The research team, led by Yuko Inoue of the University of Tokyo and Institute of Science Tokyo, together with Rebecca Wilson of the University of Bristol, Naoko Adachi, and corresponding author Shiho Kino, drew on an unusually powerful data source: the 2022 Programme for International Student Assessment, or PISA, administered by the Organisation for Economic Co-operation and Development. PISA is best known for benchmarking the academic performance of fifteen-year-olds, but the 2022 cycle included a retrospective question asking students whether they had felt lonely during the pandemic-related school closures. By harvesting responses from 91,591 students across 35 OECD countries, the investigators assembled a dataset large and geographically broad enough to detect patterns that smaller, single-country studies could easily miss.

The headline number is sobering on its own. Overall, 42.8 percent of students agreed or strongly agreed that they had felt lonely while schools were shut, and 14.3 percent strongly agreed. In other words, roughly two in five adolescents across some of the world’s wealthiest democracies reported experiencing loneliness during a period when the school, for most of them the primary arena of social life, had effectively disappeared. Because the question was retrospective, asked in 2022 about the closure period, the authors are careful to frame the measure as perceived loneliness during that time rather than a real-time clinical diagnosis. Still, the sheer scale of agreement across such a diverse sample underscores how disruptive the closures were to adolescent social connectedness.

Methodologically, the study goes well beyond simple percentages. The team used multilevel ordinal logistic regression, a statistical framework appropriate when the outcome, loneliness, is measured on an ordered scale and when students are nested within schools and countries, allowing the model to account for clustering at each level. The central exposure of interest was parental education, used as a proxy for socioeconomic status, with the highest parental attainment categorized and tertiary education, meaning university-level degrees, serving as the reference point for the most advantaged group. The models adjusted for an unusually rich set of covariates: the duration of school closures, students’ perceived learning during closures, difficulties with self-directed learning, self-efficacy in self-directed learning, and measures of family and school support. This adjustment strategy matters because these factors plausibly lie on the pathway between socioeconomic background and loneliness, and ignoring them could distort the estimated associations.

The first major result concerns gender. Female students had significantly higher odds of reporting greater loneliness than male students, with an odds ratio of 1.80 and a 95 percent confidence interval of 1.66 to 1.95. An odds ratio of this magnitude, and with a confidence interval that does not come close to crossing 1.0, indicates a robust and substantial difference: girls were nearly twice as likely as boys to report elevated loneliness during the closures. This aligns with a broader literature suggesting that adolescent girls tend to derive more of their emotional support from peer networks and may be more sensitive to interruptions in face-to-face contact, although the PISA data cannot disentangle the underlying psychological mechanisms.

The second and more surprising result emerges from the interaction between gender and parental education. In epidemiological terms, an interaction tests whether the effect of one factor depends on the level of another. Here, the researchers found a statistically significant interaction, with particularly elevated odds of loneliness among female students whose parents had attained tertiary education. The odds ratio for the interaction term was 1.35, with a 95 percent confidence interval of 1.11 to 1.65. Translated into plain language, the protective effect that higher socioeconomic status is often assumed to confer on adolescent mental health did not extend to loneliness during the closures, and for girls from university-educated families the burden was actually amplified relative to what the main effects alone would predict.

Why might this counterintuitive pattern arise? The authors themselves are measured, noting that adolescents with tertiary-educated parents are not necessarily protected from loneliness. Several plausible explanations circulate in the wider literature. Families with more resources may have maintained academic continuity through devices, tutors, and parental supervision, but academic support is not the same as peer connection. Highly educated parents were also more likely to work in jobs compatible with strict remote work, potentially meaning tighter household isolation rather than looser rules. Adolescent girls in such households may have experienced heightened pressure around self-directed learning and achievement, and the loss of structured social time may have hit hardest among those most embedded in school-based friendship networks. The PISA data cannot adjudicate among these hypotheses, but the interaction finding signals that policymakers should not assume socioeconomic advantage automatically buffers emotional wellbeing during educational disruptions.

