Evidence map›Paper›PMID 28235407›Full record

ArticleEnvironmental health : a global access science source2017

Accuracy of two geocoding methods for geographic information system-based exposure assessment in epidemiological studies.

Elodie Faure, Aurélie M N Danjou, Françoise Clavel-Chapelon, Marie-Christine Boutron-Ruault, Laure Dossus, Béatrice Fervers

Abstract read
In one paragraph

Article in Environmental health : a global access science source, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  8. Enrichment of a Data Lake to Support Population Health Outcomes Studies Using Social Determinants Linked EHR Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
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  18. Chronic Kidney Disease in Agricultural Communities.The American journal of medicine · 2019
    Review
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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

6 authors.

Elodie FaureCancer and Environnent Department, Centre Léon Bérard, 28 rue Laennec, 69373, Lyon, Cedex, 08, France.
Aurélie M N DanjouCancer and Environnent Department, Centre Léon Bérard, 28 rue Laennec, 69373, Lyon, Cedex, 08, France.
Françoise Clavel-ChapelonInserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Team "Generations for Health", 94805, Villejuif, France.
Marie-Christine Boutron-RuaultInserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Team "Generations for Health", 94805, Villejuif, France. Marie-Christine.BOUTRON@gustaveroussy.fr.
Laure DossusInserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Team "Generations for Health", 94805, Villejuif, France.
Béatrice FerversCancer and Environnent Department, Centre Léon Bérard, 28 rue Laennec, 69373, Lyon, Cedex, 08, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEnvironmental exposure assessment based on Geographic Information Systems (GIS) and study participants' residential proximity to environmental exposure sources relies on the positional accuracy of subjects' residences to avoid misclassification bias. Our study compared the positional accuracy of two automatic geocoding methods to a manual reference method.

methodsWe geocoded 4,247 address records representing the residential history (1990-2008) of 1,685 women from the French national E3N cohort living in the Rhône-Alpes region. We compared two automatic geocoding methods, a free-online geocoding service (method A) and an in-house geocoder (method B), to a reference layer created by manually relocating addresses from method A (method R). For each automatic geocoding method, positional accuracy levels were compared according to the urban/rural status of addresses and time-periods (1990-2000, 2001-2008), using Chi Square tests. Kappa statistics were performed to assess agreement of positional accuracy of both methods A and B with the reference method, overall, by time-periods and by urban/rural status of addresses.

resultsRespectively 81.4% and 84.4% of addresses were geocoded to the exact address (65.1% and 61.4%) or to the street segment (16.3% and 23.0%) with methods A and B. In the reference layer, geocoding accuracy was higher in urban areas compared to rural areas (74.4% vs. 10.5% addresses geocoded to the address or interpolated address level, p < 0.0001); no difference was observed according to the period of residence. Compared to the reference method, median positional errors were 0.0 m (IQR = 0.0-37.2 m) and 26.5 m (8.0-134.8 m), with positional errors <100 m for 82.5% and 71.3% of addresses, for method A and method B respectively. Positional agreement of method A and method B with method R was 'substantial' for both methods, with kappa coefficients of 0.60 and 0.61 for methods A and B, respectively.

conclusionOur study demonstrates the feasibility of geocoding residential addresses in epidemiological studies not initially recorded for environmental exposure assessment, for both recent addresses and residence locations more than 20 years ago. Accuracy of the two automatic geocoding methods was comparable. The in-house method (B) allowed a better control of the geocoding process and was less time consuming.

Indexed as

Epidemiologic StudiesGeographic MappingAdultAgedBreast NeoplasmsEnvironmental ExposureFemaleGeographic Information SystemsHumansMiddle AgedEnvironmental epidemiologyEpidemiologyGeocodingGeographic information systemGISResidential history

Identifiers

PMID28235407
PMCPMC5324215

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Registered trials

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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.