The findings, published in Neurology, the medical journal of the American Academy of Neurology, arrive at a pivotal moment. Anti-amyloid therapies represent the first approved drugs that modify the underlying biology of Alzheimer’s disease rather than merely managing its symptoms, and their use is expected to expand steadily as diagnostic tools improve and clinical experience grows. But the study’s numbers reveal a stark pattern in who is actually reaching the infusion chair. Black adults had 86 percent lower odds of receiving an anti-amyloid medication compared with non-Hispanic white adults, while Hispanic adults had 79 percent lower odds, after the researchers accounted for other clinical and demographic factors.

“The association we found between race/ethnicity and anti-amyloid medication use raises important questions about how patients are identified, evaluated and ultimately selected for treatment,” said Melissa Elafros, M.D., Ph.D., co-first author of the study and the Andrea and Lawrence A. Wolfe Research Professor at University of Michigan Medical School. “It’s critical that we understand and address the disparities we are seeing today so that as many patients as possible receive benefits.”

To conduct the analysis, the research team drew on a database of more than one million adults diagnosed with mild cognitive impairment or dementia. From that population, they identified 2,427 patients who had received an anti-amyloid medication and compared them with a closely matched group of untreated patients. Because the study was observational, it captures associations rather than proving cause and effect, but the scale of the dataset allowed the investigators to examine how race, ethnicity, comorbid health conditions and social circumstances all intersected with the likelihood of treatment.

Beyond race and ethnicity, the researchers found that social and economic disadvantage played a powerful role. Participants who faced greater disadvantages, measured through factors including income, education, and access to housing and neighborhood resources, were nearly half as likely to receive the latest therapies as their less vulnerable counterparts. Health comorbidities were also strongly associated with whether patients were treated, suggesting that clinicians and health systems may be weighing a complex mix of medical and social considerations when deciding who is a candidate for drugs that require regular infusions, repeated brain imaging and careful monitoring for side effects such as amyloid-related imaging abnormalities.

What the study did not find may be just as consequential as what it did. Once patients began anti-amyloid therapy, adherence was similar across racial and ethnic groups, meaning that the disparities concentrate at the front door of treatment rather than in the day-to-day management of it. “Although race, ethnicity and overall vulnerability are associated with whether patients receive an anti-amyloid medication, we found no differences in initial adherence among those who start treatment,” said Brian C. Callaghan, M.D., M.S., senior author of the study and the Eva L. Feldman, MD, PhD Professor at U-M Medical School. “This suggests that interventions should focus on helping eligible patients start therapy, rather than on adherence after treatment begins.”

That distinction carries significant implications for how the field responds. If patients who begin therapy take the drugs as prescribed at comparable rates, then the bottleneck lies upstream, in the processes that determine who is referred, who undergoes amyloid testing, who is evaluated at specialized memory centers and who is ultimately offered treatment. Anti-amyloid drugs are typically reserved for people with early-stage disease confirmed by biomarkers, a requirement that depends on access to specialists, advanced imaging, lumbar punctures or other diagnostic resources that are unevenly distributed across the health care landscape. Communities that have historically faced barriers to neurologic care may therefore be systematically underrepresented among treatment candidates before any prescribing decision is even made.

The study was funded through a research contract with the American Academy of Neurology, and the authors note that its observational design means unmeasured factors could contribute to the observed differences. Even so, the consistency of the signal across more than two thousand treated patients and a comparable untreated comparison group strengthens the case that the disparities reflect structural patterns rather than random variation. Additional authors on the paper include Lavanya Muthukumar, M.S., and Samuel Terman, M.D., both of the University of Michigan, with further contributors listed in the published article.

For clinicians and policymakers, the message from the Michigan team is that the window for shaping equitable access is open now, while anti-amyloid therapies are still early in their real-world rollout. The researchers argue that understanding and addressing the disparities observed today is essential so that the benefits of a new generation of Alzheimer’s treatments reach as many eligible patients as possible, rather than reproducing the inequities that have long characterized dementia care. As these drugs move from specialized centers into broader clinical practice, the study offers a baseline measurement of who is being left behind, and a warning that without deliberate intervention, the first disease-modifying era of Alzheimer’s medicine could widen existing gaps in brain health.

Subject of Research: Racial, ethnic and socioeconomic disparities in access to anti-amyloid Alzheimer's disease therapies

Article Title: Who gets Alzheimer’s drugs? Race, vulnerability and health status shape access

Article References: Who gets Alzheimer’s drugs? Race, vulnerability and health status shape access. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: Alzheimer's disease, anti-amyloid therapy, health disparities, mild cognitive impairment, dementia, Neurology, Michigan Medicine, adherence, social determinants of health, race and ethnicity, amyloid plaques, disease-modifying treatment

The study, led by Jessica A. Chen and Emily C. Williams of the University of Washington and VA Puget Sound Health Care System, examined monthly treatment patterns among more than 110,000 veterans diagnosed with opioid use disorder between March 2018 and February 2022. Published in Addiction Science & Clinical Practice, the research drew on 48 monthly cohorts extracted from national electronic health records, covering outpatients aged 18 and older with a past-year opioid use disorder diagnosis. The team tracked receipt of any medication for opioid use disorder, including methadone, buprenorphine, and naltrexone, and then examined methadone and buprenorphine separately to see how each medication’s use changed over time and across racial and ethnic groups.

The analytical design was deliberately granular. Rather than comparing a single pre-pandemic year with a single pandemic year, the researchers constructed 48 consecutive monthly cohorts, allowing them to trace trends with unusual precision across the entire 2018 to 2022 window. The primary outcome was receipt of any medication for opioid use disorder in a given month. Secondary analyses split the picture by medication type, because methadone and buprenorphine are delivered through very different channels: methadone is dispensed only through federally regulated opioid treatment programs with strict supervision requirements, while buprenorphine can be prescribed by office-based clinicians and carried in a patient’s pocket.

