Assigning Metabolic Equivalent Values to the 2002 Census Occupational Classification System

2011 ◽  
Vol 8 (4) ◽  
pp. 581-586 ◽  
Author(s):  
Catrine Tudor-Locke ◽  
Barbara E. Ainsworth ◽  
Tracy L. Washington ◽  
Richard Troiano
Keyword(s):  
Light Intensity ◽  
Time Use ◽  
Population Survey ◽  
Classification Systems ◽  
Occupational Activity ◽  
Population Estimates ◽  
Metabolic Equivalent ◽  
Occupational Classification ◽  
American Time Use Survey ◽  
Time Use Survey

Background:The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories.Methods:We describe the methods and rationale for assigning detailed Metabolic Equivalent (MET) estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5323 (2917 males and 2406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day.Results:Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared with using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations.Conclusions:Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

scholarly journals Income Inequality, Social Comparison, and Happiness in the United States

2021 ◽  
Vol 7 ◽  
pp. 237802312098564
Author(s):  
Tim Futing Liao
Keyword(s):  
Income Inequality ◽  
Social Comparison ◽  
Time Use ◽  
Population Survey ◽  
The United States ◽  
Comparison Theory ◽  
American Time Use Survey ◽  
Individual Level ◽  
Time Use Survey ◽  
The Individual

Using social comparison theory, I investigate the relation between experienced happiness and income inequality. In the analysis, I study happiness effects of the individual-level within-gender-ethnicity comparison-based Gini index conditional on a state’s overall inequality, using a linked set of the March 2013 Current Population Survey and the 2013 American Time Use Survey data while controlling major potential confounders. The findings suggest that individuals who are positioned to conduct both upward and downward comparison would feel happier in states where overall income inequality is high. In states where inequality is not high, however, such effects are not present because social comparison becomes less meaningful when one’s position is not as clearly definable. Therefore, social comparison matters where inequality persists: One’s comparison with all similar others’ in the income distribution in a social environment determines the effect of one’s income on happiness, with the comparison target being the same gender-ethnic group.

scholarly journals Cyclical Variation in Labor Hours and Productivity Using the ATUS

2013 ◽  
Vol 103 (3) ◽  
pp. 99-104 ◽  
Author(s):  
Michael C Burda ◽  
Daniel S Hamermesh ◽  
Jay Stewart
Keyword(s):  
Time Use ◽  
Population Survey ◽  
Work Hours ◽  
Monthly Variation ◽  
American Time Use Survey ◽  
Hours Of Work ◽  
Time Use Survey ◽  
The Hours ◽  
Using Data ◽  
Weekly Work

We examine monthly variation in weekly work hours using data from 2003 to 2010. The data sources include the Current Population Survey (CPS) on hours/worker, the Current Employment Survey (CES) on hours/job, and the American Time Use Survey (ATUS) on both. The ATUS data minimize recall difficulties and constrain hours of work to accord with total available time. The ATUS hours/worker are less cyclical than the CPS series, but the hours/job are more cyclical than the CES series. We present alternative estimates of productivity based on ATUS data, and find that it is more pro-cyclical than other productivity measures.

scholarly journals Sleep Duration and Waking Activities in Relation to the National Sleep Foundation’s Recommendations: An Analysis of US Population Sleep Patterns from 2015 to 2017

2021 ◽  
Vol 18 (11) ◽  
pp. 6154
Author(s):  
Michael Osei Mireku ◽  
Alina Rodriguez
Keyword(s):  
Sleep Duration ◽  
Time Use ◽  
Variance Estimation ◽  
Estimation Method ◽  
Short Sleep Duration ◽  
Weighted Estimates ◽  
American Time Use Survey ◽  
Increased Risk ◽  
The Us ◽  
Time Use Survey

The objective was to investigate the association between time spent on waking activities and nonaligned sleep duration in a representative sample of the US population. We analysed time use data from the American Time Use Survey (ATUS), 2015–2017 (N = 31,621). National Sleep Foundation (NSF) age-specific sleep recommendations were used to define recommended (aligned) sleep duration. The balanced, repeated, replicate variance estimation method was applied to the ATUS data to calculate weighted estimates. Less than half of the US population had a sleep duration that mapped onto the NSF recommendations, and alignment was higher on weekdays (45%) than at weekends (33%). The proportion sleeping longer than the recommended duration was higher than those sleeping shorter on both weekdays and weekends (p < 0.001). Time spent on work, personal care, socialising, travel, TV watching, education, and total screen time was associated with nonalignment to the sleep recommendations. In comparison to the appropriate recommended sleep group, those with a too-short sleep duration spent more time on work, travel, socialising, relaxing, and leisure. By contrast, those who slept too long spent relatively less time on each of these activities. The findings indicate that sleep duration among the US population does not map onto the NSF sleep recommendations, mostly because of a higher proportion of long sleepers compared to short sleepers. More time spent on work, travel, and socialising and relaxing activities is strongly associated with an increased risk of nonalignment to NSF sleep duration recommendations.

scholarly journals Which Jobs are Done from Home? Evidence from the American Time Use Survey

2020 ◽  
Author(s):  
Lena Hensvik ◽  
Thomas Le Barbanchon ◽  
Roland Rathelot
Keyword(s):  
Time Use ◽  
American Time Use Survey ◽  
Time Use Survey

scholarly journals Graphical Representation of Time Use Diaries in Stata: ATUS Tempograms

2020 ◽  
Author(s):  
Kamila Kolpashnikova
Keyword(s):  
Survey Data ◽  
Time Use ◽  
Graphical Representation ◽  
American Time Use Survey ◽  
The Us ◽  
Time Use Survey ◽  
Representation Of Time

In this paper, I will demonstrate how to create tempograms using the original American Time Use Survey data from the US Bureau of Labor Statistics2. For this project, the 2003-2018sample of diaries is used (file names: atusact0318 and atussum0318).Additionally, I identify the bottleneck, where the performance of Stata’s underlying functions could be optimised to improve the work with time-use data for researchers who use Stata.

scholarly journals Exploring daily time-use patterns: ATUS-X data extractor and online diary visualization tool

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252843
Author(s):  
Kamila Kolpashnikova ◽  
Sarah Flood ◽  
Oriel Sullivan ◽  
Liana Sayer ◽  
Ekaterina Hertog ◽  
...  
Keyword(s):  
Time Use ◽  
Visualization Tool ◽  
Policy Makers ◽  
Online Tool ◽  
American Time Use Survey ◽  
Use Patterns ◽  
Accessibility Barriers ◽  
Academic Researchers ◽  
Time Use Survey ◽  
Daily Time

Time-use data can often be perceived as inaccessible by non-specialists due to their unique format. This article introduces the ATUS-X diary visualization tool that aims to address the accessibility issue and expand the user base of time-use data by providing users with opportunity to quickly visualize their own subsamples of the American Time Use Survey Data Extractor (ATUS-X). Complementing the ATUS-X, the online tool provides an easy point-and-click interface, making data exploration readily accessible in a visual form. The tool can benefit a wider academic audience, policy-makers, non-academic researchers, and journalists by removing accessibility barriers to time use diaries.

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