The study’s limitations deserve honest treatment. The loneliness measure is a single self-report item, which is efficient for cross-national surveys but cannot capture the depth, duration, or clinical significance of loneliness. Retrospective reporting introduces recall bias, since students answered in 2022 about experiences that had occurred up to two years earlier, and mood at the time of reporting may color memories of the closure period. The cross-sectional design precludes causal inference: the associations describe who reported loneliness, not what caused it. Parental education, while a widely used and defensible proxy, is only one dimension of socioeconomic status and may behave differently across the 35 countries in the sample. Finally, the data cover OECD countries only, so the findings cannot be generalized to low- and middle-income settings where school closures often lasted longer and support infrastructures were thinner.

Even with those caveats, the implications are concrete. The authors conclude that emotional and academic support must be provided across gender and socioeconomic groups during educational disruptions, not targeted narrowly at disadvantaged households. Schools planning for future closures, whether from pandemics, natural disasters, or other emergencies, should build in structured social contact, monitor loneliness as systematically as they monitor learning loss, and pay particular attention to girls, who bore a consistently heavier emotional load in this data. The work was supported by grants from the Japan Society for the Promotion of Science, including a Grant-in-Aid for JSPS Fellows (24KJ0065) and a Grant-in-Aid for Early-Career Scientists (22K17266), and the authors report no competing interests. As a secondary analysis of publicly available OECD data, the study required no new ethical approval. What it delivers is a warning worth heeding: when schools close, loneliness does not discriminate by parental diploma, and the adolescents who seem safest on paper may be quietly struggling the most.

Subject of Research: Adolescent loneliness and socioeconomic and gender differences during COVID-19 pandemic-related school closures

Article Title: Adolescent loneliness and socioeconomic factors during the pandemic-related school closures: a cross-sectional study using retrospective PISA data

Article References: Inoue, Y., Wilson, R., Adachi, N., & Kino, S. (2026). Adolescent loneliness and socioeconomic factors during the pandemic-related school closures: a cross-sectional study using retrospective PISA data. International Journal for Equity in Health. https://doi.org/10.1186/s12939-026-03018-3

Image Credits: AI Generated

DOI: 10.1186/s12939-026-03018-3

Keywords: adolescent loneliness, school closures, COVID-19, PISA 2022, socioeconomic status, parental education, gender differences, mental health, OECD countries, public health, self-directed learning, health equity

The research draws on the Gothenburg H70 Birth Cohort Study, one of the longest-running population studies of ageing in the world. In 2014 to 2016, researchers comprehensively examined 70-year-olds born in 1944 who were living in Gothenburg, achieving a 72 percent response rate. Participants underwent extensive interviews and clinical assessments covering education, income, childhood family economic circumstances, mental health, cardiovascular disease, anthropometry, and laboratory measures, and they provided blood samples for genotyping. A follow-up examination was conducted five to eight years later, with a mean follow-up of roughly six years and a response rate of 77.6 percent among survivors. After excluding participants with missing parental data and those whose parents died before age 41, likely from causes unrelated to biological ageing such as accidents, the final baseline sample comprised 1,126 individuals, 523 men and 603 women.

The researchers classified parental longevity, or PL, into three groups. Participants were considered to have high parental longevity if both parents survived to age 85, which applied to 17.2 percent of the sample; medium parental longevity if one parent reached 85, applying to 43.3 percent; and low parental longevity if neither parent did, applying to 39.4 percent. The age-85 threshold was chosen deliberately: the participants’ parents were born around 1920, when cohort life expectancy was only about 74 years, so reaching 85 represented genuinely exceptional survival for that generation. Alongside this family-history measure, the team constructed two polygenic longevity scores, or PGLSs, using genome-wide association summary statistics from a large international meta-analysis of longevity genes, combined with a Bayesian shrinkage method and a European ancestry reference panel. One score included variants in the APOE locus, a gene region strongly tied to age-related disease and mortality, while the other excluded it.

