干旱区生态环境知识资源中心(Arid): Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities

Arid

DOI	10.3390/ijgi10110745
	Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities
	Almalki, Abrar; Gokaraju, Balakrishna; Mehta, Nikhil; Doss, Daniel Adrian
通讯作者	Almalki, A (corresponding author), North Carolina Agr & Tech State Univ, AI&VI Lab NCAT, 1601 East Market St, Greensboro, NC 27411 USA. ; Almalki, A (corresponding author), North Carolina Agr & Tech State Univ, Visualizat & Comp Adv Res Ctr ViCAR, 1601 East Market St, Greensboro, NC 27411 USA.
来源期刊	ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
EISSN	2220-9964
出版年	2021
卷号	10 期号:11
英文摘要	Food access is a major key component in food security, as it is every individual's right to proper access to a nutritious and affordable food supply. Low access to healthy food sources influences people's 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' 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-areas with scarce access to nutritious food; food swamps-areas with more availability of unhealthy food options compared to healthy food options; and food oases-areas with a relatively higher availability of healthy food options than unhealthy options. Our results presented a positive correlation coefficient of R-2 = 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.
英文关键词	disaster preparedness smart cities sustainable cities food desert regression analysis
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000724510800001
WOS关键词	ENVIRONMENT ; DESERTS ; MODEL ; TIME
WOS类目	Computer Science, Information Systems ; Geography, Physical ; Remote Sensing
WOS研究方向	Computer Science ; Physical Geography ; Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/373760
作者单位	[Almalki, Abrar; Gokaraju, Balakrishna] North Carolina Agr & Tech State Univ, AI&VI Lab NCAT, 1601 East Market St, Greensboro, NC 27411 USA; [Almalki, Abrar; Gokaraju, Balakrishna] North Carolina Agr & Tech State Univ, Visualizat & Comp Adv Res Ctr ViCAR, 1601 East Market St, Greensboro, NC 27411 USA; [Mehta, Nikhil] Univ N Carolina, Dept Informat Syst & Supply Chain Management, Greensboro, NC 27402 USA; [Doss, Daniel Adrian] Univ Tennessee, Johnston Div Business, Pulaski, TN 37478 USA; [Doss, Daniel Adrian] Univ Tennessee, Cybersecur, Pulaski, TN 37478 USA
推荐引用方式 GB/T 7714	Almalki, Abrar,Gokaraju, Balakrishna,Mehta, Nikhil,et al. Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities[J],2021,10(11).
APA	Almalki, Abrar,Gokaraju, Balakrishna,Mehta, Nikhil,&Doss, Daniel Adrian.(2021).Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,10(11).
MLA	Almalki, Abrar,et al."Geospatial and Machine Learning Regression Techniques for Analyzing Food Access Impact on Health Issues in Sustainable Communities".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 10.11(2021).