A pilot study using geospatial analysis to identify hot-spot of populations utilizing services at university based counseling centers

Patel, Rahul; Walker, Tanesha L.; Weber, Zachary; Kelley, Sarah D.; Hansen, Ryan W

doi:10.1080/07448481.2020.1798970

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…The age-adjusted and fully adjusted mortality rates were used as input for cluster analysis with optimized hotspot analysis (ArcGIS Desktop, Release 10; Environmental Systems Research Institute, Redlands, CA); the distance band used for analysis was identified based on incremental spatial autocorrelation. 29,30 We considered clusters (not individual counties) statistically significant at P < .05 and a Z score of 1.96 (95% confidence level). An important note about clustering is that it is "high-high" clustering.…”

Section: Discussionmentioning

confidence: 99%

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County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care

2021

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BACKGROUND AND AIMS: Data have demonstrated state-wide variability in mortality rates from liver disease (cirrhosis þ hepatocellular carcinoma), but data are lacking at the local level (eg, county) to identify factors associated with variability in liver disease-related mortality and hotspots of liver disease mortality. METHODS: We used Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research data from 2009 to 2018 to calculate county-level, ageadjusted liver disease-related death rates. We fit multivariable linear regression models to adjust for county-level covariates related to demographics (ie, race and ethnicity), medical comorbidities (eg, obesity), access to care (eg, uninsured rate), and geographic (eg, distance to closest liver transplant center) variables. We used optimized hotspot analysis to identify clusters of liver disease mortality hotspots based on the final multivariable models. RESULTS: In multivariable models, 61% of the variability in among-county mortality was explained by county-level race/ethnicity, poverty, uninsured rates, distance to the closest transplant center, and local rates of obesity, diabetes, and alcohol use. Despite adjustment, significant within-state variability in county-level mortality rates was found. Of counties in the top fifth percentile (ie, highest mortality) of fully adjusted mortality, 60% were located in 3 states: Oklahoma, Texas, and New Mexico. Adjusted mortality rates were highly spatially correlated, representing 5 clusters: South Florida; Appalachia and the eastern part of the Midwest; Texas and Oklahoma; New Mexico, Arizona, California, and southern Oregon; and parts of Washington and Montana. CONCLUSIONS: Our data demonstrate significant intrastate differences in liver disease-related mortality, with more than 60% of the variability explained by patient demographics, clinical risk factors for liver disease, and access to specialty liver care.

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Section: Discussionmentioning

confidence: 99%

“…As a result, an individual county can be considered part of a hotspot based on its surrounding counties, even if it is not in the top 5% for mortality. 29,30 WHAT YOU NEED TO KNOW…”

Section: Discussionmentioning

confidence: 99%

County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care

2021

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“…This clustering technique is an extension of the Getis-Ord Gi* hotspot analysis, which finds the spatial clusters of statistically significant higher values (hotspots) or lower values (coldspots) as compared to the surrounding locations in an area using the parameters derived from characteristics of the input data [52]. Many researchers have increasingly used this statistical method in many fields [53][54][55][56][57][58].…”

Section: Potentiometric Surface Mapsmentioning

confidence: 99%

Assessing Impacts of Land Subsidence in Victoria County, Texas, Using Geospatial Analysis

Younas

Khan

Qasim

et al. 2022

Land

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Land subsidence is an ongoing problem negatively affecting Victoria County along the Gulf Coast. Groundwater withdrawal and hydrocarbon extraction in the County are some of the known factors behind this geological hazard. In this study, we have used geospatial analysis and a conceptual model to evaluate land subsidence. A significant decline in the groundwater level in this area was noted from 2006 to 2016. The decline in the water level correlates with the major drought events along the Gulf Coast reported in earlier studies. These results are further corroborated by the emerging hotspot analysis performed on the groundwater data. This analysis divides the study area into intensifying, sporadic, and persistent hotspots in the northwest region and intensifying, persistent coldspots in the southeast region of Victoria County. Hydrocarbon production data show high oil and gas extraction from 2017 to 2021. There are a higher number of hydrocarbon production wells in the central and southern regions of the County than elsewhere. The conceptual models relate these events and suggest the existence of subsidence in the County, through which the water and hydrocarbon reservoirs in the study area may lose their reservoir characteristics due to sediment compaction.

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A pilot study using geospatial analysis to identify hot-spot of populations utilizing services at university based counseling centers

Cited by 2 publications

References 7 publications

County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care

County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care

Assessing Impacts of Land Subsidence in Victoria County, Texas, Using Geospatial Analysis

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