At the start of the study window, the system looked remarkably equitable on the surface. In March 2018, non-Hispanic Black and non-Hispanic White veterans with opioid use disorder received any medication for opioid use disorder at nearly identical rates, 27.3 percent and 27.8 percent respectively. Hispanic Black patients started at 28.0 percent, essentially matching Hispanic White patients at 28.4 percent and Hispanic patients who were neither Black nor White at 27.0 percent. Four years later, that parity had eroded. By February 2022, 35.0 percent of non-Hispanic White patients were receiving medication, compared with only 29.3 percent of non-Hispanic Black patients. Among Hispanic patients, the same pattern emerged: Hispanic Black patients stood at 26.2 percent, while Hispanic White and Hispanic neither Black nor White patients had climbed to 33.2 percent and 33.7 percent respectively.

The medication-specific numbers reveal where the divergence originated. Buprenorphine receipt increased after the pandemic began, but the increase was strikingly unequal. Non-Hispanic White patients rose from 27.9 percent to 29.8 percent receiving buprenorphine, while non-Hispanic Black patients moved only from 13.9 percent to 15.5 percent and Hispanic Black patients from 11.6 percent to 15.1 percent. In other words, White veterans were roughly twice as likely as Black veterans to receive buprenorphine at both the start and the end of the study period, and the pandemic-era expansion of prescribing did little to narrow that chasm.

Methadone told the opposite story. Receipt of methadone declined after the pandemic began for every group, yet Black patients remained far more dependent on it than White patients. Non-Hispanic Black patients fell from 17.4 percent to 14.4 percent receiving methadone, and Hispanic Black patients from 17.1 percent to 11.9 percent, while non-Hispanic White patients declined only from 6.6 percent to 5.5 percent. The result is a persistent structural pattern: Black veterans with opioid use disorder were more than twice as likely as White veterans to be on methadone, the medication tied to daily clinic visits and rigid dispensing schedules, and far less likely to be on buprenorphine, the medication most compatible with ordinary life, employment, and privacy.

Why does this split matter clinically? Buprenorphine and methadone are both full-strength opioid agonist treatments that reduce overdose mortality and improve retention in care, but they impose different burdens. Methadone traditionally requires daily attendance at a specialized clinic, which can be difficult for people with inflexible jobs, unreliable transportation, or childcare responsibilities. Buprenorphine, by contrast, can be prescribed in routine medical settings and taken at home. When pandemic policies loosened methadone dispensing rules and eased buprenorphine initiation, the expectation was that both medications would reach more people, particularly those historically excluded. The VHA data show that overall access did expand, but the expansion accrued disproportionately to White patients, leaving the underlying hierarchy of treatment untouched.

The study’s authors are careful to frame the findings as descriptive rather than causal. The analysis documents trends in receipt by race and ethnicity across the pre-pandemic and pandemic periods; it does not identify the specific mechanisms that produced the widening gaps. Still, the implications are pointed. Pandemic-related policy changes were intended to expand access to medications for opioid use disorder, the researchers conclude, but their benefits may not have been equitably distributed across racial and ethnic groups. Improving equity, they argue, may require targeted approaches to reduce barriers to both buprenorphine and methadone, rather than assuming that broad flexibilities will lift all boats.

The research also carries methodological significance for how health systems monitor equity. By disaggregating Hispanic patients into Hispanic Black, Hispanic White, and Hispanic neither Black nor White subgroups, the study avoided treating Hispanic veterans as a monolithic category and surfaced disparities that aggregate statistics would conceal. Hispanic Black patients, for example, ended the study period with the lowest medication receipt of any subgroup examined, a finding invisible in analyses that collapse all Hispanic patients together. The work was supported by the National Institute on Drug Abuse and was informed by consultation from groups of veterans with lived and living experience of opioid use, including the Veterans’ Opioid Use disorder Inequities CommitteE and the Research with Expert Advisors on Drug Use panel.

For a health system caring for a population at elevated risk of fatal overdose, the message is sobering. The VHA is the largest integrated healthcare system in the United States, and its electronic health records offer one of the few national windows into how treatment patterns actually shifted when prescribing rules changed. The data show that between 2018 and 2022, the share of White veterans receiving buprenorphine grew while the share of Black veterans receiving methadone shrank, and the two trends combined to leave Black patients with less access to the most flexible, most widely available treatment option. As policymakers consider making pandemic-era flexibilities permanent, the study suggests that flexibility alone is not enough; without deliberate attention to who actually receives each medication, the same structural inequities will persist, and the promise of expanded opioid treatment will remain unevenly fulfilled.

Subject of Research: Racial and ethnic inequities in receipt of methadone and buprenorphine for opioid use disorder in the Veterans Health Administration before and after COVID-19

Article Title: Trends in receipt of methadone vs. buprenorphine by race/ethnicity before and after COVID-19 (2018–2022): a Veterans Health Administration study

Article References: Chen, J. A., Dunn, J. A., Maskey, P., Austin, E. J., Durland, M. L., Ravi, V., Warth, A., Brooks, J., Marshall, S., van Draanen, J., Jones-Smith, J., & Williams, E. C. (2026). Trends in receipt of methadone vs. buprenorphine by race/ethnicity before and after COVID-19 (2018–2022): a Veterans Health Administration study. Addiction Science & Clinical Practice. https://doi.org/10.1186/s13722-026-00730-x

Image Credits: AI Generated

DOI: 10.1186/s13722-026-00730-x

Keywords: opioid use disorder, medications for opioid use disorder, methadone, buprenorphine, health disparities, Veterans Health Administration, COVID-19, race and ethnicity, veterans, addiction treatment, health policy, Trends

The research team, led by Lauren Lang of Emory University and Julianna Gerold of the Massachusetts General Hospital Athinoula A. Martinos Center for Biomedical Imaging, together with colleagues at Harvard, Brown, and the University of Minnesota, set out to answer two questions. The first was empirical: what guidance do neuroscience journals currently provide, and how much does it vary? The second was normative: should that guidance be standardized, and if so, what form should the standards take? Their answer to the first question is unambiguous. Their answer to the second is more nuanced, and it challenges the field to think carefully about the difference between how variables are reported and what those variables actually mean.

