• J Urban Health · Apr 2021

    Web Data Mining: Validity of Data from Google Earth for Food Retail Evaluation.

    • Mariana Carvalho de Menezes, Vanderlei Pascoal de Matos, Maria de Fátima de Pina, Bruna Vieira de Lima Costa, MendesLarissa LouresLLDepartment of Nutrition, Universidade Federal de Minas Gerais, Av. Alfredo Balena 190, Belo Horizonte, MG, 30130-100, Brazil., PessoaMilene CristineMCDepartment of Nutrition, Universidade Federal de Minas Gerais, Av. Alfredo Balena 190, Belo Horizonte, MG, 30130-100, Brazil., Paulo Roberto Borges de Souza-Junior, Amélia Augusta de Lima Friche, CaiaffaWaleska TeixeiraWTFaculdade de Medicina, Universidade Federal de Minas Gerais. Observatório de Saúde Urbana, Av. Alfredo Balena 190, Belo Horizonte, MG, 30130-100, Brazil., and de Oliveira CardosoLetíciaLNational School of Public Health, Fiocruz-RJ, Rua Leopoldo Bulhões, 1480- Manguinhos, Rio de Janeiro, 21041-210, Brazil..
    • National School of Public Health, Fiocruz-RJ, Rua Leopoldo Bulhões, 1480- Manguinhos, Rio de Janeiro, 21041-210, Brazil. marysnut@gmail.com.
    • J Urban Health. 2021 Apr 1; 98 (2): 285-295.

    AbstractTo overcome the challenge of obtaining accurate data on community food retail, we developed an innovative tool to automatically capture food retail data from Google Earth (GE). The proposed method is relevant to non-commercial use or scholarly purposes. We aimed to test the validity of web sources data for the assessment of community food retail environment by comparison to ground-truth observations (gold standard). A secondary aim was to test whether validity differs by type of food outlet and socioeconomic status (SES). The study area included a sample of 300 census tracts stratified by SES in two of the largest cities in Brazil, Rio de Janeiro and Belo Horizonte. The GE web service was used to develop a tool for automatic acquisition of food retail data through the generation of a regular grid of points. To test its validity, this data was compared with the ground-truth data. Compared to the 856 outlets identified in 285 census tracts by the ground-truth method, the GE interface identified 731 outlets. In both cities, the GE interface scored moderate to excellent compared to the ground-truth data across all of the validity measures: sensitivity, specificity, positive predictive value, negative predictive value and accuracy (ranging from 66.3 to 100%). The validity did not differ by SES strata. Supermarkets, convenience stores and restaurants yielded better results than other store types. To our knowledge, this research is the first to investigate using GE as a tool to capture community food retail data. Our results suggest that the GE interface could be used to measure the community food environment. Validity was satisfactory for different SES areas and types of outlets.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…