Selected article for: "logistic regression and low subsequent"

Author: Mattingly, J. L.; Petrov, M. E.
Title: Association between covid-19 pandemic related unemployment and change in sedentary screen time among previously employed adults
  • Cord-id: ivcur0kj
  • Document date: 2021_1_1
  • ID: ivcur0kj
    Snippet: Introduction: Worldwide, the COVID-19 pandemic has resulted in widespread job loss and disruptions in daily life. However, the role of job loss during the COVID-19 pandemic on health behaviors such as sedentary screen time (SST) is unknown. The purpose of this study was to determine the association between employment status change during the pandemic and change in SST. Methods: A 25-minute online survey was distributed through local and global social media from 5/21/2020-7/01/2020. A subsample o
    Document: Introduction: Worldwide, the COVID-19 pandemic has resulted in widespread job loss and disruptions in daily life. However, the role of job loss during the COVID-19 pandemic on health behaviors such as sedentary screen time (SST) is unknown. The purpose of this study was to determine the association between employment status change during the pandemic and change in SST. Methods: A 25-minute online survey was distributed through local and global social media from 5/21/2020-7/01/2020. A subsample of employed adults (n=417;M=38.45y, range: 18-75;74.8.% women) provided complete self-reported pre-and during-COVID-19 employment status (categorized as remained employed and became unemployed), pre-and during-COVID-19 hours of daily SST for non-work-related purposes [low: <5h;high: >5]. Change in daily SST was categorized as low-low (ref), low-high, and high-high. The subsample of participants that changed from high to low SST in the sample was low and were removed from subsequent analyses. Multinomial logistic regression models were conducted to examine the association of change in employment status on change inSST while adjusting for age, gender, education level, body mass index, current minutes of physicalactivity per week, and current typical 24-hour sleep duration. Results: of the 417 participants who were employed prior to the pandemic, 15.6% (n=675).Became Unemployed. The proportion of participants in the low-low, low-high, and high-high changein SST groups were 46.8% (n=195), 25.4% (n=106), and 27.8% (n=116), respectively. Relative toadults who remained employed, adults who became unemployed had a 3.02 greater odds(95%CI:1.51, 6.02) of being in the high-high change in SST group, and had a 2.54 greater odds(95%CI:1.23,5.25) of being in the low-high change in SST group relative to participants who were consistently low in SST. Conclusion: In this cross-sectional study of an international, online sample of adults, becomingunemployed was associated with a greater odds of both maintaining high levels of sedentary screentime, and increasing sedentary screen time to high levels. Action to protect people in the workforce from job loss and employment disruption in times of global economic upheaval may preventincreased adoption of maladaptive lifestyle behaviors, such as high levels of SST.

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