To conduct the survey, the researchers examined the 25 highest impact factor journals in the Neurosciences category of the Observatory of International Research rankings as of May 2024. They excluded two journals, Molecular Neurodegeneration and Sleep Medicine Reviews, for insufficient human neuroimaging content or insufficient website information, and added four others where influential human neuroimaging work is frequently published: Human Brain Mapping, Science, Nature, and Oxford Open Neurosciences. Between June 28 and July 10, 2024, the team reviewed each journal’s website for author guidance on population descriptors and emailed senior editors to ask about their journals’ standards, policies, or informal norms for reporting demographic data. Nineteen of the 25 journals contacted responded.

The results paint a picture of a field without a common playbook. Twenty-one of the 27 journals, or 78 percent, provide authors with at least some guidance on reporting race and ethnicity, but four of those limit their guidelines exclusively to clinical trials rather than all human studies. That leaves 22 percent of journals offering no guidance whatsoever. Among the journals that do provide direction, six different guideline frameworks are in circulation, with the International Committee of Medical Journal Editors recommendations, Nature’s guidance, and the American Medical Association Manual of Style the most commonly adopted. Most guidelines simply require that reported categories be defined and that any decision to omit race or ethnicity be explained, without specifying how authors should define or operationalize the categories themselves. Only one journal, Human Brain Mapping, states an explicit preference, favoring ethnicity over race.

A smaller group of journals has adopted more comprehensive frameworks. Seven of the 27, or 26 percent, follow either Nature’s guidelines or the AMA Manual of Style. Nature’s guidance calls for reporting race and ethnicity or justifying any omission, using inclusive and respectful language, considering genetic ancestry, and warning that manuscripts may be revised or rejected for racist or harmful content. The AMA’s 2024 update goes further in one crucial respect: it states explicitly that race, ethnicity, and geographic origin are not valid proxies for genetic ancestry, and it requires authors to use inclusive and specific language, attend to privacy and ethics, apply nuanced categorization, and acknowledge limits on generalizability. Yet even these detailed frameworks stop short of telling researchers how to define the categories they report.

Perhaps the most revealing finding concerns the editors themselves. When the researchers corresponded with one senior editor whose journal publishes author guidelines on its website, the editor replied that the journal had, in the editor’s words, no specific policies on the description of race and ethnicity demographic variables. If the people running journals are not always aware of their own published policies, the authors reasoned, author compliance is likely to suffer. To test that suspicion, the team conducted a pilot analysis of Biological Psychiatry, one of only two journals in their sample that had adopted the AMA guidelines, which require reporting of race and ethnicity or an explanation for their absence. Reviewing all human subjects research articles published in the journal between February 1 and August 15, 2024, they found that only 30 of 61 articles, or 49 percent, reported participants’ race, ethnicity, or ancestry. Just a single article complied with all AMA requirements, and it did so largely because its homogenous sample rendered many of the reporting guidelines inapplicable.

The authors speculate that low adherence reflects both the relative newness of these policies and inconsistent enforcement. Many working investigators were trained at a time when instruction on reporting race and ethnicity was not a priority in scientific writing. But the deeper issue the review raises is conceptual. Race is a sociopolitical construct that does not map onto genetic ancestry, yet it is frequently used as a proxy for genetic ancestry or for exposure to social determinants of health. When race or ethnicity stands in for social determinants, researchers cannot precisely identify the mechanisms underlying observed effects, and attributing differential health outcomes to race places the burden of disease on individuals while obscuring systemic causes. The stakes of getting this wrong are not abstract. In the nineteenth and early twentieth centuries, practices such as cranial measurement were deployed to rank intelligence across racialized groups, reinforcing biologically deterministic hierarchies. Although those claims have been discredited, their methodological legacy persists whenever socially constructed categories are treated as proxies for biological difference in contemporary neuroimaging analyses.

At the same time, the authors are careful not to argue that race and ethnicity should be abandoned as research variables. The 2022 National Academies report on improving representation in clinical trials and research documents how recognizing the distinct medical needs of various groups has contributed to reductions in health disparities. Mindful use of population descriptors can promote representativeness, increase generalizability, and keep findings interpretable for the populations to which they apply. The challenge, then, is to design standards that neither reify biological race nor erase the ethical relevance of these variables. The authors draw a key distinction between procedural standards, which require researchers to report their decisions about whether and how to include race, and substantive standards, which would require every study to define race the same way. Given the recognized variation in how individuals define race and ethnicity, they conclude that a universal substantive standard is not advisable. Instead, they endorse the view articulated by Cardenas-Iniguez and Gonzalez in 2024 that no categorical definition of race and ethnicity is exhaustive and without limitations, and that researchers should be intentional, equitable, and responsible in their chosen operationalization.

