The study, led by David A. Stupplebeen of the University of Hawaiʻi at Mānoa, with Candice D. Donaldson and Tam D. Vuong of the California Department of Public Health and UC Davis Comprehensive Cancer Center, drew on pooled data from the 2022 and 2023 cycles of the Online California Adult Tobacco Survey. That survey is designed to be representative of California adults, and the researchers restricted their analysis to people between the ages of 18 and 64, yielding a weighted analytic sample of 10,332 respondents. Because the data were weighted, the findings are intended to reflect the broader adult population of the state rather than just the people who happened to answer the questionnaire.

What sets this investigation apart is its measurement strategy. Rather than simply recording whether respondents belonged to a racial or ethnic minority group or identified as sexual or gender minorities, the researchers measured discrimination directly using the Everyday Discrimination Scale, a widely used instrument that asks about routine experiences of being treated with less courtesy or respect, being insulted, or being perceived as less capable. Respondents were then classified into categories based on the type of discrimination they attributed their experiences to: none at all, discrimination related to something other than race or sexual orientation, racial or ethnic discrimination only, sexual orientation discrimination only, or the joint experience of both racial-ethnic and sexual orientation discrimination.

The researchers also captured a dimension that is often overlooked in health disparities research: frequency. Experiencing discrimination once is not the same as living with it as a chronic, repeating feature of daily life. By standardizing discrimination scores and modeling both the type and the reported frequency of discriminatory experiences, the team could ask whether the chronicity of mistreatment mattered independently of its kind. The answer, according to their statistical models, was yes, and the patterns were strikingly different across categories.

The core results come from logistic regression models that adjusted for a range of demographic and socioeconomic factors, allowing the researchers to isolate the association between discrimination and tobacco use from confounders such as age, income, education, and other characteristics. Compared with adults who reported no discrimination, those who experienced discrimination tied to other reasons had 32 percent higher odds of current cigarette use, with an adjusted odds ratio of 1.32 and a 95 percent confidence interval of 1.11 to 1.57. Those who experienced sexual orientation discrimination alone faced roughly double the odds of smoking, with an adjusted odds ratio of 2.05 and a confidence interval of 1.47 to 2.85, the single largest effect observed in the study.

Perhaps the most counterintuitive finding involved people who reported experiencing both racial-ethnic and sexual orientation discrimination. Their adjusted odds of smoking were elevated, at 1.26 with a confidence interval of 1.10 to 1.45, but the effect was smaller than for sexual orientation discrimination alone. The same held true for vaping: joint discrimination was associated with 31 percent higher odds of current vaping, while racial-ethnic discrimination alone carried 53 percent higher odds and other discrimination 37 percent higher odds. The researchers interpret this not as evidence that intersectional discrimination is somehow protective, but as a reminder that the relationship between layered prejudice and health behavior is not a simple additive one, where each additional form of discrimination mechanically stacks risk on top of risk.

Across both outcomes, the direction of association was consistent: more discrimination, and more frequent discrimination, went together with higher odds of tobacco product use. For vaping, the adjusted odds ratios were 1.37 for other discrimination, 1.53 for racial-ethnic discrimination only, and 1.31 for joint discrimination, all with confidence intervals that excluded the null value of 1.0. The consistency of the positive association across two distinct tobacco products, one a combustible product with a century of epidemiological baggage and the other a relatively recent phenomenon, suggests that the underlying mechanism is not specific to any single delivery device but may relate to how people cope with chronic social stress.

The biological plausibility for such a link comes from a substantial body of research on minority stress and allostatic load. Chronic exposure to discriminatory treatment is thought to activate the body’s stress response systems repeatedly, elevating cortisol and sympathetic nervous system activity over time. Tobacco use, in this framework, can function as both a pharmacological coping mechanism, delivering nicotine that temporarily blunts negative affect, and a behavior embedded in social environments where stress and marketing pressure converge. The California findings cannot prove causation, since the data are cross-sectional and discrimination and tobacco use were measured at the same time, but they add to a growing pattern of evidence that perceived discrimination behaves like a modifiable risk factor for one of the world’s leading causes of preventable death.

