The study, led by Emily L. Podany and Andrew A. Davis of Washington University in St. Louis together with collaborators at Weill Cornell Medicine, Northwestern University, and Massachusetts General Hospital, drew on clinical and genomic data collected between 2015 and 2024. All patients had metastatic breast cancer and had undergone liquid biopsy testing with the Guardant360 assay, which detects mutations, copy number changes, and gene fusions across dozens of cancer-related genes from a simple blood sample. To quantify neighborhood disadvantage, the team used the Area Deprivation Index, or ADI, a validated composite of seventeen measures including poverty, employment, and education, ranked nationally from 1 to 100 by nine-digit zip code. Patients scoring 60 or above were classified as living in high deprivation neighborhoods.

Of the 1,127 patients analyzed, 335, or 29.7 percent, lived in high deprivation areas. Black patients were more than three times as likely as White patients to reside in these neighborhoods, reflecting the deep entanglement of race and socioeconomic disadvantage in the United States. After adjusting for age, race, cancer subtype, sites of metastatic disease, treatment line, and other clinical variables, the researchers found that patients from high deprivation neighborhoods had roughly 49 percent higher odds of harboring TP53 mutations in their tumors. Conversely, they were significantly less likely to carry AKT1 mutations, an alteration typically enriched in slower-growing, lower-grade luminal tumors.

The TP53 gene encodes p53, often described as the guardian of the genome. In healthy cells, this tumor suppressor protein halts division when DNA is damaged, triggers repair mechanisms, and pushes irreparably damaged cells into programmed death. When TP53 is mutated, that safety net collapses, allowing abnormal cells to proliferate unchecked. Mutations in the gene appear in roughly 30 percent of breast cancers and are linked to higher tumor grade, more aggressive subtypes, and worse prognosis. The new findings echo earlier tissue-based studies that connected household income and socioeconomic deprivation to higher p53 mutation frequency, but they extend that evidence to a large, racially diverse cohort of metastatic patients using blood-based genomic profiling.

Intriguingly, patients in high deprivation neighborhoods were less likely to present with visceral, lymph node, or soft tissue metastases, which might ordinarily suggest less advanced disease. Yet their survival was shorter. The authors propose that TP53-mutated tumors may drive rapid, aggressive progression even at lower disease burden, potentially before the kind of metastatic crises that prompt urgent intervention. They also point to the compounding weight of social determinants of health: patients in deprived neighborhoods experience higher rates of food insecurity, sarcopenia, and chronic disease, all of which erode the physical resilience needed to tolerate intensive cancer treatment.

The study also uncovered a stark treatment gap. Among 136 patients with hormone receptor-positive, HER2-negative metastatic disease who carried activating PIK3CA mutations and were therefore eligible for PI3K inhibitor therapy, only 17.4 percent of those in high deprivation neighborhoods actually received the drugs, compared with 36.7 percent of patients in low deprivation areas. This disparity emerged despite equal rates of PIK3CA mutations across deprivation groups, meaning the biological eligibility for targeted therapy was the same. The gap points squarely at access, not biology, as the limiting factor.

PI3K inhibitors such as alpelisib, approved by the Food and Drug Administration in 2019, and related AKT pathway inhibitors such as capivasertib represent some of the most consequential advances in precision oncology for breast cancer. But these therapies are expensive, require genomic testing to identify eligible mutations, and are often available primarily at academic cancer centers concentrated in affluent regions. Prior research has shown that patients from disadvantaged neighborhoods travel longer distances for care, are less likely to enroll in clinical trials, more often lack private insurance, and experience longer treatment delays and higher rates of therapy discontinuation. The new data suggest these structural barriers now extend into the era of molecularly targeted medicine.

Survival differences were perhaps the most sobering result. Median overall survival from the time of circulating tumor DNA testing was 24 months for patients in high deprivation neighborhoods versus 28 months for those in low deprivation areas, a statistically significant difference. When the researchers stratified by race, the picture became even more stark: Black patients in high deprivation neighborhoods survived a median of just 15 months, compared with 25 months for Black patients in low deprivation areas and 28 months for White patients regardless of neighborhood. Notably, Black patients living in advantaged neighborhoods fared as well as White patients, indicating that neighborhood deprivation and race interact to produce the worst outcomes rather than race acting alone.

The authors caution that the study has limitations. All patients were treated at large academic medical centers, so the findings may not generalize to community hospitals or rural clinics. The Area Deprivation Index has been criticized for overemphasizing housing values, and a single time-point measure cannot capture the cumulative environmental exposures involved in carcinogenesis, which unfolds over years or decades. Because the analysis was exploratory, no correction for multiple statistical testing was applied. Still, the cohort’s geographic breadth, spanning catchment areas across multiple states, and its use of individual-level chart review and uniform genomic testing lend considerable strength to the conclusions.

The implications reach beyond oncology. If living in a deprived neighborhood is associated with a distinct mutational landscape in metastatic tumors, then environmental stressors, chronic inflammation, and social adversity may be biologically embedded in cancer in ways that precision medicine alone cannot undo. The research team calls for laboratory studies of environmental exposures, epidemiological work on molecular subtypes by deprivation, and implementation science aimed at dismantling barriers to targeted therapy access. The team also plans structured patient interviews to understand precisely why eligible patients in high deprivation areas miss out on PI3K inhibitors. In the meantime, the study stands as a molecular argument that zip code should not determine tumor biology, treatment, or survival, and that closing the gap will require intervening on the neighborhoods themselves, not just the cancers within them.

Subject of Research: Associations between neighborhood deprivation and breast cancer tumor genomics, targeted treatment use, and survival in metastatic breast cancer patients

Article Title: Associations of neighborhood deprivation with breast cancer tumor genomics, targeted treatment use, and survival

Article References: Podany, E. L., Foffano, L., Gerratana, L., Medford, A. J., Heater, N. K., Nicolò, E., Tapiavala, S., Pontolillo, L., Putur, A., Jaber, D. A., Clifton, K., Katakam, N., Addison, S., Lipsyc-Sharf, M., Reduzzi, C., Ademuyiwa, F. O., Puglisi, F., Gradishar, W. J., Ma, C. X., … Davis, A. A. (2026). Associations of neighborhood deprivation with breast cancer tumor genomics, targeted treatment use, and survival. Breast Cancer Research and Treatment, 219(2), Article 5. https://doi.org/10.1007/s10549-026-08068-3

Image Credits: AI Generated

DOI: 10.1007/s10549-026-08068-3

Keywords: breast cancer, neighborhood deprivation, Area Deprivation Index, TP53, circulating tumor DNA, PI3K inhibitors, health disparities, precision oncology, metastatic breast cancer, survival, social determinants of health, liquid biopsy

The research team, led by Tetsuji Minami of the National Cancer Center Japan alongside collaborators from several Japanese institutions, broke the 8.6 percent figure into distinct categories: 4.9 percent identified as gay or lesbian, 1.1 percent as bisexual, 1.0 percent as asexual or unsure of their attraction, and 1.6 percent as gender-diverse, meaning their current gender identity did not match the sex assigned to them at birth or fell outside the binary altogether. These estimates align with the 7.0 to 16.8 percent range reported in earlier Japanese studies conducted by private companies, government agencies, and sociologists, but earlier efforts suffered from convenience sampling, inadequate statistical adjustment, and narrow cohorts that limited their generalizability. By contrast, the new study calibrated its web-based sample against the Japanese government’s 2019 Comprehensive Survey of Living Conditions using a statistically demanding technique called inverse probability weighting.