Models for such an approach already exist in adjacent fields and large-scale consortia. The Adolescent Brain Cognitive Development Study cautions against misusing population descriptors in genetic analyses and emphasizes responsible interpretation as a condition of data access, noting that self-reported race and ethnicity primarily reflect social and environmental experiences rather than genetic variation. The UK Biobank employs standardized ethnic background categories with defined subcategories while publishing clear statements about selection biases, including healthy volunteer bias and socioeconomic skew, giving researchers context for interpretation rather than implying global representativeness. In genetics and epidemiology, professional societies such as the International Genetic Epidemiology Society and programs like the National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine initiative have issued recommendations emphasizing careful terminology, explicit justification for population groupings, avoidance of race or ethnicity as proxies for genetic ancestry, and consideration of potential harms alongside analytic benefits.

The authors close with three concrete recommendations. First, journals should require transparency about whether and how race, ethnicity, and ancestry are used in every human neuroscience study, giving researchers flexibility while demanding justification. Second, journal editors should collaborate to develop field-wide procedural standards, drawing on existing frameworks from Nature, the AMA, and ICMJE, and the team is pursuing this goal through a new project called Improving Recruitment, Engagement, and Access for Community Health Equity for BRAIN Next-Generation Human Neuroimaging Research, or REACH for BRAIN, which is convening an expert working group with community input to fill the guidance gap. Third, the field should learn from the Sex and Gender Equity in Research guidelines, which took three years to develop, were published in 2016, and required years of sustained follow-up, including adoption by the World Health Organization, before achieving widespread implementation. The lesson is that writing guidelines is only the first step. At present, most human neuroscience studies are silent about why race or ethnicity were or were not included and about how those variables were defined. Changing that, the authors argue, would improve interpretability, enable cross-cohort harmonization, and force researchers to confront a scientific history in which purported racial differences in brain structure were used to perpetuate racism, ensuring that modern analytic frameworks do not quietly reintroduce outdated assumptions.

Subject of Research: Ethical and methodological challenges in reporting race and ethnicity population descriptors in human neuroscience research

Article Title: Addressing ethical challenges in the reporting of race and ethnicity population descriptors in human neuroscience research

Article References: Lang, L., Gerold, J., Little, E., McFarland, C., Tawe, B., Jain, R. K., & Shen, F. X. (2026). Addressing ethical challenges in the reporting of race and ethnicity population descriptors in human neuroscience research. Frontiers in Neuroimaging, 5, Article 1744569. https://doi.org/10.3389/fnimg.2026.1744569

Image Credits: AI Generated

DOI: 10.3389/fnimg.2026.1744569

Keywords: neuroscience, neuroimaging, race and ethnicity, population descriptors, journal guidelines, research ethics, health equity, biobanks, reproducibility, genetic ancestry, scientific publishing, population neuroscience

The study, published in BMC Psychiatry by Kimberly Smith, Bohye Kim, Jane Paik Kim and Sripriya Chari, examined records from 3,521,905 US-based adults who received mental health services provided or funded through state mental health agencies in 2018. The data came from the Substance Abuse and Mental Health Services Administration’s Mental Health Client-Level Data Annual Report, a federal dataset that aggregates client-level information from publicly funded mental health programs across the country. Because the dataset is publicly available and fully de-identified, the researchers were able to conduct a secondary analysis without direct contact with human participants, and formal ethics approval and informed consent were not required under institutional standards for such research.

The central question was deceptively simple: among people who are already seeking outpatient mental health care, do rates of diagnosed psychosis differ between Asian individuals and people of other racial groups? This framing matters enormously. Most previous research on racial disparities in psychosis has compared rates across the general population, where differences in service use can mask or distort true differences in illness. By restricting the analysis to a help-seeking sample, the Stanford team attempted to hold constant, at least partially, the enormous barrier that mental health service use represents for many Asian Americans, and to look instead at what happens once people are inside the system.

The comparison group was carefully constructed. The researchers contrasted psychosis diagnoses against what they call DAPS conditions: depression, anxiety, personality disorders and substance use disorders. These four diagnostic categories represent the bulk of outpatient psychiatric practice, and they serve as a benchmark for how frequently different racial groups receive non-psychotic diagnoses once they seek care. Prevalence ratios and odds ratios were calculated to quantify the differences, the standard epidemiological tools for comparing the probability of a diagnosis across groups within a large cross-sectional dataset.

The headline result was that, relative to Asian individuals, the proportion of people with a recorded psychosis diagnosis was 49 percent lower among non-Asian/non-Black individuals, corresponding to a prevalence ratio of 0.51. In other words, within this enormous help-seeking population, Asian clients were roughly twice as likely as clients from other racial groups, excluding Black individuals, to have a psychosis diagnosis on record. Black and African American individuals showed a different pattern: the proportion with a recorded psychosis diagnosis was 6 percent higher than among Asian individuals, a prevalence ratio of 1.06, a modest elevation that the authors characterize as relatively small in magnitude.

The odds ratio analysis added further nuance. Asian Americans had higher odds of having a recorded psychosis diagnosis than non-Asian/non-Black individuals, reinforcing the prevalence findings. Black and African American individuals had modestly higher odds of a recorded psychosis diagnosis than Asian individuals, although the authors emphasize that the size of this difference was small. The results for the DAPS conditions were more varied, with different racial groups showing different patterns across depression, anxiety, personality disorders and substance use diagnoses. This heterogeneity is itself informative, because it suggests that the elevated psychosis signal among Asian help-seekers is not simply a mirror image of lower rates of other diagnoses, but part of a more complicated diagnostic landscape that differs group by group.

