scholarly journals Geospatial analysis of neighborhood deprivation index (NDI) for the United States by county

2020 ◽  
Vol 16 (1) ◽  
pp. 101-112 ◽  
Author(s):  
Marcus R. Andrews ◽  
Kosuke Tamura ◽  
Sophie E. Claudel ◽  
Samantha Xu ◽  
Joniqua N. Ceasar ◽  
...  
2020 ◽  
Vol 13 (12) ◽  
Author(s):  
Shivani A. Patel ◽  
Maya Krasnow ◽  
Kaitlyn Long ◽  
Theresa Shirey ◽  
Neal Dickert ◽  
...  

Background: Longstanding racial disparities in heart failure (HF) outcomes exist in the United States, in part, due to social determinants of health. We examined whether neighborhood environment modifies the disparity in 30-day HF readmissions and mortality between Black and White patients in the Southeastern United States. Methods: We created a geocoded retrospective cohort of patients hospitalized for acute HF within Emory Healthcare from 2010 to 2018. Quartiles of the Social Deprivation Index characterized neighborhood deprivation at the census tract level. We estimated the relative risk of 30-day readmission and 30-day mortality following an index hospitalization for acute HF. Excess readmissions and mortality were estimated as the absolute risk difference between Black and White patients within each Social Deprivation Index quartile, adjusted for geographic clustering, demographic, clinical, and hospital characteristics. Results: The cohort included 30 630 patients, mean age 66 years, 48% female, 53% Black. Compared with White patients, Black patients were more likely to reside in deprived census tracts and have higher comorbidity scores. From 2010 to 2018, 29.4% of Black and 23.0% of White patients experienced either a 30-day HF readmission or 30-day death ( P <0.001). Excess in composite 30-day HF readmissions and mortality for Black patients ranged from 3.9% (95% CI, 1.5%–6.3%; P =0.0002) to 6.8% (95% CI, 4.1%–9.5%; P <0.0001) across Social Deprivation Index quartiles. Accounting for traditional risk factors did not eliminate the Black excess in combined 30-day HF readmissions or mortality in any of the neighborhood quartiles. Conclusions: Excess 30-day HF readmissions and mortality are present among Black patients in every neighborhood strata and increase with progressive neighborhood socioeconomic deprivation.


2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S197-S197
Author(s):  
Pratik Panchal ◽  
Stacy Kahn ◽  
Caroline Zellmer ◽  
Zain Kassam ◽  
Majdi Osman ◽  
...  

2021 ◽  
Vol 116 (3) ◽  
pp. e47
Author(s):  
Nivedita R. Potapragada ◽  
Benjamin J. Peipert ◽  
Paul M. Lantos ◽  
Benjamin S. Harris ◽  
Kara N. Goldman

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243028
Author(s):  
Madhav K. C. ◽  
Evrim Oral ◽  
Susanne Straif-Bourgeois ◽  
Ariane L. Rung ◽  
Edward S. Peters

Background Louisiana in the summer of 2020 had the highest per capita case count for COVID-19 in the United States and COVID-19 deaths disproportionately affects the African American population. Neighborhood deprivation has been observed to be associated with poorer health outcomes. The purpose of this study was to examine the relationship between neighborhood deprivation and COVID-19 in Louisiana. Methods The Area Deprivation Index (ADI) was calculated and used to classify neighborhood deprivation at the census tract level. A total of 17 US census variables were used to calculate the ADI for each of the 1148 census tracts in Louisiana. The data were extracted from the American Community Survey (ACS) 2018. The neighborhoods were categorized into quintiles as well as low and high deprivation. The publicly available COVID-19 cumulative case counts by census tract were obtained from the Louisiana Department of Health website on July 31, 2020. Descriptive and Poisson regression analyses were performed. Results Neighborhoods in Louisiana were substantially different with respect to deprivation. The ADI ranged from 136.00 for the most deprived neighborhood and –33.87 in the least deprived neighborhood. We observed that individuals residing in the most deprived neighborhoods had almost a 40% higher risk of COVID-19 compared to those residing in the least deprived neighborhoods. Conclusion While the majority of previous studies were focused on very limited socio-environmental factors such as crowding and income, this study used a composite area-based deprivation index to examine the role of neighborhood environment on COVID-19. We observed a positive relationship between neighborhood deprivation and COVID-19 risk in Louisiana. The study findings can be utilized to promote public health preventions measures besides social distancing, wearing a mask while in public and frequent handwashing in vulnerable neighborhoods with greater deprivation.


2019 ◽  
Vol 6 (5) ◽  
pp. 275-281
Author(s):  
Paige E. Nichols ◽  
Taylor P. Kohn ◽  
Nora M. Haney ◽  
Stephen A. Boorjian ◽  
Matthew T. Gettman ◽  
...  

Stroke ◽  
2019 ◽  
Vol 50 (Suppl_1) ◽  
Author(s):  
Suzanne E Judd ◽  
George Howard ◽  
Virginia J Howard ◽  
Elsayed Z Soliman ◽  
Philippa J Clarke ◽  
...  

CHEST Journal ◽  
2020 ◽  
Author(s):  
Liora Sahar ◽  
Vanhvilai L. Douangchai Wills ◽  
Ka Kit Liu ◽  
Ella A. Kazerooni ◽  
Debra S. Dyer ◽  
...  

Author(s):  
Ahsan Ali ◽  
Randall Edgell

Introduction : Background: Several accrediting bodies certify the level of stroke care hospitals provide. The Joint Commission on Hospital Accreditation (JC) is the largest accrediting body in the United States. There is no open source Geographic Information Systems (GIS) dataset showing the distribution of JC accredited centers by ZIP code. Objective: to create a stroke center accessibility and stroke center desert system using geospatial analysis and machine learning which provides real‐time assessment of stroke center availability, distribution and access to care. Methods : Geospatial data layers of JC accredited stroke centers were compiled using data sources including U.S. Census Bureau and CDC. Map layers corresponding to the levels of JC accredited stroke hospitals geolocated using ZIP code were created as follows: 1) Acute Stroke Ready 2) Primary 3) Thrombectomy Capable 4) Comprehensive Stroke Center. A GIS dataset displaying stroke mortality by region was obtained from the ArcGIS Living Atlas. Stroke center deserts are analyzed using a 4.5 hour drive map along with population and diversity. Machine learning models were implemented to estimate stroke mortality as a function of distance to care centers and capability levels of the stroke centers. Results : Stroke centers are highly concentrated within large urban centers. There are geographic regions that have poor access to stroke centers. Such regions include the Gulf Coast States of Louisiana, Mississippi, and Alabama that have large areas with poor stroke center access while having some of the highest stroke mortality in the country. (Figure 1 ‐ Stroke Center Distribution in the United States) Dot Symbols: Blue = Acute Stroke Ready; Green = Primary; Yellow = Thrombectomy Capable; Red = Comprehensive Raster Data: Stroke Mortality by ZIP Code; White to Purple Scale with Purple = Highest Mortality Conclusions : There are regional variations in stroke center availability. There are certain regions with high stroke mortality with very little stroke center access. Geospatial AI tools can be utilized to improve stroke systems of care.


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