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Int. J. Environ. Res. Public Health 2016, 13(1), 2; doi:10.3390/ijerph13010002

Statistical Validation of a Web-Based GIS Application and Its Applicability to Cardiovascular-Related Studies

1
Research Centers in Minority Institutions Translational Research Network Data Coordinating Center, 1230 Raymond Road, Jackson, MS 39204, USA
2
Department of Epidemiology and Biostatistics, School of Public Health, Jackson State University, 350 W. Woodrow Wilson Drive Jackson Medical Mall, Suite 301, Jackson, MS 39213, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Mark Edberg, Barbara E. Hayes, Valerie Montgomery Rice and Paul B. Tchounwou
Received: 13 July 2015 / Revised: 30 September 2015 / Accepted: 14 October 2015 / Published: 22 December 2015
View Full-Text   |   Download PDF [800 KB, uploaded 22 December 2015]   |  

Abstract

Purpose: There is abundant evidence that neighborhood characteristics are significantly linked to the health of the inhabitants of a given space within a given time frame. This study is to statistically validate a web-based GIS application designed to support cardiovascular-related research developed by the NIH funded Research Centers in Minority Institutions (RCMI) Translational Research Network (RTRN) Data Coordinating Center (DCC) and discuss its applicability to cardiovascular studies. Methods: Geo-referencing, geocoding and geospatial analyses were conducted for 500 randomly selected home addresses in a U.S. southeastern Metropolitan area. The correlation coefficient, factor analysis and Cronbach’s alpha (α) were estimated to quantify measures of the internal consistency, reliability and construct/criterion/discriminant validity of the cardiovascular-related geospatial variables (walk score, number of hospitals, fast food restaurants, parks and sidewalks). Results: Cronbach’s α for CVD GEOSPATIAL variables was 95.5%, implying successful internal consistency. Walk scores were significantly correlated with number of hospitals (r = 0.715; p < 0.0001), fast food restaurants (r = 0.729; p < 0.0001), parks (r = 0.773; p < 0.0001) and sidewalks (r = 0.648; p < 0.0001) within a mile from homes. It was also significantly associated with diversity index (r = 0.138, p = 0.0023), median household incomes (r = −0.181; p < 0.0001), and owner occupied rates (r = −0.440; p < 0.0001). However, its non-significant correlation was found with median age, vulnerability, unemployment rate, labor force, and population growth rate. Conclusion: Our data demonstrates that geospatial data generated by the web-based application were internally consistent and demonstrated satisfactory validity. Therefore, the GIS application may be useful to apply to cardiovascular-related studies aimed to investigate potential impact of geospatial factors on diseases and/or the long-term effect of clinical trials. View Full-Text
Keywords: Statistical validation; web-based GIS application; walkability; accessibility to healthcare facilities; density of fast-food restaurant; social determinants of cardiovascular disease Statistical validation; web-based GIS application; walkability; accessibility to healthcare facilities; density of fast-food restaurant; social determinants of cardiovascular disease
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lee, J.E.; Sung, J.H.; Malouhi, M. Statistical Validation of a Web-Based GIS Application and Its Applicability to Cardiovascular-Related Studies. Int. J. Environ. Res. Public Health 2016, 13, 2.

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