Evidence map›Paper›PMID 29792189›Full record

ArticleInternational journal of health geographics2018

A cross-sectional ecological analysis of international and sub-national health inequalities in commercial geospatial resource availability.

Winfred Dotse-Gborgbortsi, Nicola Wardrop, Ademola Adewole, Mair L H Thomas, Jim Wright

Abstract read
In one paragraph

Article in International journal of health geographics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. A Practical Strategy of Informatics, Geospatial Mapping, Geodemographic Segmentation, and Regression Analyses to Address Nonadherence to Colorectal Cancer Screening.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Article
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  8. Slums, Space, and State of Health-A Link between Settlement Morphology and Health Data.International journal of environmental research and public health · 2020
    Article
  9. Creating small-area deprivation indices: a guide for stages and options.Journal of epidemiology and community health · 2020
    Review
  10. Spatial Video Health Risk Mapping in Informal Settlements: Correcting GPS Error.International journal of environmental research and public health · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Winfred Dotse-GborgbortsiKibi Government Hospital, Ghana Health Service, Accra, Ghana.
Nicola WardropGeography and Environment, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.
Ademola AdewoleGeography and Environment, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.
Mair L H ThomasGeography and Environment, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.
Jim WrightGeography and Environment, University of Southampton, Highfield, Southampton, SO17 1BJ, UK. j.a.wright@soton.ac.uk.

Funding

Economic and Social Research Council ES/P000673/1
6 · The paper itself

Abstract

backgroundCommercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need.

methodsTo examine the distribution of commercial geospatial data resources relative to health needs, we assembled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specific (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria.

resultsInternationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospatial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. Countries such as South Africa have comparatively high commercial geospatial data availability despite high mortality, whilst countries such as South Korea have comparatively low data availability and low mortality. Sub-nationally, evidence was mixed as to whether geocoding success was lowest in more deprived districts.

conclusionsTo our knowledge, this is the first global analysis of commercial geospatial data resources in relation to health outcomes. In countries such as South Africa where there is high mortality but also comparatively rich commercial geospatial data, these data resources are a potential resource for examining healthcare utilisation that requires further evaluation. In countries such as Sierra Leone where there is high mortality but minimal commercial geospatial data, alternative approaches such as open data use are needed in quantifying patient travel times, geocoding patient addresses, and characterising patients' neighbourhoods.

Indexed as

Geographic MappingHealth ResourcesHealth Status DisparitiesInternationalitySocioeconomic FactorsBiasCross-Sectional StudiesGhanaHumansNigeriaDigital divideDrive-timesGeocodingGeospatial dataGISHealth inequalitiesInverse care lawNeighbourhood statisticsPatient travel

Identifiers

PMID29792189
PMCPMC5966850

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.