Understanding Health Profiles Using World Health Survey Data
Author Information
Author(s): Andreotti Alessandra, Minicuci Nadia, Kowal Paul, Chatterji Somnath
Primary Institution: CNR- Institute of Neuroscience, Padova Section, Padova, Italy
Hypothesis
The study aims to apply Grade of Membership (GoM) modelling to summarize health information from the World Health Survey into understandable health profiles.
Conclusion
The GoM analysis provided a robust method to identify health profiles and characteristics of healthy and non-healthy individuals across different economic categories.
Supporting Evidence
- The GoM model identified three health profiles: Robust, Intermediate, and Frail.
- Respondents in higher income categories reported better health status compared to those in lower income categories.
- More than 85% of respondents reported no diagnosed health conditions.
Takeaway
This study helps us understand different health profiles of people in various countries, showing who is healthy and who might need more help.
Methodology
The study used Grade of Membership (GoM) modelling to analyze health data from the World Health Survey conducted in 70 countries.
Potential Biases
Potential reporting bias across countries and economic categories may affect the results.
Limitations
The study did not include Turkey due to missing marital status data, and the results may not be generalizable to all populations.
Participant Demographics
The dataset included respondents aged 18 and older from 70 countries, categorized by World Bank economic classifications.
Statistical Information
P-Value
p<0.0001
Statistical Significance
p<0.0001
Digital Object Identifier (DOI)
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