At baseline, both higher parental longevity and higher polygenic scores were associated with more favourable social circumstances. People with long-lived parents, and people with higher genetic longevity scores, had spent longer in education, reported better childhood family economic conditions, and enjoyed higher current household income. Both measures were also linked to vascular health: high parental longevity and higher scores on the APOE-inclusive polygenic score were associated with less hypertension, and higher polygenic scores were inversely related to myocardial infarction, a finding the authors report as novel. But the two measures diverged sharply beyond that point, and the divergence is where the study becomes genuinely provocative.

Parental longevity, unlike the genetic scores, was associated with a broad constellation of biological advantages. Participants with high parental longevity had better scores on the Mini-Mental State Examination, higher levels of total cholesterol, HDL cholesterol and LDL cholesterol, lower body mass index, lower homocysteine, and lower levels of the inflammatory markers interleukin-6 and C-reactive protein. They were also less likely to be current smokers. Participants with even one long-lived parent showed better cognition, higher cholesterol, lower homocysteine and less smoking than those with two short-lived parents. The polygenic scores, by contrast, captured mainly the socioeconomic and cardiovascular factors and little else. Strikingly, the two measures showed no statistical association with each other at all, whether parental longevity was analysed as groups, as the mean of both parents’ ages, or as mothers’ and fathers’ ages separately.

Some of these findings challenge conventional assumptions. The higher total cholesterol and LDL cholesterol among offspring of long-lived parents may seem paradoxical, but they echo previous research, including studies suggesting that rising cholesterol in late life is associated with reduced dementia risk and lower mortality in older adults. Cholesterol is a precursor to steroid hormones essential for metabolism and immune function, and the authors caution that the so-called cholesterol paradox in late life should be interpreted carefully, noting that lipid-lowering therapy did not appear to explain the association and that frailty was rare in this relatively young-old population. Lower homocysteine among those with long-lived parents is also notable, since elevated homocysteine is linked to folate and vitamin B deficiency, endothelial dysfunction, atherosclerosis, cardiovascular events, and dementia.

Perhaps the most forward-looking result emerged at follow-up. Plasma phosphorylated-tau 217, or pTau217, is one of the most accurate blood biomarkers currently available for Alzheimer’s disease pathology, and its levels are known to rise steeply with age. In the longitudinal analyses, participants with high parental longevity showed significantly less increase in pTau217 over the six years than those whose parents had both died before 85. This suggests that Alzheimer’s pathology may establish itself later, or accumulate more slowly, in people with long-lived parents, potentially delaying the onset of dementia. Consistent with this, the high-parental-longevity group also had higher baseline MMSE scores. No such longitudinal associations were observed for the polygenic scores, and neither measure was associated with plasma neurofilament light, another age-sensitive neurodegeneration marker.

The authors are careful about causality. Lower interleukin-6 and C-reactive protein in offspring of long-lived parents may reflect healthier lifestyles and better overall health rather than a direct determinant of longevity, although low-grade inflammation, sometimes called inflammaging, is considered a central driver of accelerated ageing, dementia, cardiovascular disease and mortality. Sex also mattered: several associations, including those involving C-reactive protein, neurofilament light, creatinine and triglycerides, were significant only in women. The team also acknowledges limitations, including self-reported parental ages, possible selective survival bias, a predominantly white and age-homogeneous sample, and the smaller follow-up cohort, and they report both uncorrected and false-discovery-rate-corrected statistics, noting that some findings, including those on inflammatory markers and pTau217, did not survive multiple-comparison correction.

Nevertheless, the overall pattern is coherent and biologically plausible. Polygenic longevity scores, in their current form, appear to capture only a narrow slice of the biology of ageing, likely because longevity’s genetic architecture is highly heterogeneous and heavily environment-dependent. Parental longevity, by contrast, seems to summarise everything at once: inherited genetics, shared early environment, transgenerational social advantage, and accumulated lifestyle influences. The authors conclude that asking about parental lifespan could serve as a simple, inexpensive proxy for biological ageing, suitable for routine health assessments of older adults to flag individuals who might benefit from preventive screening for hypertension, cognitive decline, inflammation and emerging Alzheimer’s pathology. In an era of billion-dollar biomarker pipelines, the humble family history may still be one of medicine’s most underrated diagnostic instruments.

