Quality of Match for Statistical Matches Using the American Time Use Survey 2010, the Survey of Consumer Finances 2010, and the Annual Social and Economic Supplement 2011

Author(s):  
Fernando RiossAvila
Author(s):  
Michael Osei Mireku ◽  
Alina Rodriguez

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.


2020 ◽  
Author(s):  
Lena Hensvik ◽  
Thomas Le Barbanchon ◽  
Roland Rathelot

2020 ◽  
Author(s):  
Kamila Kolpashnikova

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.


PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252843
Author(s):  
Kamila Kolpashnikova ◽  
Sarah Flood ◽  
Oriel Sullivan ◽  
Liana Sayer ◽  
Ekaterina Hertog ◽  
...  

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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