The methodological implications may be as important as the substantive ones. Public health surveillance has long relied on demographic categories, race, ethnicity, sexual orientation, gender identity, to identify populations at elevated risk. Those categories are useful but blunt, and they describe characteristics that are immutable. By measuring the actual experience of discrimination, including its type and its frequency, the study demonstrates a way to identify risk that tracks something potentially changeable. If discrimination contributes to tobacco use, then reducing discrimination, through policy, enforcement, or community intervention, becomes a legitimate tobacco control strategy, not merely a matter of social justice pursued for its own sake.

The authors are careful about the limits of their work. The study is observational, the discrimination measures rely on self-report, and the attribution of discriminatory treatment to a specific cause, race versus sexual orientation versus something else, is inherently subjective. The analysis was also restricted to California adults of working age, and patterns could differ elsewhere. Still, the study, which was funded in part by the California Department of Public Health and reviewed as exempt by the University of Hawaiʻi at Mānoa Institutional Review Board, offers a template for future research: model discrimination as an exposure with both a type and a chronicity, rather than as a proxy embedded in demographic labels. If replicated, the finding that sexual orientation discrimination alone roughly doubles the odds of cigarette smoking would rank among the strongest social-environmental correlates of tobacco use ever quantified at the population level, and it would give tobacco control programs a concrete, measurable target in their efforts to close the gaps in health that demographics alone cannot explain.

Subject of Research: The association between racial/ethnic and sexual orientation discrimination and tobacco product use among California adults

Article Title: Tobacco product use at the intersection of racial/ethnic and sexual orientation discrimination among California adults, 2022–2023: an observational study

Article References: Stupplebeen, D. A., Donaldson, C. D., & Vuong, T. D. (2026). Tobacco product use at the intersection of racial/ethnic and sexual orientation discrimination among California adults, 2022–2023: an observational study. International Journal for Equity in Health. https://doi.org/10.1186/s12939-026-03054-z

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03054-z

Keywords: tobacco use, discrimination, health disparities, sexual orientation, race and ethnicity, cigarette smoking, vaping, minority stress, California, epidemiology, public health, equity

The study, published in Cancer Causes & Control, drew on the Surveillance, Epidemiology, and End Results (SEER) 12 registry program, which covers approximately twelve percent of the U.S. population and offers continuous population-based incidence data stretching back to 1992. Researchers from Baylor College of Medicine identified 68,023 cases of hepatocellular carcinoma diagnosed between January 1, 1992 and December 31, 2022 among adults aged twenty and older. Rather than simply tracking raw incidence rates, the team focused on incidence rate ratios, or IRRs, which compare the age-adjusted rate in each demographic group against a reference group, women in the sex analysis and non-Hispanic White individuals in the race and ethnicity analysis. This approach isolates relative disparities from absolute incidence, revealing whether the distance between groups is widening or narrowing even when all rates are rising together.

The headline trend is that hepatocellular carcinoma in the United States has passed through an inflection point. Annual case counts climbed from 840 in 1992 to 2,846 in 2022, an increase of nearly 239 percent, and the overall age-adjusted rate rose from 4.27 to 7.84 per 100,000 person-years over the same period. Joinpoint regression, a statistical technique that identifies inflection points in trend data using Monte Carlo permutation testing, showed that incidence rose by 4.72 percent annually from 1992 to 2009, plateaued between 2009 and 2015, and then declined by 3.41 percent per year from 2015 to 2022. This late reversal is significant because earlier forecasts, notably a 2016 projection based on data through 2012, had anticipated continued increases through 2030. The new analysis demonstrates that the anticipated turning point has in fact materialized.