The technical machinery behind the estimates deserves attention because it addresses a well-known weakness of internet surveys. Participants were drawn from a panel of 2.3 million people managed by Rakuten Insight, with stratified multistage sampling by age and sex, and a response rate of 65.7 percent among those invited. The researchers then applied two pre-set algorithms to screen out inattentive respondents, or “satisficers,” who straight-line their answers or fail directed attention checks, removing 9 percent of the raw sample. Sampling weights were predicted from a logistic regression model comparing the web survey respondents with the census-calibrated national survey, adjusting for area of residence, marital status, education, housing tenure, self-rated health, and smoking status. The resulting inverse probability weights allowed the team to produce population-level estimates with 95 percent confidence intervals, computed with a robust variance estimator, treating the findings explicitly as weighted distributions rather than causal effects, in line with modern descriptive epidemiology frameworks.

Measurement of sexual orientation and gender identity followed the internationally recommended “two-step approach,” which asks separately about sex assigned at birth and current gender identity, supplemented by a romantic and sexual attraction item to classify sexual orientation among cisgender respondents. Gender-diverse respondents were deliberately not reclassified by sexual orientation, and the authors caution that the gender-diverse category aggregates heterogeneous subgroups, including transgender, non-binary, and questioning individuals, because the survey instrument could not capture finer self-descriptions. Similarly, respondents who selected neither or unsure on the attraction item were grouped under an inclusive “asexual cisgender or unsure” label, an operationalization the authors urge readers to interpret cautiously since it may blend true asexuality with ongoing questioning. Inattentive respondents who reported anything other than male or female for assigned sex at birth were excluded as quality controls, consistent with Japan’s family register system, and were not intended to exclude minority identities.

Beyond headline prevalence, the study mapped striking demographic and socioeconomic patterns. All sexual and gender minority groups were younger on average than heterosexual respondents, with mean ages of 44.7 years for gay and lesbian participants, 38.3 for bisexual, 40.0 for asexual, and 38.4 for gender-diverse respondents, compared with 48.8 for heterosexual participants, and prevalence was concentrated under age 30. Gay respondents were more often male, while bisexual and asexual respondents were more often female, and gender-diverse respondents were evenly split by assigned sex. Marriage and partnership rates told a more complex story: only 47.7 percent of gay and lesbian respondents and 38.1 percent of gender-diverse respondents were married or partnered, versus 65.1 percent of heterosexual respondents, and a substantial share of gay and lesbian participants reported opposite-sex marriages or partnerships, a pattern the authors link to Confucian family norms emphasizing marriage and procreation, the absence of legal same-sex marriage recognition, and structural stigma.

Socioeconomic disparities emerged with unusual clarity because the national calibration allowed income, education, employment, insurance, and housing comparisons. Lower household equivalent income was more common among minority groups, particularly male sexual minorities and female gender-diverse respondents, and women had lower incomes than men within every category. Educational attainment diverged sharply from Western patterns: whereas studies in the United States and Europe generally find gay and bisexual men more educated than heterosexual men, Japanese gay, lesbian, and bisexual male respondents showed the opposite trend, with heterosexual men most likely to hold degrees. Employment differences also inverted expectations in places, with female sexual minorities more likely to be employed than heterosexual women, plausibly because married Japanese women are often outside the labor force while minority women marry less often. Health insurance coverage was lower among minority respondents of both sexes, and housing tenure varied significantly only among men, with asexual men and lesbian women least likely to own homes.

Health indicators painted a mixed picture that partially contradicts Western literature. Psychological distress, measured with the Kessler-6 scale, was consistently more common among minority respondents of both assigned sexes, echoing minority stress theory, which holds that stigma and marginalization drive mental health disparities. Body mass index patterns were also distinctive: underweight was more common among female minority respondents, while overweight and obesity clustered among male bisexual and asexual respondents and female asexual respondents. Perhaps most surprising, current smoking and habitual drinking showed limited or reversed differences, with minority groups tending to drink less than heterosexual respondents, contrary to consistent findings from England, Canada, and the United States. Substance use other than tobacco and alcohol was higher among minority respondents but remained rare overall. Medical comorbidity did not differ significantly once results were stratified by assigned sex at birth, and self-rated health differences disappeared under stratification, prompting the authors to call for future studies with covariate adjustment and clinical data linkage.

The significance of these findings extends well beyond Japanese borders. Until now, virtually all nationally representative data on sexual and gender minority populations came from Western countries, including the United States, the Netherlands, Sweden, Portugal, Canada, and the United Kingdom, creating a geographic evidence gap the authors argue reflects both research neglect and, in parts of Asia, legal environments where same-sex acts remain criminalized. Japan presents a distinctive hybrid context: same-sex relationships were historically tolerated within certain cultural traditions, cross-national analyses suggest relatively low structural stigma and low non-disclosure, yet Japan remains the only G7 nation without comprehensive anti-discrimination legislation or marriage equality. The study’s documentation of opposite-sex marriages among gay and lesbian respondents, observed at levels between the low Western figures of 3 to 9 percent and the much higher Chinese figures of 33 to 51 percent, offers rare quantitative grounding for understanding how family norms and legal structures shape minority lives in East Asian settings.

The authors draw direct policy implications from their data. They recommend that national administrative surveys routinely incorporate sexual orientation and gender identity items and household modules that recognize diverse partnership structures, enabling ongoing surveillance of socioeconomic disparities and targeted resource allocation. They call for accessible mental health support and anti-discrimination efforts in schools and workplaces to reduce the psychological burden the Kessler-6 results document, and for longitudinal and panel designs that oversample small subgroups and analyze intersections of age and assigned sex. Acknowledging limitations, including self-reported data, potential social desirability bias, residual web-survey selection bias that weighting could reduce but not eliminate, and the coarse aggregation of gender-diverse subgroups, the team nevertheless positions the work as a foundational step. With an estimated 8.6 percent of Japan’s population identifying as a sexual or gender minority, the study transforms a population previously invisible in national statistics into a measurable, monitorable constituency whose health and socioeconomic well-being can now be tracked, compared, and protected.

Subject of Research: National estimation of the proportion and characteristics of sexual and gender minorities in Japan using a nationwide cross-sectional internet survey

Article Title: Estimation of Sexual and Gender Diversity Among People Aged 15 Years and Older in Japan: A Descriptive Epidemiological Study Using a Nationwide Cross-Sectional Internet Survey

Article References: Minami, T., Inoue, M., Matsushima, M., Yoshioka, T., & Tabuchi, T. (2026). Estimation of Sexual and Gender Diversity Among People Aged 15 Years and Older in Japan: A Descriptive Epidemiological Study Using a Nationwide Cross-Sectional Internet Survey. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-026-03515-0

Image Credits: AI Generated

DOI: 10.1007/s10508-026-03515-0

Keywords: sexual orientation, gender identity, sexual and gender minorities, Japan, descriptive epidemiology, national survey, LGBTQ, health disparities, minority stress, inverse probability weighting, bisexual, transgender

The study, led by Robina Josiah Willock of Morehouse School of Medicine together with colleagues at Wayne State University, analyzed responses from 2,745 female breast cancer survivors who participated in the National Health Interview Survey between 2019 and 2022. After excluding surveys missing more than fifteen percent of key variables, the final analytic sample comprised 2,553 women, of whom 411, or 16.1 percent, reported a physician-confirmed cardiovascular diagnosis. The conditions counted were non-fatal stroke, non-fatal myocardial infarction, and coronary artery disease, the three major cardiovascular events tracked consistently in the survey.

The central exposure of interest was the poverty-to-income ratio, or PIR, a measure calculated by dividing household income by the federal poverty threshold for a family of a given size and composition. Rather than treating income as a simple linear variable, the researchers divided it into four tiers that roughly align with policy-relevant thresholds: PIR at or below 1.49, 1.50 to 2.49, 2.50 to 3.99, and 4 or higher. These cut points approximate the income boundaries governing Medicaid expansion eligibility, Affordable Care Act Marketplace cost-sharing subsidies, and premium tax credits during the study period, making the categories directly meaningful for understanding who can and cannot afford consistent insurance coverage and care.

