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Chronic Disease and Risk Factor Prevalence in Multiracial Subgroups: California, 2014-2023.

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Summary
This summary is machine-generated.

Public health data often groups multiracial adults, hiding significant health disparities. Disaggregating data reveals wide health variations among multiracial subgroups, essential for targeted prevention strategies.

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Area of Science:

  • Public Health
  • Health Disparities
  • Sociology

Background:

  • Multiracial adults are a growing demographic in the U.S.
  • Current public health data often aggregates multiracial individuals or assigns them to single-race categories.
  • This aggregation obscures critical health variations among multiracial subgroups, hindering targeted prevention efforts.

Purpose of the Study:

  • To estimate the prevalence of 28 health indicators across racial and ethnic groups, with a specific focus on disaggregated multiracial subgroups.
  • To highlight the health variations within the multiracial population that are often masked by broader data aggregation.

Main Methods:

  • Analysis of 2014-2023 California Behavioral Risk Factor Surveillance System data (n=100,177).
  • Categorization of participants based on all self-identified races, with aggregation of subgroups with fewer than 50 individuals.
  • Standardization of prevalence by age and sex using 2020 California census data, with calculation of relative standard errors and use of survey-weighted methods for comparisons.

Main Results:

  • Multiracial subgroups exhibited the highest prevalence for 24 out of 28 health outcomes studied.
  • Specific subgroups, such as American Indian or Alaska Native-Black and Hispanic-Black-White adults, showed the highest prevalence of chronic conditions, poor general health, and disability.
  • Asian Multiracial subgroups generally had the lowest prevalence, although Asian-White adults did not consistently represent the healthiest group. Health differences across multiracial subgroups exceeded 20 percentage points for nearly half of the outcomes.

Conclusions:

  • Significant health variations exist among multiracial adults, which are masked by standard data aggregation practices.
  • Without disaggregated data, subgroups facing the highest health burdens may be overlooked.
  • Public health surveillance systems need enhanced capacity for collecting and reporting disaggregated race and ethnicity data to inform effective prevention strategies.