Sex differences remain the most durable feature of liver cancer epidemiology. Men were diagnosed at 12.24 per 100,000 in 2022 compared with 3.95 per 100,000 among women, and the male-to-female incidence rate ratio never dropped below three. Yet the ratio itself declined from 3.29 in 1992 to 3.11 in 2022. The dynamics behind that shift are revealing: from 1992 to 2012 the male-to-female IRR actually increased slightly, by about half a percent per year, before falling by 1.64 percent annually thereafter. The narrowing was driven by steeper declines in male incidence after 2012 rather than any surge in female rates, and the effect was most pronounced among adults under fifty, where the IRR dropped by roughly six percent per year after 2012, though the authors caution that the confidence interval on that age-stratified estimate was wide and warrants cautious interpretation.

The most dramatic change, however, unfolded along racial and ethnic lines. In 1992, non-Hispanic Asian/Pacific Islander individuals were diagnosed with hepatocellular carcinoma at nearly six times the rate of non-Hispanic White individuals, an IRR of 5.86. By 2022 that ratio had fallen to 1.87, an average annual decline of 3.93 percent across the study period. This extraordinary convergence reflects two simultaneous movements: incidence among Asian/Pacific Islander Americans actually declined over the three decades, from about 15.2 to 10.2 per 100,000, while incidence among non-Hispanic White individuals rose from 2.6 to 5.5 per 100,000. The declining IRR therefore captures both good news in one population and rising burden in another, a nuance the authors emphasize repeatedly.

The other relative disparities narrowed more modestly. The non-Hispanic Black-to-non-Hispanic White IRR fell from 2.08 to 1.44, with the most significant decline occurring between 2005 and 2022. The Hispanic-to-non-Hispanic White IRR barely moved, easing from 2.62 to 2.40, an average annual decrease of only 0.57 percent. Across the full study period, incidence remained highest among Asian/Pacific Islander individuals at 14.27 per 100,000, followed by Hispanic individuals at 12.12, non-Hispanic Black individuals at 9.30, and non-Hispanic White individuals at 4.37. Age-stratified analyses added further texture: among adults under fifty, the Black-to-White IRR declined linearly throughout the period, whereas among older adults it first rose by 1.61 percent annually through 2005 before declining by nearly two percent annually thereafter.

What lies behind these shifting ratios? The study cannot establish causation, since SEER registries do not record individual risk factors, but the temporal patterns align strikingly with known changes in the etiology of liver cancer. Hepatitis B virus has long been a dominant driver of hepatocellular carcinoma in Asian and Pacific Islander populations, and the United States added universal infant HBV vaccination to its immunization schedule in 1991, with particularly high uptake among post-1991 birth cohorts and among Asian American children. Because preventing chronic HBV infection in infancy reduces cancer risk only after a long latency, the timing of declining incidence among younger adults in these historically high-prevalence populations is temporally compatible with a vaccination effect, though the authors stress this remains hypothesis-generating rather than proof.

Hepatitis C tells a complementary story. Direct-acting antivirals, which cure HCV infection and thereby interrupt the progression to cirrhosis and cancer, became available in the United States in late 2013 and expanded rapidly through the latter half of the 2010s. The post-2015 decline in overall hepatocellular carcinoma incidence follows this therapeutic revolution closely enough to suggest a genuine contribution, but the variable latency between viral eradication and changes in cancer risk means the association must be interpreted cautiously. Meanwhile, a countervailing force is gathering strength: metabolic dysfunction-associated steatotic liver disease, or MASLD, and diabetes are becoming increasingly dominant drivers of new liver cancer cases, and population-level alcohol consumption and alcohol-associated liver disease mortality have both risen in recent decades. These trends do not explain the recent overall decline and may instead represent a competing influence shaping which groups continue to bear the burden.

The sex-specific narrowing may be an early signal of the metabolic transition. Accumulating evidence suggests that women with diabetes and MASLD may experience a disproportionately greater relative increase in liver-related risk compared with men, and as the prevalence of metabolic disease rises, particularly among younger and middle-aged women, the historical male predominance in liver cancer may continue to attenuate. This would represent a fundamental shift in the epidemiology of a cancer whose sex disparity has been attributed in part to higher rates of viral hepatitis and heavy alcohol use among men.

