Systematic neighborhood observations at high spatial resolution: methodology and assessment of potential benefits

There is a growing body of public health research documenting how characteristics of neighborhoods are associated with differences in the health status of residents. However, little is known about how the spatial resolution of neighborhood observational data or community audits affects the identific...

Full description

Saved in:

Bibliographic Details
Published in:	PloS one Vol. 6; no. 6; p. e20225
Main Authors:	Leonard, Tammy C M, Caughy, Margaret O'Brien, Mays, Judith K, Murdoch, James C
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 03-06-2011 Public Library of Science (PLoS)
Subjects:	Analysis Biology Correlation analysis Cost benefit analysis Data Data Collection - statistics & numerical data Drug use Earth Sciences Geography Geospatial data Health research Health status Humans Literature reviews Logit models Low income groups Medicine Methods Neighborhoods Political science Public health Public Health - statistics & numerical data Reliability analysis Reproducibility of Results Researchers Residence Characteristics - statistics & numerical data Science Policy Social and Behavioral Sciences Sociology Spatial data Spatial discrimination Spatial resolution Studies Canada Montreal Quebec Canada Sweden United States > US Texas
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	There is a growing body of public health research documenting how characteristics of neighborhoods are associated with differences in the health status of residents. However, little is known about how the spatial resolution of neighborhood observational data or community audits affects the identification of neighborhood differences in health. We developed a systematic neighborhood observation instrument for collecting data at very high spatial resolution (we observe each parcel independently) and used it to collect data in a low-income minority neighborhood in Dallas, TX. In addition, we collected data on the health status of individuals residing in this neighborhood. We then assessed the inter-rater reliability of the instrument and compared the costs and benefits of using data at this high spatial resolution. Our instrument provides a reliable and cost-effect method for collecting neighborhood observational data at high spatial resolution, which then allows researchers to explore the impact of varying geographic aggregations. Furthermore, these data facilitate a demonstration of the predictive accuracy of self-reported health status. We find that ordered logit models of health status using observational data at different spatial resolution produce different results. This implies a need to analyze the variation in correlative relationships at different geographic resolutions when there is no solid theoretical rational for choosing a particular resolution. We argue that neighborhood data at high spatial resolution greatly facilitates the evaluation of alternative geographic specifications in studies of neighborhood and health.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Conceived and designed the experiments: JCM JM MC TL. Performed the experiments: JM. Analyzed the data: TL MC. Wrote the paper: TL MC JM JCM.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0020225