Methodologically, the team employed inverse probability of treatment weighting, or IPTW, in their logistic regression models, a technique that balances observed covariates across income groups more effectively than standard adjustment and reduces confounding in observational data. All estimates were weighted using the NHIS final annual sample weight, with variance estimation accounting for the survey’s complex clustering and stratification. The researchers also ran sensitivity analyses disaggregating the composite cardiovascular outcome into its individual components, and these largely confirmed a robust socioeconomic gradient: for myocardial infarction, women in the lowest income tier faced more than three times the odds of disease compared with the mid-high income tier, and for stroke more than double the odds, while the strongest protective contrast between the highest and lowest income groups yielded odds ratios of 0.26 for heart attack and 0.29 for stroke.

The headline result, however, lies in the interaction analyses. Higher income did not confer equal protection across racial and ethnic groups. The interaction between PIR and race and ethnicity was highly significant, with a p-value below 0.0001. Among Black breast cancer survivors, reaching the highest income tier reduced the odds of cardiovascular disease by 92 percent compared with the lowest tier, a striking odds ratio of 0.08. Among White survivors, the equivalent protection was a still-substantial but smaller 68 percent reduction. Among Asian survivors and those in other racial and ethnic categories, no significant association between income and cardiovascular disease emerged at any comparison, a pattern the authors attribute either to genuinely different income-health dynamics or to the instability of estimates drawn from small sample sizes in the survey.

Age told a parallel story of moderated protection. The interaction between income and age was significant at p equal to 0.017, with the strongest benefits concentrated among survivors younger than 65. In this pre-Medicare group, the highest income tier cut the odds of cardiovascular disease by 91 percent relative to the lowest tier. Among survivors aged 65 to 84, the protective gradient weakened, with only the broadest income contrasts reaching significance, and among those 85 and older the effect largely vanished except for a 56 percent reduction at the highest versus lowest income comparison. The authors suggest that Medicare and other age-linked social programs may buffer the economic circumstances of older survivors, flattening the health consequences of low income in ways that younger, uninsured, or underinsured women cannot access.

Survivorship duration and care-seeking behavior added further texture. Although the overall interaction between income and years since diagnosis was not statistically significant, strong patterns appeared at both ends of the trajectory: among women one to four years past diagnosis, the highest income tier reduced cardiovascular odds by roughly 80 percent, and among long-term survivors more than ten years out, significant protections of 38 to 61 percent persisted. Notably, the persistence of cardiovascular risk and income gradients more than a decade after diagnosis challenges the conventional survivorship model, in which surveillance typically tapers after the five-year mark. Meanwhile, the interaction between income and delayed medical care approached significance at p equal to 0.058, with women who reported no delays in follow-up showing consistent income protection across all tiers, while among those who delayed care only the very highest income group showed a significant benefit.

The biological and structural backdrop makes these findings consequential. Breast cancer therapies, particularly radiotherapy and anthracycline chemotherapy, are known to cause acute cardiotoxicity and to seed subclinical cardiac injury that manifests years later; one landmark 25-year follow-up study cited in the paper reported a 1.7-fold increase in cardiovascular mortality among irradiated patients. As survival rates climb, with the current five-year breast cancer survival standing at 91 percent and more than 4.9 million survivors projected in the United States by 2030, cardiovascular disease has become a predominant non-cancer cause of death in this population. Women of lower socioeconomic status enter survivorship with higher burdens of hypertension, diabetes, obesity, and smoking, are more often diagnosed at advanced stages requiring more cardiotoxic regimens, and are more exposed to financial toxicity, the economic fallout of diagnosis that disproportionately harms racial and ethnic minority women even after adjusting for baseline income and education.

The authors are candid about the limitations inherent in their design. All diagnoses were self-reported, introducing potential recall bias, and validation studies suggest self-reported stroke and heart attack are reasonably accurate while angina and coronary artery disease are less so. The cross-sectional design precludes any inference of causality or temporality, breast cancer stage and treatment details were unavailable for adjustment, and the predominantly non-Hispanic White sample limits generalizability, potentially underrepresenting women with advanced disease who died early. Nonetheless, the consistency of the income gradient across composite and individual outcomes, and the strength of the moderation by race and age, lend weight to the central claim: economic status functions as an independent and modifiable risk marker for cardiovascular disease in breast cancer survivors.

The practical implications are pointed. The authors argue that clinical cardiovascular risk models for breast cancer patients remain underspecified when they omit economic status, and they call for embedding longitudinal economic screening into survivorship care plans alongside traditional cardiovascular surveillance. They further propose extending cardiovascular prevention guidance beyond the current five-year threshold, expanding means-tested supports such as Medicaid expansion, subsidized supplemental coverage, and caps on out-of-pocket cardio-oncology costs toward younger survivors, and testing through comparative effectiveness trials whether routine screening of lower-income survivors improves outcomes. As the survivor population swells, the study suggests that protecting their hearts will require protecting their finances first, and that the size of that protection depends profoundly on who the survivor is.

Subject of Research: Socioeconomic and racial disparities in cardiovascular disease risk among female breast cancer survivors in the United States.

Article Title: Income, race, and cardiovascular disease in female breast cancer survivors: evidence of moderated socioeconomic protection in the National Health Interview Survey (NHIS) 2019–2022

Article References: Josiah Willock, R., Parks, D., Nabi, S., Rivers, B., Rivers, D., Li, C., & Levy, P. (2026). Income, race, and cardiovascular disease in female breast cancer survivors: evidence of moderated socioeconomic protection in the National Health Interview Survey (NHIS) 2019–2022. Journal of Cancer Survivorship. https://doi.org/10.1007/s11764-026-02112-3

Image Credits: AI Generated

DOI: 10.1007/s11764-026-02112-3

Keywords: breast cancer survivors, cardiovascular disease, poverty-to-income ratio, health disparities, social determinants of health, National Health Interview Survey, financial toxicity, cardiotoxicity, cancer survivorship, racial disparities, Medicare, survivorship care

The New Innovator Award occupies a distinctive niche in the NIH funding landscape. Rather than requiring preliminary data or a conventional track record, the program seeks out scientists whose ideas are considered transformative precisely because they depart from established approaches. Daniela Friedman, the Arnold School’s associate dean for research and leadership development, described the recognition as extremely well deserved, noting that since joining the school Shi has built an outstanding research program and distinguished herself as an innovative investigator whose work has the potential to reshape her field. For a researcher who has been on the faculty for only a short time, the award signals both the ambition of the science and the confidence the institute has placed in it.

Shi’s path to this project began far from South Carolina. She studied preventive medicine at Shanghai Jiao Tong University in China, where her involvement in tobacco control and other public health research projects led her to a realization that would define her career: improving health requires addressing not only diseases themselves but also the social and behavioral factors that shape how people live. That conviction deepened during an intervention project for people living with HIV in China. Although antiretroviral therapy has transformed HIV from a fatal diagnosis into a manageable chronic condition, Shi observed firsthand how many patients continued to struggle with stigma, fear of disclosure, and discrimination. Even individuals who were effectively controlling the virus medically tended to isolate themselves from family and friends, a pattern that convinced her that biomedical advances alone are not enough and that social and structural barriers must be confronted alongside them.