The study’s authors are careful about what these findings do and do not mean. The narrowing of incidence rate ratios signals attenuation of relative disparities, not their elimination; absolute incidence in 2022 remained substantially higher among men than women and among Asian/Pacific Islander, Hispanic, and Black individuals than among non-Hispanic White individuals. Limitations include the absence of individual-level data on risk factors, the possibility that evolving diagnostic practices and surveillance influenced case ascertainment, potential misclassification of race and ethnicity, and geographic coverage limited to roughly thirteen percent of the U.S. population, excluding regions such as Texas that appear only in newer SEER releases. The team selected SEER 12 over the broader SEER 21 database precisely because it extends back to 1992, enabling a genuinely long-term view. Still, the message for public health is clear: vaccination, antiviral therapy, and early detection have visibly reshaped who gets liver cancer in America, but continued efforts to prevent, detect, and manage both viral and metabolic liver disease are needed to close the remaining gaps.

Subject of Research: Temporal trends in sex and racial/ethnic disparities in hepatocellular carcinoma incidence in the United States from 1992 to 2022

Article Title: Temporal changes in sex and race/ethnicity incidence rate ratios for hepatocellular carcinoma in the United States, 1992–2022

Article References: Temporal changes in sex and race/ethnicity incidence rate ratios for hepatocellular carcinoma in the United States, 1992–2022. (n.d.). https://doi.org/10.1007/s10552-026-02238-w

Image Credits: AI Generated

DOI: 10.1007/s10552-026-02238-w

Keywords: hepatocellular carcinoma, liver cancer, incidence rate ratios, health disparities, SEER, hepatitis B, hepatitis C, MASLD, sex differences, race and ethnicity, cancer epidemiology, Cancer Causes & Control

Ernesto F. L. Amaral and Nereyda Y. Ortiz Osejo de Lemus of Texas A&M University analyzed American Community Survey data spanning 2005 to 2024, covering adults aged eighteen and older across the entire country. Their central question was deceptively simple: are the places where migration rates run high the same for everyone, and do the groups with the strongest regional concentrations also have the highest individual likelihood of moving? The answer, they found, is frequently no—a discrepancy with significant implications for how researchers and policymakers understand population redistribution in America.

The backdrop to the study is what demographers have called the Great American Migration Slowdown. Between 1968 and 2009, annual interstate migration rates fell from 3.6 percent to just 1.6 percent, and between 1982 and 2015, moves across state and county lines dropped by roughly half. The new analysis confirms this trajectory continued into recent years: overall migration rates bottomed out at 4.57 percent in 2012, recovered modestly through 2019, dipped during the COVID-19 pandemic, and settled back down to 4.58 percent by 2024. The decline is pronounced compared with other developed countries and is thought to reflect reduced responsiveness to regional economic differences, growing place attachment, and shifts in job mobility.

But the aggregate numbers conceal enormous variation. Hispanic, non-Hispanic African American, and non-Hispanic Native American populations consistently showed lower migration rates than non-Hispanic whites and non-Hispanic Asians throughout the two decades studied, with foreign-born Hispanics recording the lowest rates of any group. Foreign-born individuals of all backgrounds moved less often than their U.S.-born counterparts, reflecting differences in settlement histories, social networks, and access to information about destinations. When the researchers modeled individual migration odds statistically, controlling for age, education, income, marital status, children, homeownership, employment, and region of residence, these group differences persisted rather than disappearing.

The spatial half of the analysis used a technique called Local Indicators of Spatial Association, or LISA, which identifies statistically significant clusters of high or low values across neighboring geographic areas. Applied to Migration Public Use Microdata Areas—the finest geography available in the public census microdata—the method revealed striking regional signatures. In 2019, hotspots of high internal migration appeared across parts of the West, including northern California, Nevada, Utah, southern Idaho, and northwestern Wyoming, along with central Texas and northern Florida. By 2024, most of the western hotspots had faded, while Texas and Florida concentrations endured. A long corridor of low migration, stretching from Texas through the Midwest to the Northeast, remained stable across the entire period and even expanded into California and New Mexico.

