Evidence map›Paper›PMID 21684793›Full record

ArticleHealth & place2011

The socio-spatial neighborhood estimation method: an approach to operationalizing the neighborhood concept.

Malcolm P Cutchin, Karl Eschbach, Christine A Mair, Hyunsu Ju, James S Goodwin

Abstract read
In one paragraph

Article in Health & place, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Pathways from neighborhood adversity to life satisfaction among older African American adults.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025
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  13. Understanding Embodiment in Place-Health Research: Approaches, Limitations, and Opportunities.Journal of urban health : bulletin of the New York Academy 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

5 authors.

Malcolm P CutchinDepartment of Allied Health Sciences, University of North Carolina, CB #7122, Bondurant Hall, Suite 2050, Chapel Hill, NC 27599-7122, USA. mcutchin@med.unc.edu
Karl Eschbach
Christine A Mair
Hyunsu Ju
James S Goodwin

Funding

UTMB Center for Population Health and Health DisparitiesP50CA105631 · NCI · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI GOODWIN, MD, JAMES S. · 2003 to 2008
$8.5M
Established Investigator Award in Cancer Prevention & ControlK05CA134923 · NCI · UNIVERSITY OF TEXAS MED BR GALVESTON · PI GOODWIN, MD, JAMES S. · 2008 to 2019
$1.0M
NCI NIH HHS K05 CA134923NCI NIH HHS P50CA10563NCI NIH HHS P50 CA105631
6 · The paper itself

Abstract

The literature on neighborhoods and health highlights the difficulty of operationalizing "neighborhood" in a conceptually and empirically valid manner. Most studies, however, continue to define neighborhoods using less theoretically relevant boundaries, risking erroneous inferences from poor measurement. We review an innovative methodology to address this problem, called the socio-spatial neighborhood estimation method (SNEM). To estimate neighborhood boundaries, researchers used a theoretically informed combination of qualitative GIS and on-the-ground observations in Texas City, Texas. Using data from a large sample, we assessed the SNEM-generated neighborhood units by comparing intra-class correlation coefficients (ICCs) and multi-level model parameter estimates of SNEM-based measures against those for census block groups and regular grid cells. ICCs and criterion-related validity evidence using SF-36 outcome measures indicate that the SNEM approach to operationalization could improve inferences based on neighborhoods and health research.

Indexed as

Residence CharacteristicsTerminology as TopicGeographic Information SystemsHumansResearchSocioeconomic FactorsTexas

Identifiers

PMID21684793
PMCPMC3171635

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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.