That experience brought her to the Arnold School, where she enrolled in the doctoral program in health promotion, education, and behavior and later completed a postdoctoral fellowship with the department and the South Carolina SmartState Center for Healthcare Quality. During that period she worked closely with faculty members Xiaoming Li and Xueying Yang, whom she credits as exceptional mentors who encouraged her to ask meaningful research questions, think creatively, and pursue innovative approaches that combine big data and artificial intelligence to advance HIV prevention and care. She has said their guidance was instrumental in her development as an independent researcher, fostering an environment of collaboration, curiosity, and innovation while emphasizing that research should ultimately improve people’s lives. It is also the community she built there, she explains, that drew her to remain at the Arnold School as a faculty member.

The new project brings together the threads of that training into a single, data-intensive research program. Shi and her team will draw on the NIH’s All of Us Research Program, one of the largest and most diverse health data resources ever assembled, which offers researchers access to longitudinal health information from hundreds of thousands of participants across the United States. Using advanced computational techniques, including machine-learning tools, the team will analyze how patterns of sexually transmitted infections relate to HIV risk and to HIV treatment outcomes over time. The analytical challenge is considerable: STI diagnoses arrive in clinical systems as scattered events, and connecting them to downstream HIV outcomes requires models that can capture multilevel social, structural, and clinical determinants of health simultaneously.

The scientific rationale for the project rests on a well-documented but underexploited relationship. Sexually transmitted infections are known to biologically increase the risk of acquiring HIV, and they may also signal lapses in engagement with HIV care among people already living with the virus. Yet, as Shi points out, STI data remains markedly underutilized by healthcare systems and researchers when it comes to predicting who may be at higher risk of HIV infection or adverse HIV-related health outcomes. In most clinical settings, an STI diagnosis is treated as a discrete event to be treated and closed, rather than as a signal that could trigger risk stratification, intensified prevention counseling, pre-exposure prophylaxis evaluation, or re-engagement efforts. Her project aims to close that gap by turning routinely collected clinical data into actionable predictive insight.

The stakes of better prediction are substantial. Of the roughly 1.1 million Americans living with HIV, an estimated 13 percent are unaware of their status, 25 percent do not receive care, and 35 percent are not virally suppressed. Each of those gaps represents a point at which the care continuum fails both the individual and public health, since unsuppressed viral load sustains transmission risk while untreated infection progresses. The extraordinary advances of the past three decades in HIV treatment, including reduced transmission achieved through careful management and modern prevention measures, mean that these numbers do not have to be what they are. What is missing, Shi argues, is a systematic way for clinicians to identify which patients need additional support and when. Her findings are intended to help clinicians do exactly that, and to give other scientists and healthcare providers a foundation for developing more effective strategies for HIV prevention and care.

Technically, the project sits at the intersection of infectious disease epidemiology, behavioral science, and data science. By training machine-learning models on the rich, longitudinal All of Us dataset, the team hopes to detect combinations of STI histories, demographic characteristics, social determinants, and clinical indicators that reliably precede HIV acquisition or poor treatment outcomes. Such models, if validated, could eventually be embedded in electronic health record systems as risk-stratification tools, flagging patients who warrant proactive outreach. The guidelines Shi’s team plans to develop for healthcare providers will translate these statistical findings into concrete clinical workflows, addressing the persistent divide between what population data can reveal and what individual practitioners can act upon during a routine visit.

Beyond its immediate clinical aims, the project reflects a broader vision of prevention that Shi has carried since her early days in preventive medicine: one in which social context, stigma, and structural barriers are treated as measurable, modifiable components of risk rather than as background noise. Her own trajectory, from studying preventive medicine in China to leading federally funded research at a major American research university, is one she hopes will encourage other early-career researchers and international scholars to pursue ambitious ideas with the potential for meaningful public health impact. The award, by its design, rewards exactly that kind of trajectory, betting on investigators whose careers are just taking shape and whose questions are still unconventional.

Looking ahead, Shi describes the Arnold School and the Center for Healthcare Quality as a unique environment where expertise in public health, clinical research, and data science converge. She intends to use the New Innovator Award to build an independent research program that leverages large-scale data and artificial intelligence to improve HIV prevention and care, while eventually extending her methods to other infectious diseases and health disparities. She also plans to invest in the next generation of the field, mentoring students and collaborating across disciplines to translate research findings into real-world impact. For a scientist whose formative insight was that data alone is never enough, the project she has now begun represents an attempt to prove the converse as well: that when large-scale data is joined to an understanding of human behavior and social barriers, prediction can become prevention.

Subject of Research: Use of large-scale health data and artificial intelligence to identify sexually transmitted infection patterns that predict HIV infection risk and treatment outcomes in at-risk populations

Article Title: New faculty member Fanghui Shi awarded NIH grant to protect at-risk populations from contracting HIV

Article References: New faculty member Fanghui Shi awarded NIH grant to protect at-risk populations from contracting HIV. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: HIV, NIH Director's New Innovator Award, Fanghui Shi, sexually transmitted infections, machine learning, All of Us Research Program, HIV prevention, public health, health disparities, University of South Carolina, Arnold School of Public Health, data science

The core problem is deceptively simple. Fortification works by adding essential micronutrients, such as iron, zinc, vitamin A, folic acid, iodine and B vitamins, to staple foods and condiments that populations already consume regularly. Salt iodisation, the fortification of wheat and maize flour, and the enrichment of edible oils and sugar have collectively prevented countless cases of goitre, neural tube defects, anaemia and blindness. The World Health Organization and the Food and Agriculture Organization codified the technical principles of this approach in their landmark 2006 guidelines on food fortification with micronutrients, which emphasize that a food vehicle must be consumed in sufficient and relatively consistent quantities by the target population before it can serve as an effective delivery channel for added nutrients.

That consumption requirement is precisely where many programmes stumble, particularly in low- and middle-income countries where the burden of micronutrient deficiency is concentrated. National fortification programmes tend to focus on a narrow set of vehicles, most commonly wheat flour, maize flour, salt, oil and sugar, because these are centrally processed foods that manufacturers can fortify at scale under regulatory oversight. The Global Fortification Data Exchange documents that the majority of countries with fortification standards have legislated programmes built around these few staples. But dietary patterns are not uniform within or between countries. Rural households may mill their own grain outside industrial channels, urban consumers may shift toward imported or processed foods, and the poorest families may consume very little of the fortified staples at all, relying instead on other foods that never pass through a fortification facility.

The new research highlighted in the commentary takes a systemic approach to this mismatch. Using publicly available household consumption and expenditure data from ten West African countries, the study maps which foods are eaten in sufficient quantities by which population groups, and cross-references those patterns with estimates of micronutrient intake and deficiency risk. The findings are striking: to reach the populations most at risk of micronutrient deficiencies, a wider mix of fortified foods than is currently considered for fortification would be needed. In other words, the standard portfolio of flour, oil, salt and sugar is insufficient to deliver adequate micronutrients equitably across diverse West African populations, because different wealth strata, regions and demographic groups obtain their calories and nutrients from substantially different baskets of foods.

This equity lens represents a significant shift in how fortification success is measured. Traditional programme evaluations often report national-level coverage, the percentage of households consuming any fortified food, or the technical quality of fortification at the factory level. Those metrics can look impressive on paper while masking deep disparities in who actually benefits. A programme may achieve high nominal coverage of fortified wheat flour while the poorest quintile, rural children and women of reproductive age, the groups most vulnerable to anaemia and other deficiency conditions, consume negligible amounts of the fortified product. When coverage is assessed against need rather than against consumption of any fortified food, the gaps become stark, and the case for expanding and diversifying the range of fortified vehicles becomes compelling.

The implications for programme design are far-reaching. First, the analysis underscores the value of leveraging the growing volume of publicly available dietary survey data to inform fortification policy. Household consumption and expenditure surveys, national demographic and health surveys, and dedicated dietary intake assessments collectively contain the raw material needed to identify which foods each population subgroup consumes in fortification-relevant quantities. Governments and their partners can use such data to move beyond one-size-fits-all vehicle selection and toward portfolios tailored to national and subnational dietary realities. This data-driven framework offers a replicable template that other regions with high burdens of hidden hunger could adapt, provided comparable survey data are available and kept current.

