| Title |
Effect of health development assistance on health status in sub-Saharan Africa
|
|---|---|
| Published in |
Risk Management and Healthcare Policy, April 2016
|
| DOI | 10.2147/rmhp.s101343 |
| Pubmed ID | |
| Authors |
Keneni Gutema Negeri, Damen Halemariam |
| Abstract |
Data on the effect of health aid on the health status in developing countries are inconclusive. Moreover, studies on this issue in sub-Saharan Africa are scarce. Therefore, this study aims to analyze the effect of health development aid in sub-Saharan Africa. Using panel data analytic method, as well as infant mortality rate as a proxy for health status, this study examines the effect of health aid on infant mortality rate in sub-Saharan Africa. The panel was constructed from data on 43 countries for the period 1990-2010. Fixed effect, random effect, and first difference generalized method of moments estimator were used for estimation. Health development aid has a statistically significant positive effect. A 1% increase of health development assistance per capita saves the lives of two infants per 1,000 live births (P=0.000) in the region. Contrary to health aid pessimists' view, this study observes the fact that health development assistance has strong favorable effect in improving health status in sub-Saharan Africa. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 26% |
| Student > Ph. D. Student | 6 | 16% |
| Student > Postgraduate | 3 | 8% |
| Researcher | 3 | 8% |
| Student > Doctoral Student | 2 | 5% |
| Other | 6 | 16% |
| Unknown | 8 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 24% |
| Nursing and Health Professions | 6 | 16% |
| Economics, Econometrics and Finance | 3 | 8% |
| Business, Management and Accounting | 2 | 5% |
| Social Sciences | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 13 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 December 2020.
All research outputs
#1,480,542
of 25,576,275 outputs
Outputs from Risk Management and Healthcare Policy
#46
of 740 outputs
Outputs of similar age
#24,710
of 315,173 outputs
Outputs of similar age from Risk Management and Healthcare Policy
#2
of 8 outputs
Altmetric has tracked 25,576,275 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 740 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has done particularly well, scoring higher than 93% of its peers.
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We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.