Mapping Ethnic Enclaves for Health Disparities Research: A Hybrid Clustering Approach

Area of Science:

• Social epidemiology
• Geographic information systems (GIS)
• Health disparities research

Background:

• Ethnic enclaves are area-level social determinants of health, influencing ethnic health disparities.
• Current methods often map enclaves based solely on population density, neglecting spatial clustering and cultural resources.
• This limitation impacts the accurate assessment of health disparities within ethnic communities.

Purpose of the Study:

• To develop and assess a hybrid clustering enclave model (HCEM) for mapping ethnic enclaves.
• To incorporate both ethnic population concentrations and cultural resources in enclave mapping.
• To compare HCEM-derived enclaves with traditional population-threshold methods for Chinese, Japanese, and Korean populations in Los Angeles County.

Main Methods:

• Developed a hybrid clustering enclave model (HCEM) integrating population and cultural resource data.
• Applied HCEM to identify Chinese, Japanese, and Korean enclaves in Los Angeles County.
• Compared enclave maps generated by HCEM against those derived from census tract population thresholds.

Main Results:

• Different mapping approaches yielded varying sizes of ethnic enclaves and associated health disparities.
• The HCEM identified distinct enclave areas compared to population-threshold methods.
• The choice of mapping method influenced the magnitude of observed health disparities for specific Asian ethnic groups.

Conclusions:

• The method used to map ethnic enclaves significantly impacts findings on health disparities.
• Aligning enclave measurement with conceptualization and health mechanisms is crucial for accurate research.
• The HCEM provides a more multidimensional approach to mapping enclaves, aiding diverse research questions on place and health.