Why might Asian individuals who seek mental health care be more likely to carry a psychosis diagnosis? The authors are careful to note that their study represents an initial effort to understand these differential rates, and they frame the identification of culture- and race-specific factors as a crucial direction for future research. Several non-exclusive explanations are consistent with the data. One possibility is a help-seeking selection effect: because stigma surrounding mental illness remains pronounced in many Asian communities, individuals with milder conditions such as depression or anxiety may be far less likely to present to publicly funded services, while those experiencing severe psychotic symptoms may be pushed into care by families regardless of stigma. If the mildest cases never enter the dataset, the proportion of severe cases among those who do enter will appear inflated.

Diagnostic and systemic factors offer additional layers of explanation. Clinicians may interpret symptoms differently across racial and cultural boundaries, and language barriers, culturally specific idioms of distress, and limited access to culturally competent assessment can all shape which diagnosis ends up in the record. Prior research has documented that Black individuals in the United States are disproportionately diagnosed with psychotic disorders relative to mood disorders, a pattern widely attributed to a combination of presentation differences, diagnostic bias and pathways into care, and the modest elevation seen for Black individuals in this study is consistent with that literature. Whether similar mechanisms operate for Asian clients, or whether different ones do, is precisely the kind of question the authors argue future work must disentangle.

The scale of the dataset lends the findings considerable weight, but it also imposes constraints that the authors acknowledge. The Mental Health Client-Level Data capture only people who received services through state mental health agencies, meaning the many Americans who obtain care through private insurance, primary care or never seek care at all are invisible to the analysis. Diagnostic records are recorded by agencies and may vary in accuracy and completeness across states and systems. The cross-sectional design cannot establish whether differences reflect true differences in illness rates, differences in diagnostic practice, or differences in who reaches these particular services. The authors also note that the study used ChatGPT during preparation to improve readability in the introduction and discussion, with the authors reviewing and editing the content and taking full responsibility for the publication.

Even with those caveats, the implications for clinical practice and health policy are significant. If Asian Americans who do reach publicly funded outpatient care carry a heavier burden of psychotic illness than previously appreciated, then early intervention services, culturally tailored outreach and diagnostic vigilance in Asian communities become urgent priorities, rather than afterthoughts. The finding also reframes the familiar narrative of low service use: the problem may not simply be that Asian Americans use fewer services, but that the services they reach are encountering them at later, more severe stages of illness. The authors conclude that future studies aimed at identifying culture- and race-specific factors that impact people seeking mental health services in the United States could be crucial in improving functional outcomes, a research agenda that could ultimately determine whether the country’s largest mental health datasets can be turned into a tool for equity rather than a mirror of its blind spots.

Subject of Research: Racial differences in diagnosed psychosis and other mental disorders among Asian and non-Asian adults seeking US outpatient mental health services

Article Title: Exploring rates of psychosis in Asians and non-Asians seeking outpatient services in the United States

Article References: Smith, K., Kim, B., Kim, J. P., & Chari, S. (2026). Exploring rates of psychosis in Asians and non-Asians seeking outpatient services in the United States. BMC Psychiatry. https://doi.org/10.1186/s12888-026-08432-z

Image Credits: AI Generated

DOI: 10.1186/s12888-026-08432-z

Keywords: psychosis, Asian Americans, mental health services, outpatient care, health disparities, SAMHSA, diagnosis, schizophrenia, race and ethnicity, psychiatric epidemiology, BMC Psychiatry, Stanford University

The research team analyzed data from the Future of Families and Child Wellbeing Study, a landmark longitudinal project that has followed a birth cohort of children born in large U.S. cities between 1998 and 2000, many of them to unmarried parents in economically fragile households. The analytic sample for this study comprised 2,842 adolescents for whom the researchers had complete information on maternal incarceration history and behavioral outcomes measured at age fifteen. Because the Future of Families cohort deliberately oversampled families facing disadvantage, it is uniquely well suited to studying the effects of incarceration, which concentrates heavily in communities already burdened by poverty, residential instability, and limited access to social services. The data are openly available through Princeton University’s Office of Population Research archive, allowing other researchers to scrutinize and extend the findings.

Methodologically, the study operationalized adolescent aggression using established behavioral assessment instruments of the kind long validated in developmental psychology, including parent-reported measures consistent with the Child Behavior Checklist tradition. Maternal incarceration was captured as a reported life event in the child’s history, and the researchers used regression-based modeling — implemented with standard statistical software for structural equation and multivariate analysis — to estimate the association between maternal imprisonment and aggressive behavior while accounting for the dense web of confounding factors that typically co-occur with parental incarceration. These covariates include family socioeconomic status, household structure, parenting quality, neighborhood conditions, and exposure to other adverse childhood experiences. The team then tested whether the association was moderated by two adolescent characteristics: biological sex and race and ethnicity.

The central finding is stark in its simplicity. Adolescents whose mothers had been incarcerated scored higher on measures of aggressive behavior than adolescents who had not experienced maternal imprisonment, even after the models adjusted for the substantial baseline disadvantages these families face. Aggression in this context is not a vague clinical impression but a measurable constellation of externalizing behaviors — fighting, hostility, defiance, and physical acting out — that developmental scientists have repeatedly linked to later delinquency, school exclusion, and contact with the justice system. In other words, the behavior patterns elevated among adolescents of incarcerated mothers are precisely the ones that youth violence prevention programs are designed to interrupt, which is why the authors frame their results as a direct warning to practitioners and policymakers.

Perhaps the most theoretically interesting result concerns what did not differ. The association between maternal incarceration and aggression was statistically comparable for boys and girls. This null finding for sex is notable because much of the earlier literature on parental incarceration, which focused overwhelmingly on fathers, suggested gendered pathways of harm, with boys sometimes appearing more behaviorally reactive and girls more internally distressed. The new results suggest that when the incarcerated parent is the mother, the disruption is severe enough to elevate externalizing problems regardless of the adolescent’s sex. This makes sense from an attachment perspective: mothers are, in the majority of cases, the primary caregivers and the anchors of daily household routines, and their removal destabilizes caregiving arrangements, residential stability, and emotional security in ways that cut across gender lines.