Second, the findings suggest that programme planners should consider fortifying a broader array of foods, including foods consumed by lower-income and rural households that traditional programmes have overlooked. Candidate vehicles might include additional cereals, legume flours, condiments such as bouillon cubes, and other centrally processed or semi-processed products that feature prominently in local diets. Expanding the vehicle mix is not without challenges: each new fortified food requires feasibility assessment, industrial capacity, regulatory standards, quality assurance systems, monitoring and consumer acceptance. But the cost of leaving the most vulnerable populations unserved is measured in preventable childhood mortality, impaired cognitive development, reduced adult productivity and intergenerational cycles of malnutrition, costs that dwarfs the marginal expense of extending fortification to additional foods.

The broader context reinforces the urgency. Recent global assessments of micronutrient intake, including work by Osendarp and colleagues published in the Food and Nutrition Bulletin, have documented the scale of inadequate vitamin and mineral consumption across low- and middle-income countries, while companion analyses by Friesen and colleagues in The Lancet Global Health have examined the reach and quality of existing large-scale fortification programmes. Together with the new West African modeling work led by Tang and colleagues in Nature Food, these studies sketch a consistent picture: fortification is effective where it is well matched to consumption, but coverage remains incomplete and inequitable when programme design relies on a narrow set of vehicles selected without adequate attention to who eats what.

For policymakers, the message is both a warning and an opportunity. The warning is that continued investment in fortification programmes designed around convenience rather than equity risks entrenching nutritional disparities even as headline coverage statistics improve. The opportunity is that the analytical tools needed to close these gaps already exist, in the form of public dietary datasets and systematic frameworks that link consumption patterns to micronutrient needs. Adams concludes that building more equitable fortification programmes will require deliberate effort to match the foods that deficient populations actually consume with the vehicles selected for nutrient delivery. As hidden hunger continues to undermine health and development across West Africa and beyond, that matching of needs and consumption may prove to be the decisive factor determining whether the next generation of fortification programmes fulfills their considerable public health promise.

Subject of Research: Equity in large-scale food fortification programmes based on matching micronutrient needs with food consumption patterns in West Africa

Article Title: Equitable fortification programmes require matching needs and consumption

Article References: Equitable fortification programmes require matching needs and consumption. (n.d.). https://doi.org/10.1038/s43016-026-01421-1

Image Credits: AI Generated

DOI: 10.1038/s43016-026-01421-1

Keywords: food fortification, hidden hunger, micronutrient deficiency, West Africa, public health nutrition, food policy, dietary data, equity, malnutrition, fortified foods, nutrition programmes, Nature Food

The study, conducted by researchers affiliated with Moffitt Cancer Center in collaboration with CAN Community Health, a Ryan White-funded clinic network predominantly based in Florida, was published in the journal Cancer Causes & Control. It set out to identify the sociodemographic, health, and social predictors of anal and cervical cancer screening uptake among adults with and without HIV. The stakes are considerable: high-risk HPV causes more than ninety percent of anal and cervical cancers, and people with HIV are roughly seventeen times more likely to develop anal cancer than people without the virus, while women with HIV face about a fourfold increase in cervical cancer risk. HIV-related immunosuppression allows HPV infection to persist and progress more readily toward malignancy, and health system barriers contribute to later-stage diagnoses and higher mortality among this population.

Both anal and cervical cancers are unusual among malignancies in that they progress through well-defined, detectable precancerous lesions. Removing high-grade squamous intraepithelial lesions can halt progression before invasive cancer develops, which makes screening an unusually powerful prevention tool. For cervical cancer, established guidelines exist: the U.S. Preventive Services Task Force recommends screening every three years for women without HIV aged 21 to 65, while the Infectious Diseases Society of America advises annual screening for women with HIV beginning at age 21. Anal cancer screening guidance is more recent. The landmark ANCHOR study showed that treating anal high-grade lesions in people with HIV significantly reduced anal cancer incidence compared with active monitoring, and those findings underpin the International Anal Neoplasia Society consensus guidelines, which recommend screening for HIV-positive men who have sex with men and transgender women aged 35 and older, and for HIV-negative people in high-risk groups aged 45 and older.

To measure how these recommendations translate into real-world care, the research team implemented a cross-sectional survey between April and June 2024 among adult patients of the CAN clinic network, which serves more than 31,100 unique patients annually, a population that is 35 percent White, 35 percent Black, and 18 percent Hispanic or Latino. The questionnaire, distributed anonymously through the clinic’s electronic patient intake system and offered in English and Spanish, collected information on demographics, health history, cancer prevention behaviors, experiences with the health system, and social exposures including HIV-related stigma. Participants received a twenty-five dollar gift card. From the responses, 412 participants were eligible for anal cancer screening and 294 women were eligible for cervical cancer screening based on current guidelines.

The characteristics of the two screening-eligible groups reflected the populations most at risk. Among those eligible for anal cancer screening, the median age was 56 years, 88.8 percent were living with HIV, and 82.3 percent were men, with roughly two-thirds identifying as gay or lesbian. Among women eligible for cervical cancer screening, the median age was 38 and 43.5 percent were living with HIV. The researchers computed adjusted prevalence ratios using multivariable Poisson regression, guided by the Andersen Behavioral Model of health services use, with models stratified by HIV status and sex to account for documented differences in cancer risk and screening outcomes across these subpopulations.

The anal cancer findings delivered a cautiously optimistic signal. Overall, 58.6 percent of screening-eligible participants reported ever having been screened, most commonly through an anal Pap test or high-resolution anoscopy. After statistical adjustment, men with HIV were 57 percent more likely to have received anal cancer screening than men without HIV. Within the group of men with HIV, uptake was higher among those who had been diagnosed with any precancer and those living with three or more comorbidities, a pattern the authors attribute to more frequent medical encounters creating more opportunities for preventive services. Living in a household of three or more people was associated with significantly lower uptake among these men, possibly reflecting caregiving responsibilities, competing demands, or limited economic means that crowd out preventive visits.

The cervical cancer picture was far less reassuring. Only 47 percent of women with HIV had received guideline-adherent cervical screening, compared with 71 percent of women without HIV, a gap that persisted after adjustment, leaving women with HIV 40 percent less likely to be screened on time. This shortfall is particularly troubling because U.S. guidelines call for more frequent, annual screening in this higher-risk group, not less. The study also identified a psychosocial driver: among women with HIV, greater concerns about disclosing their HIV status were independently associated with lower guideline-adherent cervical screening uptake. This finding reinforces a growing body of evidence that stigma is not merely an abstract social burden but a concrete mechanism that undermines preventive care, engagement with health services, and trust in medical systems.

The researchers point to several practical implications. Community-based, culturally sensitive screening programs embedded in clinics that patients already trust appear to pay dividends, and the integrated social services offered by Ryan White-funded networks may help explain why anal cancer screening among men with HIV exceeded that of their HIV-negative counterparts. For cervical cancer, proven strategies exist to close the gap, including provider reminders, patient education campaigns, and HPV self-collection kits that can overcome geographic barriers, limited access, and the discomfort or stigma associated with pelvic examinations. The authors also note that clinician awareness matters, since gaps in provider knowledge and training about screening recommendations for people with HIV remain documented barriers alongside fragmented care, unstable housing, and transportation difficulties.

