Table 2 Bivariate analysis of dependent and independent variables
From: Utilization of breast cancer screening in Kenya: what are the determinants?
OR (95% CIs) | |
|---|---|
Level of education | |
Higher education | 1.00 |
Secondary education | 0.61 (0.56, 0.66)*** |
Primary education | 0.55 (0.51, 0.59)*** |
No education | 0.34 (0.31, 0.38)*** |
Marital status | |
Currently married | 1.00 |
Never married | 0.74 (0.70, 0.78)*** |
Formerly married | 1.01 (0.95, 1.08) |
Province of residence | |
North Eastern | 1.00 |
Coast | 1.65 (1.42, 1.91)*** |
Eastern | 1.86 (1.61, 2.14)*** |
Central | 3.24 (2.79, 3.75)*** |
Rift Valley | 1.91 (1.66, 2.20)*** |
Western | 1.75 (1.50, 2.03)*** |
Nyanza | 1.65 (1.42, 1.91)*** |
Nairobi | 2.63 (2.20, 3.13)*** |
Urban-rural residence | |
Urban | 1.00 |
Rural | 0.76 (0.73, 0.79)*** |
Employment status | |
Employed | 1.00 |
Unemployed | 0.69 (0.66, 0.72)*** |
Household wealth quintiles | |
Richest | 1.00 |
Richer | 0.81 (0.76, 0.86)*** |
Middle | 0.69 (0.65, 0.74)*** |
Poorer | 0.62 (0.58, 0.66)*** |
Poorest | 0.43 (0.41, 0.48)*** |
Insurance status | |
Insured | 1.00 |
Uninsured | 0.55 (0.52, 0.58)*** |
Age of respondents | |
45–49 | 1.00 |
40–44 | 1.03 (0.93, 1.13) |
35–39 | 0.99 (0.90, 1.08) |
30–34 | 1.00 (0.92, 1.10) |
25–29 | 0.98 (0.90, 1.07) |
20–24 | 0.83 (0.76, 0.91)*** |
15–19 | 0.55 (0.50, 0.60)*** |