Geographic Access to Diabetes Prevention Program Sites: New York State Department of Health

Ruberto, Rachael; Brissette, Ian

doi:10.5888/pcd11.130400

Cited by 3 publications

(4 citation statements)

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“…The resulting maps enabled us to communicate effectively with decision makers and engage communities. GIS has helped to visualize community assets, including certified mammography facilities, locations offering lifestyle change programs (26,27), and retail outlets offering healthy food (28), and to identify gaps and plan local action. In program monitoring, local partners provide information about community locations where evidence-based interventions are implemented (26,28).…”

Section: Introductionmentioning

confidence: 99%

Application of Geographic Information Systems to Address Chronic Disease Priorities: Experiences in State and Local Health Departments

et al. 2019

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Section: Introductionmentioning

confidence: 99%

Application of Geographic Information Systems to Address Chronic Disease Priorities: Experiences in State and Local Health Departments

et al. 2019

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“…This approach capitalizes on geographic location as a principal variable, 18 which reflects variation in a wide range of place-based characteristics associated with health. 19,20 This information may include but is not limited to age, 30 education, 43 income, 29,43 racial segregation, 14,44 employment, 45 household composition, 14,43 healthcare access, 14,31 comorbidities, 46,47 availability of recreational facilities, 19,29 and quality of food sources. 15,19 Geographic location reflects multivariate effects of unequal distribution of resource and its influences on physical and social environments.…”

Section: Discussionmentioning

confidence: 99%

“…26 These areas can be characterized using geo-referenced databases to identify environmental, social, economic, and healthcare resources shared by residents. 26–29 The spatial patterns of Type 2 diabetes have been linked to community resources for care or prevention, 30,31,17 and have helped to inform the design of interventions to reduce diabetes-related health disparities. 26,32,33 …”

Section: Introductionmentioning

confidence: 99%

Geographic Information Systems to Assess External Validity in Randomized Trials

Savoca

Ludwig

Jones

et al. 2017

American Journal of Preventive Medicine

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Introduction To support claims that RCTs can reduce health disparities (i.e., are translational), it is imperative that methodologies exist to evaluate the tenability of external validity in RCTs when probabilistic sampling of participants is not employed. Typically, attempts at establishing post hoc external validity are limited to a few comparisons across convenience variables, which must be available in both sample and population. A Type 2 diabetes RCT was used as an example of a method that uses GIS to assess external validity in the absence of a priori probabilistic community-wide diabetes risk sampling strategy. Methods GIS and 2009–2013 county death certificate records and 2013–2014 electronic medical records were used to identify community-wide diabetes prevalence. Color-coded diabetes density maps provided visual representation of these densities. Chi-square goodness of fit statistic/analysis tested the degree to which distribution of RCT participants varied across density classes compared to what would be expected given simple random sampling of the county population. Analyses were conducted in 2016. Results Diabetes prevalence areas as represented by death certificate and electronic medical records were distributed similarly. The simple random sample model was not a good fit for death certificate record (chi-square, 17.63; p=0.0001) and electronic medical record data (chi-square, 28.92; p<0.0001). Generally, RCT participants were oversampled in high–diabetes density areas. Conclusions Location is a highly reliable “principal variable” associated with health disparities. It serves as a directly measurable proxy for high-risk underserved communities, thus offering an effective and practical approach for examining external validity of RCTs.

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“…[19][20][21][22] Recent efforts are underway to identify health-care and income resources that are geographically separated from populations with the highest need and worst outcomes. [37][38][39][40] Improving geographic access to social service agencies that provide income support and job training could improve utilization by the populations most in need of these services. It has been previously shown that children living in poverty, but utilizing TANF, are three times more likely to have health insurance compared to children living in poverty without TANF.…”

Section: Discussionmentioning

confidence: 99%

Geographic Disparities in Access to Agencies Providing Income-Related Social Services

2015

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Geographic location is an important factor in understanding disparities in access to health-care and social services. The objective of this cross-sectional study is to evaluate disparities in the geographic distribution of income-related social service agencies relative to populations in need within Boston. Agency locations were obtained from a comprehensive database of social services in Boston. Geographic information systems mapped the spatial relationship of the agencies to the population using point density estimation and was compared to census population data. A multivariate logistic regression was conducted to evaluate factors associated with categories of income-related agency density. Median agency density within census block groups ranged from 0 to 8 agencies per square mile per 100 population below the federal poverty level (FPL). Thirty percent (n = 31,810) of persons living below the FPL have no access to income-related social services within 0.5 miles, and 77 % of persons living below FPL (n = 83,022) have access to 2 or fewer agencies. 27.0 % of Blacks, 30.1 % of Hispanics, and 41.0 % of non-Hispanic Whites with incomes below FPL have zero access. In conclusion, some neighborhoods in Boston with a high concentration of low-income populations have limited access to income-related social service agencies.

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Geographic Access to Diabetes Prevention Program Sites: New York State Department of Health

Cited by 3 publications

References 0 publications

Application of Geographic Information Systems to Address Chronic Disease Priorities: Experiences in State and Local Health Departments

Application of Geographic Information Systems to Address Chronic Disease Priorities: Experiences in State and Local Health Departments

Geographic Information Systems to Assess External Validity in Randomized Trials

Geographic Disparities in Access to Agencies Providing Income-Related Social Services

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