Subject of Research: Parental longevity and polygenic longevity scores in relation to ageing-related social, cardiovascular, inflammatory and neurodegenerative factors in 70-year-olds

Article Title: Parental longevity and polygenic longevity scores in relation to ageing-related factors in a population of 70-year-olds followed over six years: The Gothenburg H70 Birth Cohort Study

Article References: Seidu, N. M., Rydén, L., Skoog, J., Samuelsson, J., Kern, S., Waern, M., Zetterberg, H., Holstege, H., Erhag, H. F., Westman, E., & Skoog, I. (2026). Parental longevity and polygenic longevity scores in relation to ageing-related factors in a population of 70-year-olds followed over six years: The Gothenburg H70 Birth Cohort Study. GeroScience. https://doi.org/10.1007/s11357-026-02501-7

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02501-7

Keywords: parental longevity, polygenic longevity score, ageing, GeroScience, APOE, pTau217, Alzheimer's disease, inflammation, cholesterol, cardiovascular risk, socioeconomic status, H70 cohort

The study, led by Sukanya Chaemchoy of Chulalongkorn University together with Thanakrit Supsin, analyzed data from 24,273 students nested in 1,049 schools across Chile, Cyprus, Denmark, Greece, Korea, Norway, Romania, the Slovak Republic, Slovenia, Sweden, Chinese Taipei, and Uruguay. These were the 12 systems that administered ICILS 2023’s optional questionnaire on generative AI, which asked principals how likely they believed ChatGPT and similar tools were to help or harm students’ learning in their schools. The researchers linked these leadership reports with achievement data, principal questionnaires, and surveys completed by schools’ ICT coordinators, constructing an unusually rich picture of the organizational digital climate surrounding each student.

The five focal conditions were carefully distinguished. Positive ChatGPT expectations measured principals’ anticipated benefits, such as greater student interest in learning, better written work, and improved critical evaluation of information. Negative ChatGPT expectations captured anticipated harms, including shallow conceptual understanding, submission of work that is not the student’s own, and dependence on AI tools. Instructional ICT-use expectations reflected whether teachers were expected to integrate digital technology into teaching, assessment, and monitoring of progress, while ICT collaboration expectations concerned professional communication and collaboration via technology. Finally, pedagogical ICT hindrances, reported by ICT coordinators, captured constraints such as insufficient teacher skills, limited preparation time, weak pedagogical support, and restrictive policies.

Methodologically, the study is a masterclass in caution. The authors estimated separate weighted two-level models for each education system, treating students as nested within schools and adjusting for student sex, home internet access, computer experience, within-school socioeconomic background, and school socioeconomic composition. Because CIL was measured using five plausible values, each model was run five times and the results formally combined. The family of 60 primary tests, five school conditions across 12 systems, was then subjected to Benjamini-Hochberg false discovery rate control, a correction that dramatically raises the bar for what counts as a credible finding in large-scale educational research.

The outcome was unambiguous at the top line: not a single school condition produced a false-discovery-rate-retained association with CIL. Three coefficients did carry raw p values below 0.05. In Korea, higher ICT collaboration expectations were associated with roughly 9.55 points lower CIL, and pedagogical ICT hindrances were associated with about 4.11 points lower CIL. In the Slovak Republic, the direction reversed dramatically: ICT collaboration expectations were associated with 7.82 points higher CIL. Yet all three signals carried an FDR-adjusted q value of 0.730, meaning they are best read as nominal, system-specific hints for future replication rather than established associations.