The moderation by race and ethnicity, by contrast, was pronounced. Black adolescents exposed to maternal incarceration showed more adverse behavioral outcomes than their non-Hispanic White and Hispanic counterparts. The authors interpret this heterogeneity through the lens of stress theory — specifically the stress process framework articulated by sociologist Leonard Pearlin — which holds that the impact of any given stressor depends on the resources available to buffer it and on the accumulation of other stressors stacked on top of it. Black families in the United States are disproportionately exposed to concentrated disadvantage, discrimination, and cumulative incarceration-related stigma, and they often have thinner access to the institutional supports that might cushion the shock of a mother’s imprisonment. The finding echoes earlier work by scholars such as Christopher Wildeman and Kristin Turney, who documented that the consequences of the American prison boom are unequally distributed across children of different racial backgrounds.

Several mechanisms plausibly connect a mother’s imprisonment to a teenager’s aggression, and the study situates itself within this established theoretical architecture. Social learning theory, rooted in Albert Bandura’s classic work on the imitation of aggressive models, suggests that children exposed to criminal justice involvement in the home may normalize conflict-laden or coercive behavior. Attachment research indicates that forced separation from a primary caregiver can disrupt the secure base from which adolescents learn to regulate emotion, making impulsive and hostile responses more likely. Stress proliferation research, championed by Turney and colleagues, describes how the strain of incarceration radiates outward from the imprisoned individual to caregivers, siblings, and children, compounding over time. Finally, the stigma of having an incarcerated parent — a burden adolescents often conceal from peers and teachers — can produce social isolation that itself fuels acting out. The study does not adjudicate among these mechanisms, but its pattern of results is consistent with all of them operating simultaneously.

The authors are careful about what their design can and cannot establish. Like all observational research, the study identifies an association rather than a definitive causal effect; mothers who are incarcerated differ from mothers who are not in many ways that no statistical model can fully neutralize, including exposure to violence, substance use, and mental health problems that could independently shape adolescent behavior. The authors also call for future research to disentangle the cultural and social factors that produce the racial heterogeneity they observed — work that would require richer measures of neighborhood context, social support networks, and the subjective experience of stigma. Nonetheless, the consistency of the present findings with a large body of prior evidence, including meta-analyses showing that parental imprisonment predicts children’s antisocial behavior, mental health problems, and drug use, strengthens the case that maternal incarceration is a genuine developmental risk factor rather than a mere statistical artifact.

The policy implications are sobering. The United States imprisons more people than any other nation, and a substantial share of incarcerated women — far more than of incarcerated men — are mothers of minor children, meaning that maternal imprisonment, while less common than paternal imprisonment, may inflict a distinctive form of harm because of mothers’ central caregiving role. The study’s authors argue that youth violence prevention programs should explicitly consider maternal incarceration-related stress and stigma, and should be tailored to the unique risks and needs of subgroups defined by racial background rather than offering one-size-fits-all interventions. School-based programs, mentoring schemes, and family-centered reentry services could all incorporate screening for parental incarceration as a marker of elevated risk. As the researchers conclude, understanding both the overall and the differential effects of maternal imprisonment on adolescent behavior is an essential step toward blunting one of mass incarceration’s most far-reaching intergenerational consequences — and toward ensuring that the children least equipped to absorb the shock are no longer left to absorb it alone.

Subject of Research: The association between maternal incarceration and adolescent aggressive behaviors, including differences by adolescent sex and race/ethnicity

Article Title: Examining the Association Between Maternal Incarceration and Adolescent Aggressive Behaviors with a Focus on Adolescent Sex and Race and Ethnicity

Article References: Zhao, Q., Wu, Y., Sun, I. Y., & Ding, Y. (2026). Examining the Association Between Maternal Incarceration and Adolescent Aggressive Behaviors with a Focus on Adolescent Sex and Race and Ethnicity. Journal of Child and Family Studies. https://doi.org/10.1007/s10826-026-03386-y

Image Credits: AI Generated

DOI: 10.1007/s10826-026-03386-y

Keywords: maternal incarceration, adolescent aggression, externalizing behavior, race and ethnicity, sex differences, Future of Families and Child Wellbeing Study, stress theory, attachment, social learning theory, mass incarceration, youth violence prevention, child development

The stakes of this question are considerable. Disability insurance programs in the United States provide a financial lifeline to millions of workers whose medical conditions prevent them from maintaining substantial employment. An allowance decision can determine whether an individual has access to monthly cash benefits, health insurance coverage through Medicare after a qualifying waiting period, and a measure of economic security during what is often the most vulnerable period of their working life. Because these decisions carry such weight, any systematic difference in how applicants from different racial and ethnic groups fare in the process would raise serious concerns about fairness and equal treatment under the law. That is precisely why researchers have repeatedly examined allowance rates by race and ethnicity, and why unadjusted statistics showing gaps between groups have drawn attention from policymakers and analysts alike.

The methodological approach taken in the study is central to its contribution. Rather than relying on aggregate approval statistics alone, the investigators combined data from the American Community Survey, one of the largest and most detailed ongoing household surveys in the United States, with Social Security administrative records. This linkage allowed the researchers to observe not just whether an applicant was allowed or denied, but a rich set of characteristics describing who that applicant was before the determination was made: their marital status, their health conditions, their earnings history prior to disability, and a range of other demographic and socioeconomic attributes. This kind of linked administrative-survey infrastructure is relatively rare and highly valued in social science research, because it permits analysts to move beyond simple comparisons of group averages and toward a more complete accounting of the factors that actually drive outcomes.

