{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T04:49:04Z","timestamp":1782276544629,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Food access is a major key component in food security, as it is every individual\u2019s right to proper access to a nutritious and affordable food supply. Low access to healthy food sources influences people\u2019s diet and activity habits. Guilford County in North Carolina has a high ranking in low food security and a high rate of health issues such as high blood pressure, high cholesterol, and obesity. Therefore, the primary objective of this study was to investigate the geospatial correlation between health issues and food access areas. The secondary objective was to quantitatively compare food access areas and heath issues\u2019 descriptive statistics. The tertiary objective was to compare several machine learning techniques and find the best model that fit health issues against various food access variables with the highest performance accuracy. In this study, we adopted a food-access perspective to show that communities that have residents who have equitable access to healthy food options are typically less vulnerable to health-related disasters. We propose a methodology to help policymakers lower the number of health issues in Guilford County by analyzing such issues via correlation with respect to food access. Specifically, we conducted a geographic information system mapping methodology to examine how access to healthy food options influenced health and mortality outcomes in one of the largest counties in the state of North Carolina. We created geospatial maps representing food deserts\u2014areas with scarce access to nutritious food; food swamps\u2014areas with more availability of unhealthy food options compared to healthy food options; and food oases\u2014areas with a relatively higher availability of healthy food options than unhealthy options. Our results presented a positive correlation coefficient of R2 = 0.819 among obesity and the independent variables of transportation access, and population. The correlation coefficient matrix analysis helped to identify a strong negative correlation between obesity and median income. Overall, this study offers valuable insights that can help health authorities develop preemptive preparedness for healthcare disasters.<\/jats:p>","DOI":"10.3390\/ijgi10110745","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T17:59:38Z","timestamp":1635962378000},"page":"745","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8728-5114","authenticated-orcid":false,"given":"Abrar","family":"Almalki","sequence":"first","affiliation":[{"name":"AI&VI Lab from NCAT and Visualizations and Computing Advanced Research Center (ViCAR) North Carolina Agriculture and Technical State University, 1601 East Market Street, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Balakrishna","family":"Gokaraju","sequence":"additional","affiliation":[{"name":"AI&VI Lab from NCAT and Visualizations and Computing Advanced Research Center (ViCAR) North Carolina Agriculture and Technical State University, 1601 East Market Street, Greensboro, NC 27411, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikhil","family":"Mehta","sequence":"additional","affiliation":[{"name":"Department of Information Systems and Supply Chain Management, University of North Carolina at Greensboro, Greensboro, NC 27402, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3393-0488","authenticated-orcid":false,"given":"Daniel Adrian","family":"Doss","sequence":"additional","affiliation":[{"name":"Interim Chair of Johnston Division of Business and Associate Professor of Cybersecurity, University of Tennessee, Pulaski, TN 37478, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"ref_1","unstructured":"(2021, April 15). 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