Those patterns, however, look very different depending on which demographic group is mapped. Non-Hispanic African Americans showed pronounced high-migration clusters across southeastern regions, alongside widespread low-migration zones in the Midwest, Northeast, and West. Hispanic clustering concentrated in California, the Mountain West, Texas, and Florida. Non-Hispanic Native Americans displayed high-migration clusters in the Northwest, Southwest, and parts of the Great Plains, including Arizona, Utah, New Mexico, Colorado, Oklahoma, and Alaska—areas where Indigenous populations are geographically concentrated. Non-Hispanic Asians, by contrast, were characterized mainly by low-migration clusters in southern and Midwestern regions, with some expansion into the Northwest by 2024.

Nativity proved to be a crucial modifier of these spatial patterns. U.S.-born Hispanics showed broad high-migration clustering across western and southern areas, while foreign-born Hispanics displayed far fewer hotspots, concentrated primarily in Texas and Florida by 2024. The contrast was equally stark for African Americans: U.S.-born Black migrants exhibited a broad southeastern pattern, whereas foreign-born Black migrants showed tightly localized clusters in eastern metropolitan areas, including Florida, Atlanta, and Washington, DC—patterns likely reflecting distinct immigrant origins, settlement networks, and labor market incorporation. Foreign-born whites, meanwhile, were marked predominantly by low-migration clusters across central regions of the country.

Perhaps the study’s most striking finding is that regional concentration and individual mobility are genuinely distinct dimensions of migration. Non-Hispanic African Americans and Hispanics both showed lower individual odds of moving than non-Hispanic whites after adjustment, yet both groups displayed strong, persistent regional hotspots. Conversely, non-Hispanic Asians showed relatively high individual mobility despite maps dominated by low-migration clusters. A group can be regionally concentrated precisely because most of its members who do move go to the same places, or because past settlement histories anchor its geography, without its members being frequent movers overall. The authors are careful to note that their LISA maps describe spatial clustering at selected points in time and cannot disentangle the cumulative flows, network effects, and historical settlement processes that may have produced them.

The research also has limitations that the authors acknowledge candidly. The analysis is associational rather than causal, and the logistic regression models do not formally account for spatial autocorrelation, which could lead to underestimated standard errors. The aggregated geographic units limit the ability to study very local dynamics, and detailed subgroup-specific flow analysis at the county level would require restricted Census data. The 2020 ACS, disrupted by pandemic data-collection problems, was tested in robustness checks and found not to alter the main results. Still, the authors argue the two-pronged approach—descriptive spatial clustering paired with adjusted individual-level models—offers a descriptive framework that previous single-lens studies could not provide.

What emerges is a compelling guide for future research. The findings point directly to places and populations where localized studies could uncover the mechanisms behind the patterns: Hispanic migration in Texas and Florida, African American migration in the Southeast, foreign-born African American settlement in Atlanta and Washington, DC, and Native American migration across the Southwest, Great Plains, and Alaska. The authors suggest combining administrative county-to-county flow data with survey microdata, and applying spatially explicit methods such as geographically weighted regression, to test whether the relationships they identify vary across places. As the United States continues to grow more demographically diverse while its residents grow more rooted, understanding precisely where and how different communities redistribute themselves—and why geography and mobility do not always move in tandem—has become an essential question for demographers, economists, and anyone concerned with regional inequality.