The Korea-Slovak Republic contrast is perhaps the most intriguing descriptive finding. The same survey instrument, measuring the same construct, produced estimates with opposite signs and non-overlapping confidence intervals in the two systems. The authors are careful not to overclaim: no formal test of slope heterogeneity was conducted, and the study did not measure the national policies, governance arrangements, curricula, or implementation histories that might explain the divergence. But the pattern echoes earlier ICILS research from 2013, which found that the school-level conditions linked to teachers’ ICT use differed across Australia, the Czech Republic, Germany, and Norway, suggesting that identical school-scale scores may be embedded in fundamentally different institutional realities.

A secondary analysis reinforced this caution about pooled summaries. When the researchers constrained the focal slopes to be equal across systems, using equal total weights for each education system, all five common-slope confidence intervals included zero. The near-zero pooled estimate for ICT collaboration expectations simply cannot represent both Korea’s negative and the Slovak Republic’s positive coefficient. As the authors note, adjusting for system mean differences through country indicators does not demonstrate that school-level relationships are homogeneous, a point long emphasized in methodological work on multilevel modeling of country effects.

Six prespecified families of sensitivity analyses, covering 350 focal comparisons, tested whether the conclusions depended on weighting choices, socioeconomic decomposition, coding decisions, complete-case selection, influential schools, or survey-design variance estimation. Every sensitivity confidence interval overlapped its primary counterpart, and no comparison met the prespecified material-sensitivity criterion. The three nominal signals kept their direction in every available comparison, but they never escaped the multiplicity adjustment. In short, the null finding for school digital conditions is not a fragile artifact of one particular model specification.

What did matter, consistently, was student background. Within-school socioeconomic background showed positive adjusted associations with CIL in all 12 systems, with coefficients ranging from 7.78 to 26.52 CIL points per index point. School socioeconomic composition was also positive everywhere, at 30.57 to 64.49 points per index point, though the authors treat it cautiously because the aggregated school mean had reliability below 0.90 in seven systems. Computer experience was positively associated with CIL in every system, and female students outperformed male students in adjusted comparisons across the board. These results align with prior meta-analytic evidence of a positive, if modest, relationship between socioeconomic status and ICT literacy.

The implications reach beyond academia. As governments pour resources into digital infrastructure and school leaders form opinions about generative AI, this study warns against conflating leadership expectations with classroom reality. A principal who expects ChatGPT to boost learning is not necessarily leading a school where students actually develop stronger digital competencies, and none of the measured school conditions reliably distinguished high-CIL schools from low-CIL schools once socioeconomic and experiential factors were accounted for. The indirect pathway from leadership vision through organizational conditions, teacher practice, and student learning opportunities remains largely unmeasured, and this analysis explicitly did not test whether expectations influenced implementation or whether teacher practices mediated any association.

The authors also flag important limitations. The design is cross-sectional, so no causal or temporal claims are possible, and the 12 systems were defined by participation in the optional ChatGPT questionnaire rather than representative sampling of countries. The focal measures were principal and ICT coordinator reports rather than observations of actual teaching or student AI use, and included students had higher weighted mean CIL than excluded students in every system. Several systems, notably Chile, Norway, and Denmark, contributed fewer than 50 schools, widening school-level confidence intervals. These constraints mean the findings generalize only to the participating systems and samples analyzed.

Still, the study’s core message is a timely corrective to technological optimism. At a moment when generative AI is reshaping debates about homework, assessment, and information literacy, the largest multilevel evidence base yet assembled on principals’ AI expectations and students’ actual digital skills finds no common direct link between the two. What predicts assessed computer and information literacy, in these data, is not what school leaders expect of ChatGPT or their teachers, but the socioeconomic circumstances and accumulated computer experience that students bring with them. Until future research connects leadership expectations to real implementation, teacher enactment, and students’ digital activities, the study suggests, expectations about AI in schools should be read as organizational commentary, not as predictors of learning.

