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

Table 4 Logistic regression of self-treatment on covariates

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

ISSN: 2047-2994