The study carries limitations worth noting. It was conducted within a single, highly diverse clinic network in Florida, so results may not generalize everywhere; it captured only patient-reported characteristics rather than provider-level factors; it assessed Pap testing rather than high-risk HPV testing for cervical screening adherence; and its cross-sectional design precludes conclusions about cause and effect, including the timing of precancer diagnoses relative to screening. Small sample sizes in some stratified models may also have limited statistical power. Still, the divergent findings, with anal screening lagging among women even as it advances among men, and cervical screening falling short precisely among the women who need it most, offer clinicians and public health planners a specific map of where targeted interventions, from stigma reduction to self-sampling, could save lives among one of the nation’s most cancer-vulnerable populations.

Subject of Research: Predictors of anal and cervical cancer screening uptake among adults with and without HIV

Article Title: Predictors of anal and cervical cancer screening uptake among adults with and without HIV: survey of a community-based health clinic network

Article References: Lin, Y. C., Hume, E., Boxtha, C., Commaroto, S. A., Lael, M., Christy, S. M., Vadaparampil, S. T., Giuliano, A. R., Coghill, A. E., Schabath, M. B., Vidrine, D. J., Peterson, J., DiPalmo, S., Joshi, H., Shukla, P., Vidrine, J. I., & Islam, J. Y. (2026). Predictors of anal and cervical cancer screening uptake among adults with and without HIV: survey of a community-based health clinic network. Cancer Causes & Control, 37(10), Article 159. https://doi.org/10.1007/s10552-026-02239-9

Image Credits: AI Generated

DOI: 10.1007/s10552-026-02239-9

Keywords: HIV, anal cancer screening, cervical cancer screening, HPV, cancer prevention, health disparities, HIV stigma, Pap test, community health clinics, guideline adherence, Cancer Causes & Control, Ryan White clinics

The study draws on pooled data from the 2011 Demographic and Health Survey-Multiple Indicator Cluster Survey and the 2018 Demographic and Health Survey, two nationally representative household surveys conducted by Cameroon’s National Institute of Statistics in partnership with international agencies. Together, the surveys cover 21,465 children born in the five years preceding each wave, of whom 1,646, or 7.46 percent, died before reaching their fifth birthday. Because each survey records complete birth histories, the researchers were able to construct time-to-event measures of child survival, treating children who died as events and those still alive at the time of interview as right-censored observations.

What sets the analysis apart is its methodological approach. Most research on child mortality in sub-Saharan Africa relies on regression models that estimate the average effect of each individual predictor, such as maternal education or birth interval, while holding other factors constant. The authors argue that such variable-centered strategies obscure the reality that vulnerability rarely stems from a single adverse characteristic. Instead, mortality risk emerges from the accumulation of reproductive constraints, limited parental resources, restricted access to health services, and adverse community environments that cluster together within particular households and communities.

To capture these configurations, the researchers turned to a random survival forest, a machine learning method that extends tree-based ensembles to right-censored survival data. Unlike the conventional Cox proportional hazards model, which assumes that relative risks between individuals remain constant over time and that covariate effects are linear and additive, the random survival forest makes no such assumptions. The choice was not merely stylistic. Tests based on Schoenfeld residuals revealed widespread and statistically significant violations of the proportional hazards assumption in the Cox benchmark model, with a global test statistic of 172.35 and a p-value below 0.001, indicating that the relative contribution of risk factors changes substantially over the course of early childhood.

The random survival forest produced a continuous risk score for each child, summarizing the estimated probability of death before 59 months. When the researchers ranked children along this gradient and partitioned them into strata, three distinct groups emerged. Children in the low-risk stratum, slightly more than half of the sample, experienced a cumulative mortality of just 2.1 percent. The intermediate-risk stratum, representing roughly a quarter of children, faced a mortality of 6.3 percent. The high-risk stratum, also about a quarter of the sample, accounted for a disproportionate share of deaths, with 1,210 of the 1,646 observed deaths and a cumulative mortality of 27.8 percent. Kaplan-Meier survival curves confirmed a clear and monotonic separation of trajectories, with differences emerging within the first months of life and persisting throughout the first five years.

The social composition of each stratum proved internally coherent and revealing. Children in the low-risk stratum were predominantly embedded in advantaged contexts, characterized by overrepresentation of higher maternal and paternal education, greater maternal media exposure, wealthier households, urban residence, higher birth weight, more antenatal care visits, and greater maternal decision-making autonomy. The intermediate-risk stratum presented a more paradoxical picture: despite favorable educational and informational resources, these children were disproportionately exposed to low birth weight, short birth intervals, young motherhood, and missed antenatal care, illustrating that social resources alone cannot fully offset early-life biological vulnerabilities.

The high-risk stratum concentrated disadvantage across every dimension the researchers measured. Low birth weight appeared at markedly higher levels than in the intermediate group, alongside strong overrepresentation of short preceding birth intervals reflecting closely spaced fertility. Both mothers and partners in this group were more likely to have no formal education, mothers were disproportionately likely to receive no antenatal care and to deliver at home rather than in health facilities, and women without any household decision-making autonomy were overrepresented. The authors describe this as a configuration of compounded vulnerability, in which biological risk factors, constrained reproductive conditions, and entrenched social disadvantage reinforce one another.

Perhaps the most sobering finding concerns temporal persistence. Comparing the 2011 and 2018 survey waves, the researchers found that although overall under-five mortality in Cameroon declined from 144 to 80 deaths per 1,000 live births between 2004 and 2018, the social structuring of vulnerability remained remarkably stable. High-risk strata in both waves were characterized by the same accumulation of reproductive, educational, and healthcare disadvantages, while low-risk strata concentrated protective resources. Progress in child survival, in other words, occurred without fundamentally altering the distribution of mortality risk across social groups, raising questions about whether aggregate improvements mask persistent inequity.

The findings carry significant implications for public health policy, both in Cameroon and across sub-Saharan Africa, a region that accounts for nearly half of the global burden of under-five mortality despite representing only about 17 percent of the world’s population. In 2023, approximately 4.8 million children worldwide died before their fifth birthday, mostly from preventable causes, and progress toward the Sustainable Development Goal target of 25 deaths per 1,000 live births by 2030 remains far off track in Cameroon, where the 2018 level stood at 80 deaths per 1,000 live births. The study suggests that interventions targeting individual risk factors in isolation may be insufficient; instead, programs should address the concentration of disadvantages within identifiable high-risk population strata through integrated maternal and child health approaches.

The authors are careful to note the limitations of their approach. The strata are empirical groupings along a continuous risk gradient, not latent classes or causal typologies, and should be interpreted as descriptive representations of cumulative vulnerability rather than distinct causal entities. The analysis also relies on retrospective birth histories, which may be subject to recall bias, particularly for early neonatal deaths that are heavily concentrated in the high-risk stratum. Nevertheless, the study demonstrates that machine learning methods, used as exploratory tools rather than black-box predictors, can make mortality heterogeneity empirically observable in ways that complement conventional regression. Future research, the authors suggest, could map the spatial distribution of vulnerability strata using survey cluster coordinates, examine transitions between strata over time with longitudinal data, and apply similar person-centered survival approaches to other health outcomes and populations across the region.