The central analytical question is one that economists describe as a problem of composition versus process. Raw, unadjusted data showed differences in allowance rates across racial and ethnic groups. But a raw gap of that kind can arise in two very different ways. It could indicate that the determination process treats similarly situated applicants differently, which would suggest a disparity within the system. Alternatively, it could reflect the fact that applicants from different groups arrive at the process with different characteristics on average, such as different distributions of impairments, different work histories, different ages, or different household circumstances, and that those differences in applicant composition produce different outcomes even if the process itself is applied uniformly. Distinguishing between these two explanations requires statistical adjustment, and that is exactly what the study provides.

When the researchers accounted for socioeconomic, health, and demographic factors, the picture changed substantially. Most of the observed differences in approval rates became much smaller, and many were no longer statistically distinguishable from zero. In other words, once the researchers compared applicants who were similar in terms of the characteristics that matter for disability determinations, the residual differences associated with race and ethnicity themselves largely disappeared. The authors summarized their finding directly, writing that the differences in allowance rates by race and ethnicity in the raw, unadjusted data are mainly due to compositional differences between groups. This conclusion points away from the determination process as the primary source of the observed gaps and toward the underlying circumstances that shape who applies and with what profile of conditions and resources.

Among the factors the study identifies as associated with allowance outcomes are marital status, health conditions, and pre-disability earnings. Each of these has a plausible connection to how disability claims unfold. Health conditions are, of course, at the heart of any disability determination, since the severity and nature of impairments are what adjudicators assess. Pre-disability earnings matter because they relate to insured status and to the earnings requirements that govern eligibility for disability benefits, as well as to the kinds of work an applicant can realistically be expected to perform in the residual functional capacity framework used in evaluations. Marital status can influence household resources and the support structures available to applicants as they navigate a lengthy and often demanding application process. Differences across racial and ethnic groups in the distributions of these characteristics can therefore translate into differences in approval rates even in the absence of differential treatment within the process itself.

The findings carry important implications for how the raw statistics should be interpreted. A gap in unadjusted allowance rates is often read, in public discussion, as evidence of bias in the system. The study does not support that reading as the primary explanation. At the same time, the results should not be taken to mean that the underlying disparities are unimportant or that no policy concern remains. If applicants from different groups arrive with systematically different health conditions, earnings histories, and household circumstances, those compositional differences themselves reflect broader inequalities in American society, including differences in access to healthcare, in occupational structures, and in economic resources. The study’s contribution is to locate the source of the allowance-rate gaps in these upstream factors rather than in the determination process, which redirects attention toward the social and economic conditions that produce different applicant pools in the first place.

For policymakers, the research offers a more precise map of where intervention might be most effective. If the determination process were the main driver of the gaps, reforms would focus on adjudication standards, training, and oversight of decision-makers. Because the study finds that compositional differences dominate, the more relevant levers may lie in addressing the health and economic disparities that shape disability incidence and application behavior across communities. The findings also illustrate the value of linked administrative data for evaluating social insurance programs. Without the ability to connect survey-based measures of applicant circumstances to actual determination outcomes, analysts would be left with unadjusted statistics that invite misinterpretation. The study demonstrates how such data infrastructure can sharpen the evidence base on which fair and effective policy depends.

The study, published in Contemporary Economic Policy, a journal that has since 1982 provided a forum for scholarly analysis of important policy issues accessible to both economists and policymakers, adds a rigorous and carefully controlled data point to a debate that is often conducted with incomplete evidence. Its central message is methodological as much as substantive: raw differences between groups are not the same as disparities produced by a process, and distinguishing between the two requires data that capture the full circumstances of the people moving through the system. In the case of US disability insurance, the researchers find that when those circumstances are measured and held constant, race and ethnicity themselves largely fall out of the story, leaving marital status, health conditions, and pre-disability earnings as the factors that travel with applicants into the determination process and shape the outcomes they receive.

Subject of Research: Racial and ethnic differences in US disability insurance allowance rates and their socioeconomic and health-related explanations

Article Title: Why are there differences in US disability insurance allowance rates by race and ethnicity?

Article References: Why are there differences in US disability insurance allowance rates by race and ethnicity?. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: disability insurance, Social Security, allowance rates, race and ethnicity, American Community Survey, administrative data, health conditions, pre-disability earnings, marital status, Contemporary Economic Policy, social insurance policy, statistical adjustment

Researchers M. Muchemwa and C. Odimegwu, both based in the Demography and Population Studies Programme at the University of the Witwatersrand, drew on the National Income Dynamics Study, or NIDS, a nationally representative panel survey that has tracked thousands of South Africans across five waves between 2008 and 2017. From a pooled dataset of more than 28,000 male person-wave observations, the authors isolated 718 observations from 636 men who reported making cash contributions to children living outside their households. Because the same men were surveyed repeatedly over nearly a decade, the researchers turned to a statistical technique designed for exactly this kind of repeated-measures data: generalized estimating equations, or GEE.

The methodological choices in the study are worth unpacking, because they shape what the numbers actually mean. Child maintenance payments are continuous monetary amounts that are strongly right-skewed, meaning most men pay modest sums while a few pay very large ones. To model such data, the authors specified a Gamma distribution with a log link function, a combination that ensures predicted payments remain positive and expresses coefficients as multiplicative, or percentage, effects rather than absolute changes in rands. Because repeated observations from the same individual violate the independence assumption underlying ordinary regression, the GEE framework explicitly models the within-person correlation across survey waves. Three candidate correlation structures were compared using the quasi-likelihood under the independence model criterion, and the unstructured structure, which allows the correlation to differ between every pair of waves, produced the lowest QIC value of 14,483.032 and was retained for the final analysis.

