Evidence map›Paper›PMID 37971072›Full record

ArticleRevista de saude publica2023

Geocoding processes in cohort studies: methods applied in the EpiFloripa Aging.

Catharina Cavasin Salvador, Adalberto Aparecido Dos Santos Lopes, Danilo Resendes, Fernanda Faccio Demarco, Marcelo Dutra Della Justina, Renato Tibiriçá de Saboya, Cassiano Ricardo Rech, Eleonora d'Orsi

Abstract read
In one paragraph

Article in Revista de saude publica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Catharina Cavasin SalvadorUniversidade Estadual de Londrina. Programa Associado de Pós-Graduação em Arquitetura e Urbanismo. Londrina, PR, Brasil.ORCID http://orcid.org/0000-0002-9038-5412
Adalberto Aparecido Dos Santos LopesUniversidade Federal de Minas Gerais. Observatório de Saúde Urbana. Belo Horizonte, MG, Brasil.ORCID http://orcid.org/0000-0002-3001-6412
Danilo ResendesUniversidade Federal de Santa Catarina. Programa de Pós-Graduação em Arquitetura e Urbanismo. Florianópolis, SC, Brasil.ORCID http://orcid.org/0000-0002-0892-2742
Fernanda Faccio DemarcoUniversidade Federal de Santa Catarina. Programa de Pós-Graduação em Arquitetura e Urbanismo. Florianópolis, SC, Brasil.ORCID http://orcid.org/0000-0003-3581-5405
Marcelo Dutra Della JustinaUniversidade Federal de Santa Catarina. Programa de Pós-Graduação em Educação Física. Florianópolis, SC, Brasil.ORCID http://orcid.org/0000-0001-9301-9808
Renato Tibiriçá de SaboyaUniversidade Federal de Santa Catarina. Centro Tecnológico. Departamento de Arquitetura e Urbanismo. Florianópolis, SC, Brasil.ORCID http://orcid.org/0000-0003-4631-1413
Cassiano Ricardo RechUniversidade Federal de Santa Catarina. Centro de Desportos. Departamento de Educação Física. Florianópolis, SC, Brasil.ORCID http://orcid.org/0000-0002-9647-3448
Eleonora d'OrsiUniversidade Federal de Santa Catarina. Centro de Ciências da Saúde. Departamento de Saúde Pública. Florianópolis, SC, Brasil.ORCID http://orcid.org/0000-0003-2027-1089

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo describe the process and epidemiological implications of georeferencing in EpiFloripa Aging samples (2009-2019).

methodThe EpiFloripa Aging Cohort Study sought to investigate and monitor the living and health conditions of the older adult population (≥ 60) of Florianópolis in three study waves (2009/2010, 2013/2014, 2017/2019). With an automatic geocoding tool, the residential addresses were spatialized, allowing to investigate the effect of the georeferencing sample losses regarding 19 variables, evaluated in the three waves. The influence of different neighborhood definitions (census tracts, Euclidean buffers, and buffers across the street network) was examined in the results of seven variables: area, income, residential density, mixed land use, connectivity, health unit count, and public open space count. Pearson's correlation coefficients were calculated to evaluate the differences between neighborhood definitions according to three variables: contextual income, residential density, and land use diversity.

resultThe losses imposed by geocoding (6%, n = 240) caused no statistically significant difference between the total sample and the geocoded sample. The analysis of the study variables suggests that the geocoding process may have included a higher proportion of participants with better income, education, and living conditions. The correlation coefficients showed little correspondence between measures calculated by the three neighborhood definitions (r = 0.37-0.54). The statistical difference between the variables calculated by buffers and census tracts highlights limitations in their use in the description of geospatial attributes.

conclusionDespite the challenges related to geocoding, such as inconsistencies in addresses, adequate correction and verification mechanisms provided a high rate of assignment of geographic coordinates, the findings suggest that adopting buffers, favored by geocoding, represents a potential for spatial epidemiological analyses by improving the representation of environmental attributes and the understanding of health outcomes.

Indexed as

Geographic Information SystemsGeographic MappingAgedAgingBrazilCohort StudiesHumansMiddle Aged

Identifiers

PMID37971072
PMCPMC10681526

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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.