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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Monitoring subnational regional inequalities in health: measurement approaches and challenges
|
|---|---|
| Published in |
International Journal for Equity in Health, January 2016
|
| DOI | 10.1186/s12939-016-0307-y |
| Pubmed ID | |
| Authors |
Ahmad Reza Hosseinpoor, Nicole Bergen, Aluisio J. D. Barros, Kerry L. M. Wong, Ties Boerma, Cesar G. Victora |
| Abstract |
Monitoring inequalities based on subnational regions is a useful practice to unmask geographical differences in health, and deploy targeted, equity-oriented interventions. Our objective is to describe, compare and contrast current methods of measuring subnational regional inequality. We apply a selection of summary measures to empirical data from four low- or middle-income countries to highlight the characteristics and overall performance of the different measures. We use data from Demographic and Health Surveys conducted in Bangladesh, Egypt, Ghana and Zimbabwe to calculate subnational regional inequality estimates for reproductive, maternal, newborn, and child health services generated from 11 summary measures: pairwise measures included high to low absolute difference, high to low relative difference, and high to low ratio; complex measures included population attributable risk, weighted variance, absolute weighted mean difference from overall mean, index of dissimilarity, Theil index, population attributable risk percentage, coefficient of variation, and relative weighted mean difference from overall mean. Four of these summary measures (high to low absolute difference, high to low ratio, absolute weighted mean difference from overall mean, and relative weighted mean difference from overall mean) were selected to compare their performance in measuring trend over time in inequality for one health indicator. Overall, the 11 different measures were more remarkable for their similarities than for their differences. Pairwise measures tended to support the same conclusions as complex summary measures-that is, by identifying same best and worst coverage indicators in each country and indicating similar time trends. Complex measures may be useful to illustrate more nuanced results in countries with a great number of subnational regions. When pairwise and complex measures lead to the same conclusions about the state of subnational regional inequality, pairwise measures may be sufficient for reporting inequality. In cases where complex measures are required, mean difference from mean measures can be easily communicated to non-technical audiences. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 42% |
| United Kingdom | 2 | 17% |
| Australia | 1 | 8% |
| Colombia | 1 | 8% |
| Chile | 1 | 8% |
| Uganda | 1 | 8% |
| Unknown | 1 | 8% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 75% |
| Practitioners (doctors, other healthcare professionals) | 3 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 186 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 33 | 18% |
| Student > Master | 30 | 16% |
| Researcher | 28 | 15% |
| Student > Bachelor | 13 | 7% |
| Student > Doctoral Student | 9 | 5% |
| Other | 31 | 17% |
| Unknown | 43 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 36 | 19% |
| Medicine and Dentistry | 31 | 17% |
| Nursing and Health Professions | 24 | 13% |
| Economics, Econometrics and Finance | 6 | 3% |
| Agricultural and Biological Sciences | 4 | 2% |
| Other | 30 | 16% |
| Unknown | 56 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 18 January 2023.
All research outputs
#2,425,304
of 23,920,246 outputs
Outputs from International Journal for Equity in Health
#420
of 2,020 outputs
Outputs of similar age
#43,586
of 402,658 outputs
Outputs of similar age from International Journal for Equity in Health
#8
of 49 outputs
Altmetric has tracked 23,920,246 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,020 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,658 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.