|
Full regression analysis for predicting the influence of physician and nurse density and other socioeconomic variables on IMR, U5MR, MMR and LE in LMICs and MHICs at a global level |
||||
| IMR |
U5MR |
MMR |
LE |
|
|
|
||||
| Physician density |
||||
| LMICs |
-0.177** |
-0.317** |
-0.400** |
0.101** |
| MHICs |
-0.643** |
-0.792** |
-0.878** |
0.186** |
| Nurse density |
||||
| LMICs |
-0.026 |
0.044 |
-0.284* |
-0.034 |
| MHICs |
-0.197 |
-0.238 |
-0.397* |
-0.032 |
| Female literacy |
||||
| LMICs |
-0.573** |
-0.689** |
-0.491* |
0.088* |
| MHICs |
-4.277* |
-5.250* |
-5.051 |
0.344 |
| Health expenditure as % of GDP |
||||
| LMICs |
-0.433** |
-0.459* |
-0.348 |
0.023 |
| MHICs |
0.090 |
0.310 |
0.405 |
-0.069 |
| R2 |
||||
| LMICs |
0.556** |
0.636** |
0.716** |
0.615** |
| MHICs |
0.584** |
0.592** |
0.485** |
0.560** |
| N |
||||
| LMICs |
93 |
94 |
93 |
94 |
| MHICs |
46 |
46 |
43 |
46 |
|
* p-value < 0.05 ** p-value < 0.01 | ||||
El-Jardali et al. Human Resources for Health 2007 5:9 doi:10.1186/1478-4491-5-9 |
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