Subject of Research: Spatial patterns and demographic heterogeneity of internal migration in the United States by nativity and race/ethnicity

Article Title: Internal migration, demographic heterogeneity, and spatial patterns in the United States

Article References: Internal migration, demographic heterogeneity, and spatial patterns in the United States. (n.d.). https://doi.org/10.1007/s12546-026-09434-0

Image Credits: AI Generated

DOI: 10.1007/s12546-026-09434-0

Keywords: internal migration, demographic heterogeneity, spatial clustering, LISA, nativity, race and ethnicity, American Community Survey, population redistribution, spatial demography, United States, logistic regression, migration slowdown

The research, led by Sarah N. Kunz of Harvard Medical School and Beth Israel Deaconess Medical Center together with colleagues at Stanford University School of Medicine and the California Perinatal Quality Care Collaborative, examined data from California on very low birth weight, preterm infants born before 37 weeks of gestation who were less than 28 days old. The study period spanned 2012 through 2018, a window that captures a mature era of regionalized perinatal care in the nation’s most populous state. California offers a particularly valuable setting for this kind of analysis because of its sheer scale and the richness of its linked birth cohort records, which allow researchers to follow infants from birth through any subsequent acute transport between hospitals with unusual precision.

The design of the study was a retrospective cohort analysis, meaning the investigators looked backward at records that had already been generated by routine clinical care. Their outcome of interest was acute inter-hospital transport, the urgent movement of a newborn from one hospital to another, typically because the receiving institution can provide a level of neonatal intensive care that the discharging hospital cannot. These transports are among the highest-stakes events in neonatal medicine. A tiny infant, often weighing less than a carton of milk, is placed in a portable incubator, connected to a transport ventilator, monitored continuously, and driven or flown across traffic and distance to a destination intensive care unit. Every minute of that journey carries physiologic risk, and the quality of the stabilization before departure can determine whether the infant arrives in stable condition or in crisis.

To isolate the effect of race and ethnicity on transport likelihood, the team calculated odds ratios comparing each racial and ethnic group against non-Hispanic White infants. The comparison groups included non-Hispanic Black infants, infants classified as Asian American, Native Hawaiian, and Pacific Islander, often abbreviated AANHPI, and Hispanic infants. Critically, the models did not stop at this simple comparison. The investigators controlled for a battery of confounding factors organized into four domains: the characteristics of the hospital network in which the birth occurred, hospital-level factors such as the level of the neonatal intensive care unit, maternal sociodemographic characteristics, and infant clinical characteristics that reflect how sick the baby was at the time a transport decision would be made.

The central finding was striking in its specificity. Asian American, Native Hawaiian, and Pacific Islander infants were significantly less likely to be acutely transported than non-Hispanic White infants, with an odds ratio of 0.85 and a p-value of 0.01 after full risk adjustment. An odds ratio of 0.85 translates to roughly a 15 percent lower odds of transport for this group compared with their White counterparts, once all measured sources of confounding have been removed from the equation. In other words, this was not a difference explained by where these infants happened to be born, by the capabilities of their birth hospitals, by their gestational age or birth weight, or by the illness severity recorded in their charts. Something in the system itself appeared to be operating differently for these infants.

Equally instructive was what the analysis revealed about the strongest predictors of transport overall. Hospital-level factors, most notably the level of the neonatal intensive care unit at the birth hospital, were the variables most significantly associated with whether a transport occurred. This makes biological and organizational sense. An infant born at a community hospital without a Level III or Level IV neonatal intensive care unit is far more likely to require transfer to a regional center than an infant born already inside such a center. This mechanism is the entire logic of perinatal regionalization, the organized system through which states route high-risk mothers and infants toward hospitals with the resources to care for them. Studies stretching back to the 1980s have consistently demonstrated that very low birth weight infants delivered at appropriate levels of care experience lower mortality, and meta-analyses have confirmed the survival advantage of regionalized systems.

Yet the system does not always function as designed. Prior work by some of the same investigators has documented the phenomenon of deregionalization, in which an increasing share of very low birth weight infants are born at hospitals that lack the highest levels of neonatal capability, eroding the protective effect of the regional model. Other research from the California Perinatal Quality Care Collaborative has shown that racial and ethnic disparities extend deep into the quality of care itself, with infants from minoritized groups receiving care in neonatal intensive care units that systematically deliver lower-quality services, a pattern described as racial segregation and inequality within the neonatal intensive care landscape. The new transport findings fit into this larger mosaic, suggesting that inequities are not confined to what happens inside intensive care units but also shape the very pathways by which infants move between them.

