Using GIS and Secondary Data to Target Diabetes-Related Public Health Efforts. (May 2013)

• Record Type: Journal Article
• Authors: Curtis, Amy B.; Kothari, Catherine; Paul, Rajib; Connors, Elyse
• Is Part Of: Public health reports. Volume 128:Number 3(2013)
• Page Start: 212
• Page End: 220
• Publication Date: 2013-05
• Subjects: Public health -- United States -- Periodicals; 614.0973
• DOI: 10.1177/003335491312800311
• Languages: English
• ISSNs: 0033-3549

Abstract

Objectives: To efficiently help communities prevent and manage diabetes, health departments need to be able to target populations with high risk but low resources To aid in this process, we mapped county-level diabetes-related rates and resources/use using publicly available secondary data to identify Michigan counties with high diabetes prevalence and low or no medical and/or community resources. Methods: We collected county-level diabetes-related rates and resources from Web-based sources and mapped them using geographic information systems (GIS) software. Data included age-adjusted county diabetes rates, diabetes-related medical resource and resource use (i.e., the number of endocrinologists and percentage of Medicare patients with diabetes who received hemoglobin A1c testing in the past year), community resources (i.e., the number of certified diabetes self-management education and diabetes support groups), as well as population estimates and demographics (e.g., rural residence, education, poverty, and race/ethnicity). We created GIS maps highlighting areas that had higher-than-median rates of disease and lower-than-median resources. We also conducted linear, logistic, and Poisson regression analyses to confirm GIS findings. Results: There were clear regional trends in resource distribution across Michigan. The 15 counties in the Upper Peninsula were lacking in medical resources but higher in community resources compared with the 68 counties in the Lower Peninsula. There was little apparent association between need (diabetes prevalence) and diabetes-related resources/use. Specific counties with high diabetes prevalence and low resources were easily identified using GIS mapping. Conclusion: Using public data and mapping tools identified diabetes health-service shortage areas for targeted public health programming.