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Table 4 Logistic regression of self-treatment on covariates

From: A cross-sectional study of antimicrobial use among self-medicating COVID-19 cases in Nyeri County, Kenya

Dep. = Self-treated 0 = No; 1 = Yes Coef Odds ratio SE P-value [95% Conf Interval] Sig
Sub-county Ref. = Nyeri town
Other areas − 0.093 0.912 0.64 0.885 − 1.346 1.161  
Gender Ref = Female
Male 0.199 1.220 0.546 0.716 − 0.871 1.269  
Age group Ref. = 19–29 years
30–39 − 3.218 0.040 1.029 0.002 − 5.235 − 1.202 **
40–49 − 1.344 0.261 1.065 0.207 − 3.431 0.743  
50–59 − 2.937 0.053 1.202 0.015 − 5.293 − 0.581 *
60 +  − 4.909 0.007 1.68 0.003 − 8.2 − 1.617 **
Marital status Ref. = Married
Single − 0.509 0.601 0.784 0.516 − 2.046 1.027  
Education Ref. = High school and less
Degree or postgraduate − 0.769 0.463 0.719 0.284 − 2.178 0.639  
Occupation Ref. = Business
Farmers 0.545 1.724 0.929 0.558 − 1.276 2.365  
Health − 0.662 0.516 0.799 0.407 − 2.229 0.904  
Teachers − 0.748 0.473 0.94 0.426 − 2.591 1.095  
Income Ref. = 50–100 k
 < 50,000 − 0.139 0.870 0.805 0.863 − 1.717 1.439  
 > 100,000 0.100 1.105 1.072 0.926 − 2.002 2.202  
No income − 1.333 0.264 1.466 0.363 − 4.207 1.541  
Private insurance Ref. = No
Yes 0.719 2.053 0.668 0.282 − 0.59 2.029  
Covid symptoms Ref. = No
Yes 2.247 9.461 0.815 0.006 0.65 3.844 **
Aware of regulations Ref. = No
Yes 1.117 3.056 0.558 0.045 0.024 2.21 *
Associated with risk Ref. = No
Yes 0.169 1.184 1.183 0.887 − 2.149 2.487  
What to be done: create awareness Ref. = No
Yes 1.533 4.632 0.616 0.013 0.326 2.74 *
What to be done: Implement laws Ref. = No
Yes 0.62 1.858 0.64 0.333 − 0.635 1.874  
Constant − 1.597 0.203 2.018 0.429 − 5.552 2.357  
  1. *P < 0.05, **P < 0.01