Poorly Controlled Diabetes in New York City: Mapping High-Density Neighborhoods
To identify geographic areas in New York City (NYC) for implementing programming focused on reducing the burden attributed to poor glycemic control and improving the health of New Yorkers.Design:
We geocoded addresses of NYC residents in the NYC Hemoglobin A1c (HbA1C) Registry with high (>9%) HbA1c test values from 2011 to 2013 on an NYC base map. The ArcGIS point density spatial analysis tool was applied to create a map of NYC residents with diabetes in poor glycemic control.Setting:
The setting for HbA1c testing was medical facilities within NYC.Participants:
The study population included NYC residents (excluding undomiciled persons and addresses corresponding to prisons, hospitals, or nursing homes) 18 years or older who underwent HbA1c testing from 2011 to 2013.Main Outcome Measures:
A map depicting point density of NYC residents with poor glycemic control was developed each year from 2011 to 2013 (2011: n = 70 359; 2012: n = 75 643; 2013: n = 78 694).Results:
Particularly, high densities of persons in poor glycemic control were identified in Flatbush, East Harlem, Washington Heights/Inwood, and the South Bronx. The 2 highest-density gradients (out of 9) covered approximately 1.7% of the total habitable area in NYC, while accounting for more than 1 in 10 (10.5%) persons in poor glycemic control. The 3 highest-density gradients covered 4.1% of NYC's habitable area and accounted for more than 1 in 5 (21.9%) persons in poor glycemic control.Conclusion:
The point density analysis highlighted several defined geographic areas representing a meaningful proportion of the population in poor glycemic control. This analysis could be used to raise community awareness and guide potential programming focused on reducing the burden of poor glycemic control such as the placement of diabetes self-management education classes, community health workers, and farmers' markets. Given the geographic breadth of NYC and limited resources, focused efforts on these defined areas would reach a sizeable number of the at-risk population.