Riti Shimkhada

The U.S. has recently made progress in collecting better data on race, ethnicity, and gender identity to ensure all communities are fairly represented in research and policy. However, new executive orders from President Trump in 2025 have halted many of these efforts, including stopping data collection on transgender people and removing key datasets from public websites. These actions threaten the availability of accurate, inclusive data that supports health, equity, and civil rights.

Authors explain what’s at stake and offer suggestions to encourage and protect robust data collection that represents everyone. While legal challenges are underway, state and local groups, along with researchers, are stepping up to protect and continue this vital work to reflect and protect data that reflects the nation's full diversity.
 

The U.S. Office of Management and Budget (OMB) categorizes Filipino Americans as Asian; however, many may not identify as such, opting instead for "other" or Pacific Islander (PI). This study examines the extent to which Filipino Americans select PI or "other" rather than Asian, using a large population-based survey of Californians.

Authors analyzed data from the 2019, 2020, and 2021 California Health Interview Survey (CHIS), the largest state health survey in the U.S. that includes write-in prompts for detailed race and ethnicity data. The focus was on participants who identified as Pacific Islanders and wrote in 'Filipino,' those who selected 'Asian' and specified 'Filipino,' and respondents who chose 'other' and wrote in 'Filipino.'

Findings: The analysis included 1,859 Filipino respondents, revealing that 8.8% identified as Pacific Islander, 85.2% as Asian, and 6.1% as "other." Those identifying as PI were more likely to also identify as Latino/Hispanic, be older, and possess U.S. citizenship compared to those identifying as Asian.

Disaggregating Filipino Americans from the broader Asian category in surveys is vital for accurately identifying the community's unique needs. Authors recommend incorporating open-ended write-in prompts in surveys that ask respondents to first identify their broader race category (e.g. Asian). These prompts help identify and reclassify Filipino respondents who may have identified as PI. Such prompts are also important for other racial/ethnic communities who may be uncertain about how to categorize themselves. Ongoing, dynamic community-driven research is essential for understanding identities and effectively categorizing Filipino Americans and other communities.
 

Achieving health equity necessitates high-quality data to address disparities that have remained stagnant or even worsened over time despite public health interventions. Data disaggregation, the breakdown of data into detailed subcategories, is crucial in health disparities research. It reveals and contextualizes hidden trends and patterns about marginalized populations and guides resource allocation and program development for specific needs in these populations.

Data disaggregation underpins data equity, which uses community engagement to democratize data and develop better solutions for communities. Years of research on disaggregation show that researchers must collaborate closely with communities for adequate representation. However, despite generally positive support for this approach in health disparities research, data disaggregation faces methodological and political challenges.

This review offers a framework for understanding data disaggregation in the context of data equity and highlights critical aspects of implementation, including challenges, opportunities, and recent policy and community-based efforts to address hurdles.
 

This research letter describes the increasing trend of almost-constant social media use among California adolescents and the association with serious psychological distress, focusing on the influence of familial and experiential factors.

Respondents were asked to report on typical daily use of social media. Family connection was measured through a series of questions, including how often the adolescent felt they were able to talk to family about their feelings, how often they felt family stood by them during difficult times, how often they felt safe and protected by the adult at home, and how often they had at least two nonparent adults taking a genuine interest in them. Adolescents responding “little to never” to any of these questions were assigned to a group characterized by little to no family connection. Adolescents responding having had at least one adverse childhood experience (ACE) were assigned “yes” to the ACEs variable. Researchers used 2019–2021 California Health Interview Survey (CHIS) data.

Findings: Almost-constant social media use for the youngest teens (aged 12-14 years) increased significantly between 2019 and 2021, whereas this increase was not noted for older teens (aged 15-17 years). Among male adolescents, almost-constant social media use increased significantly between 2019 and 2021 for both age groups. By 2021, there were no longer significant differences in almost-constant social media use according to age group.

The rates of almost-constant social media use were the highest for teens living in poverty, those who have experienced ACEs, those who reported little to no family connection, and those who reported serious psychological distress.

The researchers examine the association between social media use and psychological distress controlling for ACEs and the adolescent-reported level of family connection, both of which are significantly associated with psychological distress. Even when controlling for these and other demographic variables, almost-constant social media use remained significantly associated with psychological distress. 

This research is consistent with prior research that finds increasing trends in use of social media among the youngest teens and potential adverse mental health impacts from high or almost-constant social media use.