Subject of Research: Associations between school digital conditions and student computer and information literacy across 12 ICILS 2023 education systems

Article Title: School digital conditions and student computer and information literacy across 12 education systems: system-specific multilevel evidence from ICILS 2023

Article References: Chaemchoy, S., & Supsin, T. (2026). School digital conditions and student computer and information literacy across 12 education systems: system-specific multilevel evidence from ICILS 2023. Large-scale Assessments in Education, 14(1), Article 42. https://doi.org/10.1186/s40536-026-00315-9

Image Credits: AI Generated

DOI: 10.1186/s40536-026-00315-9

Keywords: ICILS 2023, computer and information literacy, ChatGPT expectations, school digital conditions, ICT in education, generative AI, multilevel modeling, socioeconomic status, digital inequality, international assessment, plausible values, false discovery rate

The stakes of the question are hard to overstate. Executive function skills develop rapidly during childhood, and performance on executive function assessments in early life predicts academic achievement, social competence and behavioral adjustment years later. Meta-analyses cited by the authors link early executive function to reading and science outcomes, to long-term academic attainment and even to reduced risk of psychopathology. Because these skills correlate with so many positive life outcomes, they have become one of the most attractive targets for intervention in developmental science, education policy and public health. Programs ranging from preschool curricula to computerized brain training have been launched on the premise that executive function is highly malleable. Yet the review notes that the experimental evidence for far transfer, meaning improvements that carry over from trained tasks to real-world outcomes, remains weak, and meta-analytic work on cognitive training generally concludes that gains rarely generalize beyond the trained tasks themselves.

The authors begin by examining how executive function is defined and measured, and they identify this as a foundational problem. In the classic latent-variable framework, executive function decomposes into inhibition, working memory updating and shifting, with a common underlying factor. But in young children, tasks designed to tap these components often fail to show the clean separations seen in adults, and performance depends heavily on how familiar children are with task demands, labels and materials. Studies showing that familiar labels help children engage proactive control, or that multidimensional reasoning boosts performance on the dimensional change card sort task, suggest that what looks like a general executive capacity is often knowledge and context bound. The review argues that executive function is best understood as a set of skills that are shaped by experience and deployed in specific situations, rather than as a fixed, domain-general cognitive muscle that any training program can strengthen.

Measurement is where this conceptual ambiguity becomes a practical crisis. The most common assessments, including conflict tasks such as the flanker and day-night paradigms, card sorting tasks and delayed gratification measures, were largely developed in Western, educated, industrialized, rich and democratic populations. Cross-cultural work reveals striking variability: cognitive flexibility patterns differ across cultural settings, and studies in Jordan, Kenya, Brazil, South Africa and The Gambia show that task performance and its environmental predictors do not map neatly onto the models built in North American and European samples. Parent and teacher rating scales, such as the Behavior Rating Inventory of Executive Function, capture yet another construct, one that correlates imperfectly with laboratory performance measures. The authors highlight emerging alternatives, including group-based classroom assessments and observational measures that embed executive function demands in real-world activities, which may better capture how regulation skills operate where children actually live and learn.

Turning to socioeconomic status, the review acknowledges one of the most consistent findings in the literature: children from lower socioeconomic backgrounds tend to score lower on executive function assessments, an association confirmed by meta-analysis. But the authors are emphatic that this correlation is causally ambiguous and often context-dependent. Socioeconomic status is a composite construct encompassing income, education, occupation and neighborhood resources, and critics cited in the review argue that treating it as a unitary variable obscures the specific mechanisms at work. Longitudinal studies point to candidate mediators, including cognitive stimulation, language development and environmental predictability, with neuroimaging work suggesting that cognitive stimulation is linked to neural function supporting working memory. Genetic confounding also looms large, as studies of maternal education and prenatal smoking show that inherited factors account for a substantial share of the apparent environmental effects. The review warns against deficit framing, urging researchers to consider how children’s skills may represent adaptations to the specific environments they inhabit.

