Selected article for: "adjusted multivariable logistic regression analysis and logistic regression analysis"

Author: Pokora, Roman; Kutschbach, Susan; Weigl, Matthias; Braun, Detlef; Epple, Annegret; Lorenz, Eva; Grund, Stefan; Hecht, Juergen; Hollich, Helmut; Rietschel, Peter; Schneider, Frank; Sohmen, Roland; Taylor, Katherine; Dienstbuehl, Isabel
Title: Investigation of superspreading COVID-19 outbreak events in meat and poultry processing plants in Germany: A cross-sectional study
  • Cord-id: z5997w6l
  • Document date: 2021_6_10
  • ID: z5997w6l
    Snippet: Since May 2020, several COVID-19 outbreaks have occurred in the German meat industry despite various protective measures, and temperature and ventilation conditions were considered as possible high-risk factors. This cross-sectional study examined meat and poultry plants to assess possible risk factors. Companies completed a self-administered questionnaire on the work environment and protective measures taken to prevent SARS-CoV-2 infection. Multivariable logistic regression analysis adjusted fo
    Document: Since May 2020, several COVID-19 outbreaks have occurred in the German meat industry despite various protective measures, and temperature and ventilation conditions were considered as possible high-risk factors. This cross-sectional study examined meat and poultry plants to assess possible risk factors. Companies completed a self-administered questionnaire on the work environment and protective measures taken to prevent SARS-CoV-2 infection. Multivariable logistic regression analysis adjusted for the possibility to distance at least 1.5 meters, break rules, and employment status was performed to identify risk factors associated with COVID-19 cases. Twenty-two meat and poultry plants with 19,072 employees participated. The prevalence of COVID-19 in the seven plants with more than 10 cases was 12.1% and was highest in the deboning and meat cutting area with 16.1%. A subsample analysis where information on maximal ventilation rate per employee was available revealed an association with the ventilation rate (adjusted odds ratio (AOR) 0.996, 95% CI 0.993–0.999). When including temperature as an interaction term in the working area, the association with the ventilation rate did not change. When room temperatures increased, the chance of testing positive for COVID-19 (AOR 0.90 95% CI 0.82–0.99) decreased, and the chance for testing positive for COVID-19for the interaction term (AOR 1.001, 95% CI 1.000–1.003) increased. Employees who work where a minimum distance of less than 1.5 m between workers was the norm had a higher chance of testing positive (AOR 3.61; 95% CI 2.83–4.6). Our results further indicate that climate conditions and low outdoor air flow are factors that can promote the spread of SARS-CoV-2 aerosols. A possible requirement for pandemic mitigation strategies in industrial workplace settings is to increase the ventilation rate.

    Search related documents:
    Co phrase search for related documents
    • absolute relative and additional analysis: 1
    • absolute relative and adjusted model: 1, 2
    • absolute relative and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9
    • absolute relative frequency and adjusted model: 1
    • absolute relative frequency and logistic regression: 1
    • absolute value and activity level: 1
    • absolute value and actual number: 1
    • absolute value and actual value: 1
    • absolute value and additional information: 1
    • absolute value and adjusted model: 1
    • absolute value and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9
    • activity level and additional analysis: 1
    • activity level and adjusted model: 1
    • activity level and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
    • actual number and additional information: 1
    • actual number and logistic regression: 1, 2
    • actual value and logistic regression: 1, 2, 3
    • additional analysis and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
    • additional information and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16