The headline result is stark: race, age, occupation and income were all significantly associated with the amount of child maintenance paid, even after controlling for education, employment status, marital status, debt, socioeconomic status, health, religion, province and household size. Indian and White fathers paid significantly more than Black fathers, with a regression coefficient of 1.0542 that was significant at the one percent level and consistent across all three correlation specifications. Age mattered too, with men aged 53 to 57 paying more than younger men aged 18 to 28. And income emerged as a powerful driver: the Gamma model with a log link indicates that every additional 1,000 rand in household net income was associated with roughly a 3.4 percent increase in the amount paid, a coefficient of 0.0000345 that held at the one percent significance level.

One counterintuitive finding deserves attention. Men in unskilled occupations paid an estimated 44.8 percent more than men with no occupation at all, after adjusting for other characteristics. This suggests that having any foothold in the labour market, even at the lowest rung, enables financial contribution in a way that complete joblessness does not. It also hints at the psychological dimension of the provider role: men in work may feel a stronger sense of obligation and capability, while unemployed fathers, unable to meet deeply entrenched social expectations of provision, may withdraw altogether. Previous South African research has documented how feelings of failure and emasculation push men away from their children, and how mothers or maternal families sometimes deny fathers access when they cannot provide material support.

The racial pattern in the data cannot be divorced from South Africa’s history. The authors interpret their findings through the father involvement framework first proposed by Michael Lamb and colleagues in 1985, which decomposes fatherhood into three dimensions: interaction, availability and responsibility. Child maintenance payments serve here as an observable indicator of the responsibility dimension, the father’s role in ensuring that the child’s needs are met. Within this framework, the racial gap in payments reflects structural inequalities that constrain some fathers’ capacity to enact financial responsibility. Black fathers in South Africa remain disproportionately affected by unemployment, labour migration and economic marginalisation, legacies that limit both their financial capacity and their ability to maintain consistent involvement in their children’s lives. Yet the authors are careful to note that money is not the whole story: even wealthy Black fathers have faced legal action for non-payment, indicating that willingness, relational dynamics and enforcement all shape behaviour independently of capacity.

The age gradient tells a complementary story about life stage. Older men are more likely to have accumulated resources, achieved employment stability and internalised the social expectations attached to responsible fatherhood, enabling them to fulfil the responsibility dimension of involvement. Younger men, still transitioning into stable economic and social roles, may lack both the means and the readiness to assume this responsibility. Comparable findings from Finland, where a register-based study showed older parents paying higher maintenance amounts even after adjusting for income, suggest the pattern is not unique to South Africa but reflects a broader developmental logic of paternal responsibility.

The study’s technical rigour is matched by an unusually candid discussion of its limitations. The NIDS Contributions Given module does not distinguish between court-ordered formal maintenance and informal, non-regulated support, so the analysis captures all reported financial transfers to children rather than legal compliance specifically. More importantly, respondents who reported no contribution to anyone outside their household were never asked about non-resident children, making it impossible to identify fathers who should pay but do not. The analysis therefore describes the payment amounts among observed contributors, not the probability of paying. The sample was also unbalanced, with 559 men contributing a single observation, 72 contributing two and only five contributing three, and the racial comparison rests on just 23 Indian or White respondents against 620 African respondents, limiting the precision of that comparison. A sensitivity analysis using an inverse hyperbolic sine transformation, which allowed five zero-payment observations to be retained, confirmed the robustness of the positive associations for race, income, age and survey year.

What emerges from this study is a picture of child maintenance in South Africa as a dynamic, evolving behaviour rather than a static obligation. Payments were significantly higher in 2012, 2015 and 2017 than in the 2008 baseline wave, suggesting that financial contributions have grown over time even as the underlying inequalities persist. The policy implications are concrete: the authors call for programmes that improve employment opportunities, awareness campaigns that emphasise the importance of fathers’ financial contributions, and community-based fatherhood initiatives, including counselling and parenting workshops, that engage absent fathers and address the cultural and economic barriers that keep them from supporting their children. With evidence that only 40.5 percent of children with living fathers receive financial support from them, the stakes of translating these statistical insights into action could hardly be higher, both for the millions of children whose wellbeing depends on paternal support and for a society still reckoning with the structural forces that shape who gets to be a provider.

Subject of Research: Demographic and socioeconomic determinants of child maintenance payments among men in South Africa

Article Title: Demographic and socioeconomic characteristics of men paying child maintenance in South Africa: a generalized estimating equation approach

Article References: Muchemwa, M., & Odimegwu, C. (2026). Demographic and socioeconomic characteristics of men paying child maintenance in South Africa: a generalized estimating equation approach. SN Social Sciences, 6(10), Article 480. https://doi.org/10.1007/s43545-026-01739-4

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01739-4

Keywords: child maintenance, child support, fatherhood, South Africa, National Income Dynamics Study, generalized estimating equations, longitudinal analysis, father absence, income inequality, race and ethnicity, social policy, demography

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: Sarlin, S. K., Lim, H., Li, X., Liu, Y., & Thrift, A. P. (2026). Temporal changes in sex and race/ethnicity incidence rate ratios for hepatocellular carcinoma in the United States, 1992–2022. Cancer Causes & Control, 37(9), Article 153. 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: Amaral, E. F. L., & Ortiz Osejo de Lemus, N. Y. (2026). Internal migration, demographic heterogeneity, and spatial patterns in the United States. Journal of Population Research, 43(3), Article 27. 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