The authors’ interpretation of their findings is deliberately measured. They conclude that the differing likelihood of acute transport by race and ethnicity may reflect underlying inequities and implicit biases in the system of care. This framing is important because it locates the problem not in the decisions of any single clinician but in the accumulated, often invisible patterns of how referrals are initiated, how transport teams are dispatched, and how risk is assessed across different patient populations. Implicit bias in clinical decision-making is well documented across medicine, and neonatal transport involves rapid judgments under time pressure, exactly the conditions in which unexamined assumptions about patients are most likely to influence behavior. Whether the lower transport rate among AANHPI infants reflects under-triage, differences in referral relationships, communication barriers, or other mechanisms is a question the study was not designed to answer, but the statistically robust association demands investigation.

The implications for policy and practice are concrete. Because hospital-level factors dominate the transport equation, strengthening adherence to regionalization principles, ensuring that high-risk deliveries occur at appropriately equipped hospitals, and auditing transport decisions for racial and ethnic equity are all actionable levers. The study also underscores the value of the granular data infrastructure maintained by quality collaboratives, which made it possible to detect a disparity that would be invisible in national aggregates. For the AANHPI category in particular, the finding adds urgency to calls for disaggregated data, since this grouping bundles together populations with widely divergent risk profiles and outcomes. What the study ultimately delivers is a measurable signal that the ambulance is not the same ambulance for every baby, a finding that should resonate far beyond California and into every perinatal system that claims, as its founding promise, that the sickest infants will reach the highest level of care regardless of who they are.

The dataset underpinning the analysis came from the California Perinatal Quality Care Collaborative, a statewide initiative that collects detailed clinical information from neonatal intensive care units across California. Because these records are gathered under a data use agreement rather than released publicly, the authors note that the underlying data are available only upon reasonable request with the collaborative’s permission. This governance model is common among quality collaboratives, which balance the research value of granular clinical data against the privacy protections owed to patients and participating hospitals.

The study’s statistical approach deserves emphasis. By adjusting simultaneously for network, hospital, maternal, and infant characteristics, the investigators sought to ensure that the observed difference in transport odds was not an artifact of clustering, since infants born at the same hospital share equipment, staffing, and referral practices. This kind of multilevel risk adjustment is essential in perinatal research, where the hospital an infant is born in is itself shaped by maternal residence, insurance, and patterns of segregation that precede any clinical decision.

The findings also connect to a long line of evidence on neonatal outcomes by race and ethnicity. Prior studies have documented disparities in very preterm neonatal morbidities, differences in mortality among very preterm infants across hospitals in large cities, and variation in outcomes for infants born at less than 30 weeks of gestation over time. Systematic reviews of neonatal intensive care have catalogued racial and ethnic differences spanning access, quality, and outcomes, indicating that no single point in the care pathway is immune.

Acute transport occupies a distinctive position in this pathway because it sits at the junction of multiple institutions. A transport decision requires coordination between the referring hospital, the transport team, and the receiving center, each with its own protocols and thresholds for escalation. Disparities arising at this junction may be harder to detect than disparities within a single unit, which makes the statistical signal reported here particularly valuable for quality improvement efforts aimed at ensuring equitable access to regionalized care.

Subject of Research: Racial and ethnic disparities in acute inter-hospital neonatal transport among very low birth weight infants in California

Article Title: Differential transport patterns by race and ethnicity in very low birth weight infants

Article References: Kunz, S. N., Zitnik, M., Helkey, D., Razdan, S., Gould, J. B., Profit, J., & Zupancic, J. A. F. (2026). Differential transport patterns by race and ethnicity in very low birth weight infants. Journal of Perinatology. https://doi.org/10.1038/s41372-026-02896-3

Image Credits: AI Generated

DOI: 10.1038/s41372-026-02896-3

Keywords: very low birth weight, neonatal transport, race and ethnicity, health disparities, neonatal intensive care, perinatal regionalization, odds ratio, California, Journal of Perinatology, AANHPI, NICU level, implicit bias