Subject of Research: Empirical vulnerability strata in under-five mortality in Cameroon identified using survival-based machine learning on Demographic and Health Survey data

Article Title: Empirical vulnerability strata in under-five mortality in Cameroon: Evidence from DHS data

Article References: Mounchingam, A. N., & Adjiwanou, V. (2026). Empirical vulnerability strata in under-five mortality in Cameroon: Evidence from DHS data. SSM – Population Health, 35, Article 101965. https://doi.org/10.1016/j.ssmph.2026.101965

Image Credits: AI Generated

DOI: 10.1016/j.ssmph.2026.101965

Keywords: under-five mortality, Cameroon, DHS data, random survival forest, machine learning, child survival, social inequality, maternal education, antenatal care, sub-Saharan Africa, survival analysis, health disparities

The study, led by Soo Youn Bae of Seoul St. Mary’s Hospital at The Catholic University of Korea and colleagues, examined 696,960 women diagnosed with Stage I–III breast cancer between 1975 and 2021, drawing on the SEER 8 registries, the longest-running and most rigorously maintained cancer surveillance system in the United States. Rather than simply comparing average ages at the beginning and end of the period, the researchers modeled annual trajectories of diagnostic age using weighted ordinary least squares regression, estimating the rate of change—captured as a slope coefficient, β1—for each calendar year across every subgroup. The approach allowed them to detect not just whether diagnostic ages rose or fell, but how fast, at which cancer stage, and for whom.

The headline finding is a profound divergence along socioeconomic lines. Women living in the highest-income census tracts—the top quartile of neighborhood income—experienced significant, sustained increases in their age at diagnosis, consistent with the overall national trend toward later diagnosis. Women in the lowest-income quartile, by contrast, showed stagnant or even declining diagnostic ages. The pattern was particularly stark for Stage II disease: in the lowest-income group, the annual rate of change in diagnostic age was slightly negative, at β1 = −0.028 years per year, meaning that over the 46-year window, the average age at diagnosis for low-income women with Stage II breast cancer effectively moved backward while their wealthier counterparts aged into their diagnoses.

Geography told a parallel story. Women in rural communities, classified using the rural–urban continuum codes that rank counties from most metropolitan to most remote, similarly failed to participate in the national shift toward later diagnosis. Their diagnostic ages remained flat or drifted downward over the study period. The implication is uncomfortable: the demographic transition that has pushed breast cancer into later life for much of the population has simply bypassed the poorest and most geographically isolated women, whose tumors continue to be found at younger ages—and, given the established link between younger age at diagnosis for these groups and later-stage presentation, often at more dangerous points in the disease course.

The racial analysis added a second layer of complexity. Black women in the cohort showed the steepest annual increases in diagnostic age across all tumor stages, a trend that outpaced every other racial group. Yet despite this rapid upward trajectory, Black women remained younger at diagnosis than White women throughout the entire 46-year span. In other words, the fastest improvement in trajectory was not enough to close a persistent gap in the level. The finding captures a well-known paradox in breast cancer epidemiology: Black women are disproportionately diagnosed at younger ages and with more aggressive tumor subtypes, including higher rates of triple-negative and other hormone receptor–negative disease, while simultaneously facing barriers to timely screening and follow-up that delay detection within any given age band.

Why would diagnostic age rise for some groups and stall for others? The authors point to the intertwined machinery of screening access, reproductive and hormonal trends, and health care delivery. The national rise in diagnostic age partly reflects the aging of the population and the widespread adoption of screening mammography, which tends to detect cancers in older women earlier and more often. Mammography uptake, however, has never been evenly distributed. Studies spanning decades have documented lower screening rates among low-income women, rural residents, and some racial and ethnic minority groups, along with longer intervals between abnormal findings and diagnostic resolution. When screening is inconsistent, cancers are more likely to be detected symptomatically—and in groups with higher baseline risks of early-onset disease, that symptomatic detection skews young.

Hormone and reproductive factors plausibly deepen the divide. The rise and fall of menopausal hormone therapy—sharply curtailed after the Women’s Health Initiative reported increased breast cancer risk with combined estrogen plus progestin in 2002—altered incidence patterns, particularly among older, more affluent women who were most likely to use these therapies. Trends toward later childbearing, lower parity, and higher rates of obesity have reshaped risk profiles in ways that differ across socioeconomic strata. Higher-income women have, on balance, experienced risk-factor shifts associated with later-onset disease, while populations facing overlapping disadvantages have carried a heavier burden of early-onset, biologically aggressive tumors. The new trajectory data suggest these two forces have been quietly pulling the age of diagnosis apart for decades.

The technical rigor of the analysis lends weight to its conclusions. By stratifying simultaneously by stage, race, census tract income quartile, and rural–urban continuum code, and by applying weighted regression to annual mean diagnostic ages, the researchers could distinguish genuine temporal trends from artifacts of changing case mix. Stage-specific stratification matters because screening tends to shift the detected-stage distribution: rising diagnostic ages in Stage I disease can reflect early detection in older women, whereas declining or flat diagnostic ages in Stage II–III disease signal that some populations are not being caught by the early-detection net at all. The negative slope for low-income Stage II patients is precisely the signature one would expect if early-onset disease continues to dominate in a population that screening programs have failed to reach.

The policy implications are difficult to ignore. Current screening guidelines in the United States are built around age thresholds—typically recommending that average-risk women begin mammography in their 40s or 50s—implicitly assuming that breast cancer risk rises with age in a broadly uniform way. This study challenges that assumption by showing that the age structure of risk has diverged across social strata. A one-size-fits-all age-based policy, the authors argue, entrenches inequity: it calibrates optimally for high-income metropolitan women, whose diagnostic ages are rising, while under-serving low-income and rural women, whose disease continues to present earlier. Equitable, subgroup-specific screening strategies—whether through risk-adapted starting ages, enhanced outreach in underserved communities, mobile mammography in rural areas, or patient-navigation programs to shorten diagnostic delays—follow directly from the data.

The study also carries a broader lesson about how aggregate statistics can conceal inequality. Had the researchers stopped at the national average, the story would have been one of gradual progress: women, on the whole, are developing breast cancer later, and later diagnosis within a screened population generally correlates with better outcomes. Only by decomposing the trend did the deeper reality emerge—that the benefits of a half-century of progress in cancer detection and care have been distributed unevenly along lines of income, geography, and race. The two-year rise in mean diagnostic age is real, but it is an average of two very different worlds: one where women age into screenings and early detections, and another where cancer arrives early, often between screenings, and frequently at a stage that screening was supposed to prevent. Closing that diagnostic age gap, the authors conclude, is now one of the clearest quantitative targets for achieving equity in breast cancer control.

Subject of Research: Temporal trends in age at breast cancer diagnosis across socioeconomic, racial, and geographic subgroups in the United States from 1975 to 2021

Article Title: Temporal trajectories of age at breast cancer diagnosis by socioeconomic and geographic factors: a 1975–2021 SEER analysis

Article References: Bae, S. Y., Kim, C. W., Chin, J., Lee, J. A., Kim, D., Lee, Y. J., Yoon, C. I., & Park, W.-C. (2026). Temporal trajectories of age at breast cancer diagnosis by socioeconomic and geographic factors: a 1975–2021 SEER analysis. Cancer Causes & Control, 37(10), Article 160. https://doi.org/10.1007/s10552-026-02247-9

Image Credits: AI Generated

DOI: 10.1007/s10552-026-02247-9

Keywords: breast cancer, age at diagnosis, health disparities, socioeconomic factors, SEER, cancer screening, rural health, epidemiology, health equity, mammography, social determinants of health, cancer surveillance

The research team drew on the Global Burden of Disease 2023 dataset, one of the most comprehensive efforts to quantify health loss worldwide, coordinated by the Institute for Health Metrics and Evaluation. Rather than treating the planet as a single unit, the investigators stratified countries into five quintiles according to the Socio-Demographic Index, or SDI, a composite measure that combines income per capita, average educational attainment, and fertility rates. This allowed them to track how the burden of thalassemia evolved from 1990 to 2023 not just in terms of raw numbers, but in rates adjusted for the age structure of each population, a critical distinction when comparing regions with vastly different demographic profiles.

