# Table 4 Multiple linear regression of significant independent predictors of COVID-19-Impact on Quality of Life

Variables Bivariate linear regression Multiple linear regression model
β (95% CI) P value β (95% CI) P value
Age 0.17 (0.1 to 0.3) < 0.001 0.09 (− 0.009 to 0.2) 0.07
Sex 0.14 (0.06 to 0.26) 0.001 0.1 (0.02 to 0.2) 0.02
Employment − 0.02 (− 0.1 to 0.08) 0.6
Monthly income 0.1 (0.03 to 0.2) 0.01 0.1 (0.004 to 0.2) 0.04
Educational level 0.09 (0.01 to 0.2) 0.03
Marital status 0.17 (0.1 to 0.3) < 0.001
Smoking − 0.02 (− 0.16 to 0.1) 0.6
Comorbidities 0.13 (0.06 to 0.3) 0.004
Previous Covid-19 infection − 0.002 (− 0.1 to 0.1) 0.9
Personally know someone infected with COVID-19 0.18 (0.12 to 0.3) < 0.001 0.15 (0.08 to 0.3) 0.001
Personally know someone who died of COVID-19 0.1 (0.008 to 0.2) 0.04
Have a symptom suggestive of COVID-19 in past 14 days 0.07 (− 0.02 to 0.2) 0.1
Duration 0.17 (0.1 to 0.3) < 0.001 0.1 (0.006 to 0.2) 0.04
Constant 2.03
Model F 9.1
Model R2 0.1
P value < 0.001
1. β: regression coefficient, CI: Confidence Interval, Model F: Model Analysis of Variance F test, Model R2: Model R square. Qualitative variables were included in the model as dummy variables. They are coded as 0: age < 40 years, male sex, not employed, sufficient income, > secondary education, not married, not smoker, no comorbidities, no previous COVID-19 infection, not know someone infected with COVID -19, not know someone died with COVID -19, no symptoms suggestive of COVID-19 in the past 14 days, the second half of data collection period