The home environment and parenting emerge as a second major experiential domain, and one where the evidence is similarly suggestive but rarely decisive. Household chaos, characterized by noise, crowding and unpredictable routines, is associated with poorer executive function, an effect documented in meta-analysis and partially buffered by high-quality childcare. Home literacy environments, parental scaffolding, autonomy support and attachment security all show positive associations with children’s self-regulation in numerous studies spanning the United States, China, Chile, Korea and Côte d’Ivoire. Experimental work adds encouraging signal: an experimental study found that autonomy-supportive interactions improved preschoolers’ self-regulation, and a randomized clinical trial showed that an early parenting intervention accelerated inhibitory control development among children involved with child protective services. Still, the review stresses that most of this evidence is correlational, that effect sizes are typically modest, and that gene-environment correlation means children both shape and are shaped by their families in ways that standard designs cannot untangle.

Schooling, the third focal domain, offers some of the strongest quasi-experimental evidence that experience shapes executive function. School cutoff designs, which compare children born just before and just after enrollment deadlines, indicate that a year of schooling improves cognitive control and even alters associated patterns of brain activation. Differential growth in working memory across school-year and summer months suggests that classrooms actively promote executive function development rather than merely tracking maturation. The quality of teacher-child interactions matters as well, with meta-analytic evidence linking classroom interaction quality to children’s executive function gains. Curricular interventions tell a more complicated story. Programs such as Tools of the Mind generated early enthusiasm, but large rigorous evaluations have produced mixed results, while games-based approaches such as Red Light, Purple Light have shown benefits for school readiness in some low-income samples, including trials in Kenya. The Chicago School Readiness Project stands out for demonstrating longer-term impacts on behavioral regulation that persisted into late adolescence.

Why, then, has the intervention literature so often fallen short of its promise? The review offers a synthesis: interventions have typically treated executive function as a generic capacity to be exercised like a muscle, rather than asking what specific experiences, in specific contexts, help specific children regulate their behavior toward specific goals. The authors draw on a growing contextual perspective in developmental science, one that recognizes culture as constitutive rather than incidental. Culturally organized practices such as autonomy and helping, Indigenous frameworks of connectedness and culturally meaningful forms of self-regulation all suggest that the skills valued and cultivated in one community may differ from those assumed by standardized assessments and imported curricula. Ethical concerns raised by anthropologists about parenting interventions exported to low- and middle-income countries reinforce the point that interventions must be grounded in local meanings, values and strengths rather than framed around supposed deficits.

The review closes by outlining four key directions for future work. First, researchers need better conceptualizations of environmental quality and experience, moving beyond coarse socioeconomic categories to measure the specific features of environments, such as cognitive stimulation, predictability and stress, that plausibly shape developing regulation skills. Second, the field must improve the measurement of executive function itself, developing contextually grounded assessments that are validated across cultural and linguistic groups and that capture regulation as it unfolds in classrooms, homes and everyday activities. Third, studies must be designed to support stronger causal inference, leveraging natural experiments, randomized designs and genetically informed methods while remaining ecologically valid. Fourth, the authors call for greater attention to diversity and equity in who is studied, how findings are interpreted and who benefits from the resulting interventions, including genuine partnerships with communities in majority-world settings.

For a field with such high public stakes, the message of this review is both sobering and generative. Executive function skills matter enormously, they are demonstrably linked to experience, and yet the science of exactly how experience builds them remains incomplete in ways that have limited the success of interventions designed to improve children’s life chances. By demanding sharper concepts, better measures and culturally informed designs, the authors are not dismissing decades of work but redirecting it toward the questions that matter most. If the next generation of research can specify how experiences get under the skin to strengthen children’s regulation of thought and action, the promise of executive function science, from closing achievement gaps to designing smarter educational policies, may finally be kept.

