Table 3 Multivariate generalized estimating equation model† to examine the association between health service utilization by different types and explanatory variables in Afghanistan, Bangladesh, and India
Afghanistan | Bangladesh | India | ||||
|---|---|---|---|---|---|---|
Variables | In-person care | Non-conventional healthcare | In-person care | Non-conventional healthcare | In-person care | Non-conventional healthcare |
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
Environmental factor | ||||||
After one year of COVID-19 outbreak | 0.7 (0.6,0.9)* | 1.4 (1.1,1.8)* | 0.4 (0.09,2.5) | 2.9 (0.4,20.0) | 0.6 (0.3,1.1) | 1.6 (0.9,2.8) |
Pre-disposing factors | ||||||
26 years and above | 0.8 (0.6,1.1) | 1.1 (0.8,1.4) | 1.1 (0.8,4.6) | 0.8 (0.2,3.6) | 0.8 (0.4,1.4) | 1.0 (0.6,1.9) |
Male | 1.2 (0.8,1.9) | 0.8 (0.5,1.2) | - | - | 0.7 (0.3,1.5) | 1.3 (0.6,2.7) |
Less than tertiary education | 0.9 (0.7,1.2) | 1.0 (0.8,1.3) | 3.8 (0.6,22.8) | 0.1 (0.02,1.2) | 0.9 (0.5,1.7) | 1.0 (0.5,1.8) |
Large household | 1.3 (1.06,1.7)* | 0.6 (0.5,0.8)* | 1.4 (0.2,10.0) | 0.5 (0.08,3.0) | 1.1 (0.6,2.1) | 0.8 (0.4,1.5) |
Enabling/Disabling factors | ||||||
Rural | 1.0 (0.7,1.2) | 1.0 (0.7,1.2) | 1.2 (0.2,5.8) | 0.9 (0.2,3.5) | 0.8 (0.5,1.5) | 1.0 (0.6,1.8) |
Poor financial status | 0.9 (0.7,1.2) | 0.9 (0.7,1.2) | 0.2 (0.02,3.7) | 3.8 (0.2,53.5) | 0.7 (0.4,1.3) | 0.6 (0.2,1.3) |
Not participating in any income-generating activity | 0.8 (0.6,1.1) | 1.1 (0.8,1.4) | 0.8 (0.2,3.3) | 0.8 (0.2,3.1) | 1.1 (0.6,2.2) | 1.1 (0.6,2.1) |
Income | 1.08 (1.02,1.1)* | 0.9 (0.8,0.9)* | 0.7 (0.4,1.2) | 1.3 (0.7,2.5) | 1.0 (0.9,1.1) | 0.9 (0.8,1.0) |
Need for care factors | ||||||
Need assistance in managing NCDs | 0.8 (0.6,1.1) | 1.2 (0.9,1.6) | 2.5 (0.6,10.4) | 0.4 (0.09,2.2) | 0.8 (0.4,1.6) | 1.2 (0.6,2.3) |