Evidence map›Paper›PMID 41405826›Full record

ArticleJournal of racial and ethnic health disparities2025

Chronic Disease and Aging-Related Risk Factors in Multiracial Subgroups: California, 2014-2023.

Tracy Lam-Hine, Michelle C Odden, Aliya Saperstein, Tainayah W Thomas, David H Rehkopf

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of racial and ethnic health disparities, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Tracy Lam-HineDepartment of Epidemiology and Population Health, Stanford University School of Medicine, 1701 Page Mill Road, Palo Alto, CA, 94304, USA. lamhine@stanford.edu.ORCID http://orcid.org/0000-0001-9040-2991
Michelle C OddenDepartment of Epidemiology and Population Health, Stanford University School of Medicine, 1701 Page Mill Road, Palo Alto, CA, 94304, USA.
Aliya SapersteinDepartment of Sociology, Stanford University, Stanford, CA, USA.
Tainayah W ThomasDepartment of Epidemiology and Population Health, Stanford University School of Medicine, 1701 Page Mill Road, Palo Alto, CA, 94304, USA.
David H RehkopfDepartment of Epidemiology and Population Health, Stanford University School of Medicine, 1701 Page Mill Road, Palo Alto, CA, 94304, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultiracial adults represent a growing U.S. population but are often grouped together or reassigned to single-race categories in public health research, when they are included in analysis at all. Aggregation obscures subgroup variation and limits opportunities for targeted prevention.

methodsWe analyzed 2014-2023 California Behavioral Risk Factor Surveillance System data (n = 100,177) to estimate prevalence of 28 chronic disease and aging-related risk factors across racial and ethnic groups, including disaggregated Multiracial subgroups. We classified participants based on all self-identified races, limited aggregatation to subgroups with N < 50, and standardized prevalence by age and sex using 2020 California population distributions. Survey-weighted methods produced prevalence estimates, relative standard errors, and subgroup comparisons.

resultsMultiracial subgroups had the highest prevalence for 24 of 28 outcomes. Prevalence differences across Multiracial subgroups also exceeded 20 percentage points for nearly half of all outcomes. American Indian or Alaska Native-Black and Hispanic-Black-White adults showed the greatest burden of chronic disease, poor general health, and disability in the sample. In contrast, while several Asian Multiracial subgroups (e.g., Asian-Black, Asian-Native Hawaiian or Pacific Islander) had the lowest prevalence across multiple domains, Asian-White adults were not consistently the healthiest Multiracial subgroup. DISCUSSION: Health outcomes for Multiracial adults do not follow a fixed hierarchy; subgroup position varies across domains. Wide variation is masked by common aggregation practices, leading to missed opportunities to identify and support high-burden subgroups. Surveillance systems should expand capacity to collect and report disaggregated race and ethnicity data to strengthen prevention efforts.

Indexed as

AgingChronic diseaseDisaggregationEthnicityMultiracialPreventionRace

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.