Modeling Cardiovascular Disease Prevalence in the US
Author Information
Author(s): Peter Congdon
Primary Institution: Queen Mary University of London
Hypothesis
Geographic and demographic factors significantly influence the prevalence of cardiovascular disease.
Conclusion
The study shows that geographic variations in cardiovascular disease prevalence are influenced by both demographic composition and distinct geographic effects.
Supporting Evidence
- Geographic effects improve the statistical fit of the model.
- Prevalence estimates vary significantly by age, sex, ethnicity, and education.
- Distinct geographic effects are necessary for accurate small area prevalence estimation.
Takeaway
This study looks at how where you live and who you are can affect your chances of having heart problems. It shows that both your neighborhood and your background matter.
Methodology
A multilevel prevalence model was used, incorporating survey data on patient risk factors and geographic influences.
Potential Biases
Potential biases may arise from the reliance on survey data and the geographic context of respondents.
Limitations
The model may not account for all unobserved geographic influences and relies on available demographic data.
Participant Demographics
The study included diverse demographic groups based on age, sex, ethnicity, and education level.
Digital Object Identifier (DOI)
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