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Transforming geographic scale: a comparison of combined population and areal weighting to other interpolation methods

Overview of attention for article published in International Journal of Health Geographics, August 2017
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Title
Transforming geographic scale: a comparison of combined population and areal weighting to other interpolation methods
Published in
International Journal of Health Geographics, August 2017
DOI 10.1186/s12942-017-0102-z
Pubmed ID
Authors

Elaine Hallisey, Eric Tai, Andrew Berens, Grete Wilt, Lucy Peipins, Brian Lewis, Shannon Graham, Barry Flanagan, Natasha Buchanan Lunsford

Abstract

Transforming spatial data from one scale to another is a challenge in geographic analysis. As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the United States, we examined methods to estimate mortality within zones at varying distances from these facilities: (1) geographic centroid assignment, (2) population-weighted centroid assignment, (3) simple areal weighting, (4) combined population and areal weighting, and (5) geostatistical areal interpolation. For the primary study, we used county mortality counts from the National Center for Health Statistics (NCHS) and population data by census tract for the United States to estimate zone mortality. In this paper, to evaluate the five mortality estimation methods, we employed address-level mortality data from the state of Georgia in conjunction with census data. Our objective here is to identify the simplest method that returns accurate mortality estimates. The distribution of Georgia county adolescent cancer mortality counts mirrors the Poisson distribution of the NCHS counts for the U.S. Likewise, zone value patterns, along with the error measures of hierarchy and fit, are similar for the state and the nation. Therefore, Georgia data are suitable for methods testing. The mean absolute value arithmetic differences between the observed counts for Georgia and the five methods were 5.50, 5.00, 4.17, 2.74, and 3.43, respectively. Comparing the methods through paired t-tests of absolute value arithmetic differences showed no statistical difference among the methods. However, we found a strong positive correlation (r = 0.63) between estimated Georgia mortality rates and combined weighting rates at zone level. Most importantly, Bland-Altman plots indicated acceptable agreement between paired arithmetic differences of Georgia rates and combined population and areal weighting rates. This research contributes to the literature on areal interpolation, demonstrating that combined population and areal weighting, compared to other tested methods, returns the most accurate estimates of mortality in transforming small counts by county to aggregated counts for large, non-standard study zones. This conceptually simple cartographic method should be of interest to public health practitioners and researchers limited to analysis of data for relatively large enumeration units.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 16%
Student > Master 8 14%
Other 4 7%
Student > Doctoral Student 3 5%
Researcher 3 5%
Other 6 11%
Unknown 23 41%
Readers by discipline Count As %
Environmental Science 5 9%
Social Sciences 5 9%
Earth and Planetary Sciences 3 5%
Medicine and Dentistry 3 5%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 11 20%
Unknown 27 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 14 August 2017.
All research outputs
#14,360,215
of 22,996,001 outputs
Outputs from International Journal of Health Geographics
#402
of 629 outputs
Outputs of similar age
#176,586
of 317,751 outputs
Outputs of similar age from International Journal of Health Geographics
#9
of 13 outputs
Altmetric has tracked 22,996,001 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 629 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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 317,751 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.