Application of spatial statistics and segmentation and market solutions to examine disparities in heart disease and selected risk factors in the District of Columbia

learning objectives:

Demonstrate spatial disparities in heart disease, mortality and hospital discharges, and selected risk factors.

Formulate evidence-based public health decision-making by quantifying spatial patterns of heart disease and selected risk factors.

Evaluate linkage between heart disease, hospital discharges and mortality, and selected risk factors.

objectives:

Use spatial statistics and segmentation and market solution data to evaluate spatial disparities in heart disease and selected risk factors in the District of Columbia. Spatial analysis of heart disease morbidity, mortality, hospital discharges and selected risk factors, and lifestage group characteristics can provide a cost-effective targeting of heart disease burden.     

methods:

   Heart disease morbidity, mortality and hospital discharges, and segmentation and market

   solutions data were subjected to spatial analysis in order to design cost-effective and targeted intervention strategies.  

results:

Preliminary results showed collocated high heart disease incidence, mortality, hospital discharges and selected risk factors are disproportionately distributed across District zip codes. This trend is also consistent with spatial patterns of modifiable risk factors (diabetes, obesity, and smoking) and non-modifiable risk factors (age, access to quality health care, and access to healthy foods).

conclusions:

Generally, high heart disease incidence, mortality and hospital discharges were collocated with high diabetes, overweight, obesity, smoking and the 65-plus age group. High heart disease morbidity, mortalities, hospital discharges and selected risk factors are associated with Young Achievers and Sustaining Families lifestage groups.