Online Program

Innovative technology for the planning and evaluation of local community health: GIS modeling of diabetes and predictor variables

Wednesday, November 6, 2013 : 8:30 a.m. - 8:50 a.m.

Anthony Olivieri, MURP, Food for Health, the Environment, Economy and Democracy (FHEED,LLC), Fort Lauderdale, FL
Teina Phillips, MPA, TOUCH Program Director, Broward Regional Health Planning Council, Hollywood, FL

T. Lucas Hollar, PhD, Master of Public Health Program, College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL
Nicole Cook, PhD, MPA, Master of Public Health Program, College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL
Michael Delucca, MHM, BRHPC, Broward Regional Hospital Planning Council, Hollywood, FL
Efforts to innovatively improve and evaluate health conditions of communities, like those of the Centers for Disease Control and Prevention (CDC) Community Transformation Grants (CTG), face the burden of identifying substantive confluences of health inequities and chronic disease across space. Broward Regional Health Planning Council's “Transforming Our Community's Health” (TOUCH), made possible with funding from CDC CTG, employs GIS methods to locate areas of significant interaction between Long Term Diabetes rates (LTD) and actionable predictor variables for intervention and evaluation activities aimed at increasing healthy food consumption. To identify areas of need, monitor efforts to ameliorate disparities, and evaluate interventions, TOUCH correlated ZIP Code hospital discharge LTD with rates of African Americans (AA), Earned Income Tax Credit returns (EITC), and the proportion of unhealthy food retail to healthy retail square footage per population (FOOD). TOUCH analyzed all variables with GIS for autocorrelation (hot spots/cold spots) and employed spatial regression models to test the relationship between LTD and predictor variables. LTD positively correlates with rates of AA (+0.80), EITC (+0.82), and FOOD (+0.54). Controlling for autocorrelation, one regression model (R^2 =77) finds a significant association between LTD with AA (p<0.00), Unhealthy Food Retail (p<.0.00), and Healthy Food Retail (p<0.04). Based on the spatial distribution of LTD and its social and environmental determinants across 439 square miles, TOUCH established strategies for increasing healthy food consumption in targeted communities. These activities demonstrate how policymakers, researchers, and the public may employ GIS as an innovative technology to develop geo-strategically informed intervention and evaluation plans.

Learning Areas:

Assessment of individual and community needs for health education
Planning of health education strategies, interventions, and programs
Public health or related research

Learning Objectives:
Discuss how to use GIS as a community health modeling and planning tool. Explain the difference between data correlation and spatial association. Assess the strengths and limitations of the presented GIS techniques for improving and evaluating the health conditions of communities.

Keyword(s): Geographic Information Systems, Food and Nutrition

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have a Master's degree in Urban and Regional Planning with a specialization in community food systems planning and GIS. I have a contract with the Broward Regional Health Planning Council to conduct GIS health disparities research. This work is funded and evaluated by the CDC's CTG grant program.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.