Identifying Neighborhood Characteristics for Health Planning
Author Information
Author(s): Pedigo Ashley, Seaver William, Odoi Agricola
Primary Institution: The University of Tennessee, Knoxville
Hypothesis
The study aims to classify neighborhoods based on socioeconomic and demographic factors to better understand health needs related to stroke and myocardial infarction.
Conclusion
The study identifies four distinct neighborhood profiles that can guide health planners in addressing health disparities related to stroke and myocardial infarction.
Supporting Evidence
- Four distinct peer neighborhoods were identified based on socioeconomic and demographic characteristics.
- The highest risk of stroke and MI mortality was found in less affluent neighborhoods located in urban areas.
- The study utilized robust multivariate methods to classify neighborhoods effectively.
- Health planners can use the findings to allocate resources and design targeted health programs.
Takeaway
This study looked at different neighborhoods to see how their characteristics affect health, helping planners know where to focus their efforts.
Methodology
The study used robust principal component analysis, fuzzy cluster analysis, and discriminant analysis to classify neighborhoods based on socioeconomic and demographic characteristics.
Potential Biases
Potential biases may arise from using census data, which can have sampling and non-sampling errors.
Limitations
The study relied on 2000 census data, which may be outdated, and did not include individual-level risk factors.
Participant Demographics
The study focused on neighborhoods in East Tennessee, including diverse socioeconomic and demographic characteristics.
Statistical Information
P-Value
p=0.01
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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