compendium of Physical Activities: Methods and Rationale

Walking Behavior Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA.
Journal of physical activity & health (Impact Factor: 1.95). 06/2009; 6(3):347-53.
Source: PubMed


The 2003 Bureau of Labor Statistics American Time Use Survey (ATUS) contains 438 distinct primary activity variables that can be analyzed with regard to how time is spent by Americans. The Compendium of Physical Activities is used to code physical activities derived from various surveys, logs, diaries, etc to facilitate comparison of coded intensity levels across studies.
This article describes the methods, challenges, and rationale for linking Compendium estimates of physical activity intensity (METs, metabolic equivalents) with all activities reported in the 2003 ATUS.
The assigned ATUS intensity levels are not intended to compute the energy costs of physical activity in individuals. Instead, they are intended to be used to identify time spent in activities broadly classified by type and intensity. This function will complement public health surveillance systems and aid in policy and health-promotion activities. For example, at least one of the future projects of this process is the descriptive epidemiology of time spent in common physical activity intensity categories.
The process of metabolic coding of the ATUS by linking it with the Compendium of Physical Activities can make important contributions to our understanding of American's time spent in health-related physical activity.

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    • "The MET values within each occupational category were then averaged to determine a MET value for each occupational group (Table 1). This approach for MET value assignment was necessary given the previously determined ISCO classifications; comparison with other approaches, such as that developed for the American Time Use Survey [29], was done where there was some general overlap in the main occupational categories. "
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    ABSTRACT: Examination of historical trends and projections in estimated energy expenditure in Russia is important given the country's economic downturns and growth. Nationally representative data from the Russia Longitudinal Monitoring Survey (RLMS) from 1995-2011 was used to determine the metabolic equivalents of task (MET)-hours per week from occupational, domestic, travel, and active leisure physical activity (PA) domains, as well as sedentary leisure time (hours per week) among adults 18-60 years. Additionally, we projected what these values would be like in 2020 and 2030 if observed trends continue. Among male adults, the largest contributor to total PA was occupational PA followed by travel PA. In contrast, domestic PA followed by occupational PA contributed most to total PA among female adults. Total PA was 282.9 MET-hours per week in 1995 and declined to 231.7 in 2011. Total PA is projected to decrease to 216.5 MET-hours per week in 2020 and to 193.0 MET-hours per week in 2030. The greatest relative declines are occurring in travel PA. Female adults are also exhibiting significant declines in domestic PA. Changes in occupational and active leisure PA are less distinct. Policies and initiatives are needed to counteract the long-term decline of overall physical activity linked with a modernizing lifestyle and economy among Russian adults.
    International Journal of Behavioral Nutrition and Physical Activity 01/2014; 11(1):11. DOI:10.1186/1479-5868-11-11 · 4.11 Impact Factor
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    • "This study represents the first detailed analyses of trends in HMEE derived from nationally representative historical time-use databases. HMEE was derived using an empirically supported protocol for the translation of PA into EE [39], [61]. Our results on the allocation of time to HM, LTPA and screen-based media use are in agreement with other research [33], [52], [62], [63]. "
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    ABSTRACT: Relationships between socio-environmental factors and obesity are poorly understood due to a dearth of longitudinal population-level research. The objective of this analysis was to examine 45-year trends in time-use, household management (HM) and energy expenditure in women. Using national time-use data from women 19-64 years of age, we quantified time allocation and household management energy expenditure (HMEE) from 1965 to 2010. HM was defined as the sum of time spent in food preparation, post-meal cleaning activities (e.g., dish-washing), clothing maintenance (e.g., laundry), and general housework. HMEE was calculated using body weights from national surveys and metabolic equivalents. The time allocated to HM by women (19-64 yrs) decreased from 25.7 hr/week in 1965 to 13.3 hr/week in 2010 (P<0.001), with non-employed women decreasing by 16.6 hr/week and employed women by 6.7 hr/week (P<0.001). HMEE for non-employed women decreased 42% from 25.1 Mj/week (6004 kilocalories per week) in 1965 to 14.6 Mj/week (3486 kcal/week) in 2010, a decrement of 10.5 Mj/week or 1.5 Mj/day (2518 kcal/week; 360 kcal/day) (P<0.001), whereas employed women demonstrated a 30% decrement of 3.9 Mj/week, 0.55 Mj/day (923 kcal/week, 132 kcal/day) (P<0.001). The time women spent in screen-based media use increased from 8.3 hr/week in 1965 to 16.5 hr/week in 2010 (P<0.001), with non-employed women increasing 9.6 hr/week and employed women 7.5 hr/week (P<0.001). From 1965 to 2010, there was a large and significant decrease in the time allocated to HM. By 2010, women allocated 25% more time to screen-based media use than HM (i.e., cooking, cleaning, and laundry combined). The reallocation of time from active pursuits (i.e., housework) to sedentary pastimes (e.g., watching TV) has important health consequences. These results suggest that the decrement in HMEE may have contributed to the increasing prevalence of obesity in women during the last five decades.
    PLoS ONE 02/2013; 8(2):e56620. DOI:10.1371/journal.pone.0056620 · 3.23 Impact Factor
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    • "We matched the ABS activity codes used in the 1992 and 1997 Time Use Surveys to those used in the 2006 survey so that codes would be consistent across the surveys. We then assigned to all primary activities an intensity classification based on the Compendium of Physical Activities [1] and the intensity coding system used in the American Time Use Survey.[10] The intensity classification comprised three categories defined by metabolic equivalents (MET; 1 MET = 4.184 kJ per kilogram of body weight per hour): sedentary activities (<=1.5 METs), light activities (>1.5 to <3 METs), moderate-to-vigorous activities (> = 3 METs) and occupational activities. "
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    ABSTRACT: Current epidemiological data highlight the potential detrimental associations between sedentary behaviours and health outcomes, yet little is known about temporal trends in adult sedentary time. This study used time use data to examine population trends in sedentary behaviours in non-occupational domains and more specifically during leisure time. We conducted secondary analysis of population representative data from the Australian Time Use Surveys 1992, 1997 and 2006 involving respondents aged 20 years and over with completed time use diaries for two days. Weighted samples for each survey year were: n = 5851 (1992), n = 6419 (1997) and n = 5505 (2006). We recoded all primary activities by domain (sleep, occupational, transport, leisure, household, education) and intensity (sedentary, light, moderate). Adjusted multiple linear regressions tested for differences in time spent in non-occupational sedentary behaviours in 1992 and 1997 with 2006 as the reference year. Total non-occupational sedentary time was slightly lower in 1997 than in 2006 (mean = 894 min/2d and 906 min/2d, respectively; B = -11.2; 95%CI: -21.5, -0.9). Compared with 2006, less time was spent in 1997 in sedentary transport (B-6.7; 95%CI: -10.4, -3.0) and sedentary education (B = -6.3; 95%CI: -10.5, -2.2) while household and leisure sedentary time remained stable. Time engaged in different types of leisure-time sedentary activities changed between 1997 and 2006: leisure-time computer use increased (B = -26.7; 95%CI: -29.5, -23.8), while other leisure-time sedentary behaviours (e.g., reading, listening to music, hobbies and crafts) showed small concurrent reductions. In 1992, leisure screen time was lower than in 2006: TV-viewing (B = -24.2; 95%CI: -31.2, -17.2), computer use (B = -35.3; 95%CI: -37.7, -32.8). In 2006, 90 % of leisure time was spent sedentary, of which 53 % was screen time. Non-occupational sedentary time has increased slightly from 1997 to 2006 in the Australian adult population. This seems to be the result of small increases in sedentary transport and education time while sedentary household and leisure time were stable over this time period. However, almost all leisure time is spent sedentary and the composition of sedentary leisure time changed between 1992 and 2006 towards a larger proportion being screen-based activities. This could be an important observation for public health, as most of the evidence on the detrimental effects of sedentary behaviour is around watching television and health.
    International Journal of Behavioral Nutrition and Physical Activity 06/2012; 9(1):76. DOI:10.1186/1479-5868-9-76 · 4.11 Impact Factor
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