Evidence map›Paper›PMID 33005987›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2021

Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology.

Jana A Hirsch, Kari A Moore, Jesse Cahill, James Quinn, Yuzhe Zhao, Felicia J Bayer, Andrew Rundle, Gina S Lovasi

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

53 citing papers in PubMed.

  1. Article
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  5. Measuring "third places": Comparing neighborhood data for cognitive health research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  9. Observational
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  14. Healthcare Access in the Aftermath: A Longitudinal Analysis of Disaster Impact on US Communities.International journal of environmental research and public health · 2025
    Article
  15. Article
  16. Article
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  18. Article
  19. Article
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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

8 authors.

Jana A HirschDepartment of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, PA, Philadelphia, USA.
Kari A MooreUrban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Jesse CahillDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
James QuinnDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
Yuzhe ZhaoUrban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Felicia J BayerUrban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA.
Andrew RundleDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York City, NY, USA.
Gina S LovasiDepartment of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, PA, Philadelphia, USA. gsl45@drexel.edu.ORCID 0000-0003-2613-9599

Funding

Characterizing health impacts of built environment features using complex dataR01HL131610 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SANCHEZ, BRISA N · 2017 to 2021
$3.6M
Communities Designed to Support Cardiovascular Health for Older AdultsR01AG049970 · NIA · DREXEL UNIVERSITY · PI LOVASI, GINA S · 2015 to 2018
$2.8M
ConProject-003R56AG049970 · NIA · DREXEL UNIVERSITY · PI LOVASI, GINA S · 2022 to 2023
$1.3M
NHLBI NIH HHS R01 HL131610NHLBI NIH HHS R01HL131610NIA NIH HHS 1R01AG049970NIA NIH HHS 3R01AG049970-04S1NIA NIH HHS R01 AG049970NIA NIH HHS R56 AG049970
6 · The paper itself

Abstract

Retail environments, such as healthcare locations, food stores, and recreation facilities, may be relevant to many health behaviors and outcomes. However, minimal guidance on how to collect, process, aggregate, and link these data results in inconsistent or incomplete measurement that can introduce misclassification bias and limit replication of existing research. We describe the following steps to leverage business data for longitudinal neighborhood health research: re-geolocating establishment addresses, preliminary classification using standard industrial codes, systematic checks to refine classifications, incorporation and integration of complementary data sources, documentation of a flexible hierarchical classification system and variable naming conventions, and linking to neighborhoods and participant residences. We show results of this classification from a dataset of locations (over 77 million establishment locations) across the contiguous U.S. from 1990 to 2014. By incorporating complementary data sources, through manual spot checks in Google StreetView and word and name searches, we enhanced a basic classification using only standard industrial codes. Ultimately, providing these enhanced longitudinal data and supplying detailed methods for researchers to replicate our work promotes consistency, replicability, and new opportunities in neighborhood health research.

Indexed as

CommerceResidence CharacteristicsEnvironmentHealth BehaviorHumansBusinessesClassificationCohort studiesCommercialFood environmentGeographyGIS or geographic information systemsPhysical activity destinationsPlace and health

Identifiers

PMID33005987
PMCPMC8079597

What OpenQuestion holds

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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.