The scale of progress in high-income settings is striking. In high SDI regions, age-standardized mortality declined at an average annual rate of 4.12 percent, while age-standardized disability-adjusted life years, or DALYs, a metric that captures both years of life lost and years lived with disability, fell by 4.20 percent per year. High-middle SDI regions followed closely behind, with annual reductions of 3.86 percent in mortality and 3.93 percent in DALY rates. These sustained declines reflect decades of accumulated advances: widespread carrier screening programs, prenatal and premarital genetic testing, safer and more reliable blood transfusion systems, and improved iron chelation therapy that prevents the fatal organ damage caused by transfusional iron overload.

The picture in low SDI regions could hardly be more different. There, absolute deaths from thalassemia rose by 16 percent over the study period, and absolute prevalence climbed by a remarkable 66 percent, reaching 321,005 cases by 2023. The most likely interpretation of this paradox is bittersweet: more children with thalassemia are surviving infancy thanks to basic medical interventions, but without access to the lifelong transfusion and chelation infrastructure that sustains patients in wealthier countries, many of these individuals live with severe untreated disease. Rising prevalence in this context signals both survival gains and a growing reservoir of patients whose ongoing care needs are not being met.

One finding stands out as particularly concerning for global health planners. The low-middle SDI group was the only stratum in which age-standardized incidence showed a statistically significant net increase over the full study period, with an average annual percentage change of plus 0.12 percent. Incidence reflects the number of new cases being born, which is directly tied to carrier frequency and reproductive patterns rather than to treatment quality. A rising incidence in this band suggests that prevention programs, particularly premarital and prenatal screening for carrier couples, have not yet achieved the penetration seen in higher SDI regions, where such programs in places like Cyprus, Sardinia, and parts of the Middle East famously reduced the birth incidence of severe thalassemia by well over 90 percent.

Methodologically, the study went beyond simple linear trend analysis. The researchers applied joinpoint regression, a statistical technique that identifies inflection points where the trajectory of a disease burden indicator changes direction or speed, and then calculates annual percentage changes within each segment along with an overall average annual percentage change. This approach revealed that the burden of thalassemia has not moved along smooth trajectories anywhere in the world. Instead, all five SDI strata displayed non-linear, multi-phase patterns, with recent reversals in incidence and prevalence rates in low and low-middle SDI regions, hinting that gains made in some periods have been partially undone in others, possibly reflecting disruptions in health services, demographic shifts, or changes in screening coverage.

The persistence of a nearly six-fold gap in age-standardized death and DALY rates between the highest and lowest SDI quintiles by 2023 is perhaps the study’s most sobering conclusion. Thalassemia is, in principle, a survivable condition: with regular transfusions and effective iron chelation, patients in well-resourced systems can live full lives, and curative options such as hematopoietic stem cell transplantation exist for those with matched donors. In low SDI settings, however, safe blood supplies are often insufficient, chelation drugs may be unaffordable or unavailable, and specialized monitoring of iron burden is limited. The disease, in effect, has become a marker of where a person happens to be born.

The authors argue that closing this gap requires targeted, equitable strategies rather than generic health system strengthening. They point specifically to expanded premarital and carrier screening programs tailored to regions with high carrier frequencies, strengthened national blood supply systems to guarantee reliable transfusion access, and sustained investment in the health workforce and infrastructure needed to deliver lifelong care. Gene therapy and newly approved transformative treatments may eventually reshape the global landscape, but their current cost places them far beyond the reach of the populations that carry the greatest burden, raising pressing questions about how emerging cures can be made globally accessible.

As the world’s demographic center of gravity shifts toward the regions least equipped to manage inherited disease, the findings serve as both a warning and a roadmap. The three-decade record shows unequivocally that thalassemia burden can be driven down when screening, blood systems, and treatment are made available. The failure, the study makes clear, is not scientific but structural, and the next chapter of this global story will be written by the choices governments and international agencies make about investing in the health systems of those who have been left behind.

Thalassemia arises from inherited defects in the production of hemoglobin, the oxygen-carrying protein inside red blood cells. The two principal clinical forms, alpha and beta thalassemia, result from reduced synthesis of the corresponding globin chains, leading to chronic anemia whose severity ranges from silent carrier status to transfusion-dependent disease. Because carriers are typically asymptomatic, the condition passes silently through generations in populations where the trait is common, and in many regions carrier frequencies reach double-digit percentages. This population genetics explains why incidence, which counts newly affected births, responds only slowly to interventions and why prevention depends on identifying carrier couples before or during reproductive years rather than on treating existing patients.

The DALY metric used in the analysis deserves particular attention when interpreting the findings. By combining years of life lost to premature mortality with years lived in states of reduced health, DALYs capture dimensions of suffering that death statistics alone miss. For a chronic condition like thalassemia, where patients may survive for decades with impaired quality of life, the DALY decline in high SDI regions reflects not only fewer deaths but also healthier lives among survivors, a consequence of better transfusion schedules, more tolerable oral chelation regimens, and improved surveillance of complications such as cardiac iron deposition and endocrine dysfunction.

The choice of age-standardized rates as the primary comparison metric also shapes the interpretation. Populations in low SDI regions tend to be young, with high fertility and a large share of children, precisely the age group where severe thalassemia manifests. Age standardization removes this demographic distortion, allowing a fair comparison of disease intensity across settings. That absolute counts can rise even while standardized rates fall, or vice versa, is a recurring source of confusion in burden studies, and the divergent patterns observed here, with falling rates but rising absolute numbers in the poorest regions, illustrate how population growth can outpace epidemiological improvement.

Joinpoint regression, while more informative than simple linear trends, carries its own interpretive cautions. The technique identifies change points that may correspond to real epidemiological shifts, but it can also flag inflections driven by changes in data availability, modeling assumptions, or coding practices within the GBD framework. The authors’ finding of multi-phase trajectories across all strata should therefore be read as a description of complex dynamics rather than a precise causal timeline. Nevertheless, the consistency of the direction of change, with sustained improvement at the top of the development spectrum and stagnation or reversal at the bottom, lends credibility to the central conclusion that development level remains the dominant determinant of thalassemia outcomes.

The study’s reliance on modeled estimates is also worth noting. In many low SDI countries, vital registration systems are incomplete, and the true prevalence of thalassemia is difficult to measure directly, requiring statistical synthesis from surveys, registries, and neighboring populations. This uncertainty is greatest exactly where the burden appears highest, meaning the reported disparities may be conservative if anything, since undercounting is more likely in the settings with the weakest surveillance infrastructure.

For clinicians and policymakers, the practical message is that the tools needed to prevent and manage thalassemia are neither new nor technologically exotic. Premarital screening, reliable blood banking, and generic iron chelators are established interventions whose effectiveness has been demonstrated for decades. The barrier identified by this analysis is one of implementation and financing, and the documented trajectory of high SDI regions serves as evidence that sustained, coordinated investment can transform a fatal childhood disease into a manageable chronic condition.

Subject of Research: Global trends and socioeconomic disparities in the burden of thalassemia from 1990 to 2023

Article Title: Global burden of thalassemia by socio-demographic index, 1990–2023: trends, disparities, and future implications

Article References: Sawaira, F., Shahab, S. H., Mal, M., Kritika, F., Osama, M., Hayat, S., Gul, O., Moeez, A., Yasir, M., Junaid, M., Arsalan, M., Mughees, M., & Al Diab Al Azzawi, M. (2026). Global burden of thalassemia by socio-demographic index, 1990–2023: trends, disparities, and future implications. Annals of Hematology. https://doi.org/10.1007/s00277-026-07247-y

Image Credits: AI Generated

DOI: 10.1007/s00277-026-07247-y

Keywords: thalassemia, global burden of disease, socio-demographic index, health disparities, DALYs, age-standardized rates, joinpoint regression, premarital screening, blood transfusion, iron chelation, prevalence, global health inequity

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