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Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of
Various address georeferencing (AG) tools are currently available. But little is known about the quality of each tool. Using data from the EPIPorto cohort we compared the most commonly used AG tools in terms of positional error (PE) and subjects' misclassification according to census tract soci...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254921/ https://www.ncbi.nlm.nih.gov/pubmed/25469514 http://dx.doi.org/10.1371/journal.pone.0114130 |
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author | Ribeiro, Ana Isabel Olhero, Andreia Teixeira, Hugo Magalhães, Alexandre Pina, Maria Fátima |
author_facet | Ribeiro, Ana Isabel Olhero, Andreia Teixeira, Hugo Magalhães, Alexandre Pina, Maria Fátima |
author_sort | Ribeiro, Ana Isabel |
collection | PubMed |
description | Various address georeferencing (AG) tools are currently available. But little is known about the quality of each tool. Using data from the EPIPorto cohort we compared the most commonly used AG tools in terms of positional error (PE) and subjects' misclassification according to census tract socioeconomic status (SES), a widely used variable in epidemiologic studies. Participants of the EPIPorto cohort (n = 2427) were georeferenced using Geographical Information Systems (GIS) and Google Earth (GE). One hundred were randomly selected and georeferenced using three additional tools: 1) cadastral maps (gold-standard); 2) Global Positioning Systems (GPS) and 3) Google Earth, single and in a batch. Mean PE and the proportion of misclassified individuals were compared. Google Earth showed lower PE than GIS, but 10% of the addresses were imprecisely positioned. Thirty-eight, 27, 16 and 14% of the participants were located in the wrong census tract by GIS, GPS, GE (batch) and GE (single), respectively (p<0.001). Misclassification according to SES was less frequent but still non-negligible −14.4, 8.1, 4.2 and 2% (p<0.001). The quality of georeferencing differed substantially between AG tools. GE seems to be the best tool, but only if prudently used. Epidemiologic studies using spatial data should start including information on the quality and accuracy of their georeferencing tools and spatial datasets. |
format | Online Article Text |
id | pubmed-4254921 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-42549212014-12-11 Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of Ribeiro, Ana Isabel Olhero, Andreia Teixeira, Hugo Magalhães, Alexandre Pina, Maria Fátima PLoS One Research Article Various address georeferencing (AG) tools are currently available. But little is known about the quality of each tool. Using data from the EPIPorto cohort we compared the most commonly used AG tools in terms of positional error (PE) and subjects' misclassification according to census tract socioeconomic status (SES), a widely used variable in epidemiologic studies. Participants of the EPIPorto cohort (n = 2427) were georeferenced using Geographical Information Systems (GIS) and Google Earth (GE). One hundred were randomly selected and georeferenced using three additional tools: 1) cadastral maps (gold-standard); 2) Global Positioning Systems (GPS) and 3) Google Earth, single and in a batch. Mean PE and the proportion of misclassified individuals were compared. Google Earth showed lower PE than GIS, but 10% of the addresses were imprecisely positioned. Thirty-eight, 27, 16 and 14% of the participants were located in the wrong census tract by GIS, GPS, GE (batch) and GE (single), respectively (p<0.001). Misclassification according to SES was less frequent but still non-negligible −14.4, 8.1, 4.2 and 2% (p<0.001). The quality of georeferencing differed substantially between AG tools. GE seems to be the best tool, but only if prudently used. Epidemiologic studies using spatial data should start including information on the quality and accuracy of their georeferencing tools and spatial datasets. Public Library of Science 2014-12-03 /pmc/articles/PMC4254921/ /pubmed/25469514 http://dx.doi.org/10.1371/journal.pone.0114130 Text en © 2014 Ribeiro et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ribeiro, Ana Isabel Olhero, Andreia Teixeira, Hugo Magalhães, Alexandre Pina, Maria Fátima Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of |
title | Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of |
title_full | Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of |
title_fullStr | Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of |
title_full_unstemmed | Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of |
title_short | Tools for Address Georeferencing – Limitations and Opportunities Every Public Health Professional Should Be Aware Of |
title_sort | tools for address georeferencing – limitations and opportunities every public health professional should be aware of |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4254921/ https://www.ncbi.nlm.nih.gov/pubmed/25469514 http://dx.doi.org/10.1371/journal.pone.0114130 |
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