Subject of Research: How experience such as socioeconomic status, parenting and schooling shapes the development of childhood executive function skills

Article Title: Understanding how experience supports the development of executive function skills

Article References: Doebel, S., Chevalier, N., Lipina, S. J., Rabii, V., & Ahmed, S. F. (2026). Understanding how experience supports the development of executive function skills. Nature Reviews Psychology. https://doi.org/10.1038/s44159-026-00614-6

Image Credits: AI Generated

DOI: 10.1038/s44159-026-00614-6

Keywords: executive function, child development, socioeconomic status, parenting, home environment, schooling, cognitive control, self-regulation, working memory, inhibitory control, cognitive flexibility, intervention

The study, published in the journal Large-scale Assessments in Education, was conducted by Markéta Žáková and Tomáš Lintner of Masaryk University in the Czech Republic. Drawing on PISA 2018 data from more than 600,000 fifteen-year-old students across 75 education systems, the pair set out to answer a deceptively simple question: does it matter which operational definition of academic resilience a researcher uses? The answer, they found, is a resounding yes, with consequences that ripple through prevalence estimates, country rankings, and conclusions about which factors help disadvantaged students beat the odds.

Academic resilience combines two ingredients: adversity, usually measured by socioeconomic status, and positive adaptation, usually measured by achievement. But researchers disagree about how to stitch those ingredients together. One common approach simply identifies students who land in the bottom slice of the socioeconomic distribution and the top slice of achievement, for example the poorest quarter who score in the top quarter. A second approach instead computes what each student’s achievement should be, statistically speaking, given their family background, and flags students who substantially outperform that expectation, an approach known as the residual method. A third treats resilience as a process rather than an outcome, predicting achievement as a continuous variable within the disadvantaged group and never labeling anyone resilient at all.

Žáková and Lintner compared these approaches systematically. They estimated a top-achiever definition, a residual definition computed within each country, and a residual definition benchmarked against an international standard, each at three different threshold levels, 20, 25, and 33 percent, spanning the range most commonly used in the published literature. All told, this produced nine binary operationalizations plus the continuous-outcome model, yielding nearly a thousand country-level analyses. Each estimate was pooled across ten plausible values for achievement and twenty multiply imputed datasets, with standard errors that fully accounted for PISA’s complex two-stage sampling design.

The headline finding is stark. The cross-country mean prevalence of academically resilient students ranged from 7.5 percent under the strictest definition to 35.3 percent under the most inclusive residual benchmark, a nearly fivefold difference computed from identical data. Part of this spread is arithmetic, since looser thresholds mechanically admit more students, but the deeper problem emerges when countries are ranked. Rankings were reasonably stable across thresholds within a given definition, yet they diverged sharply across definitions. The correlation between rankings produced by the top-achiever approach and the residual approaches fell as low as 0.51, and between the two residual variants, which differ only in whether the statistical expectation is local or global, it dropped to between 0.32 and 0.47. A country celebrated as an equity champion under one definition can rank unremarkably under another, and the discrepancy is itself informative about what its disadvantaged students actually do well.

The authors illustrate why with a thought experiment grounded in their results. A lower-performing system with a steep socioeconomic gradient may rank poorly on the top-achiever definition, because few of its disadvantaged students reach absolute excellence, yet rank highly on the within-country residual definition, because modest local expectations are easy to exceed. That same system may then sink again on the internationally benchmarked residual definition, since beating a weak local bar is not the same as meeting a global standard. The researchers argue that resilience rankings should therefore be reported under multiple definitions side by side, as complementary views of equity rather than competing estimates of a single quantity, a practice the OECD itself briefly adopted nearly a decade ago.

What about the protective factors that resilience research is meant to uncover? Here the news is more reassuring at the global level and more troubling at the level of individual countries. When the authors pooled effects meta-analytically across all 75 systems, three motivational constructs drawn from expectancy-value theory, students’ self-perceived reading competence, their enjoyment of reading, and their attitude toward learning, were consistently and positively associated with resilience under every operationalization and threshold, and girls consistently outperformed boys. Read that result alone, and the choice of definition seems inconsequential.

The country-by-country picture tells a different story. When each education system was analyzed separately, as is standard in PISA-based research, findings were consistent across all nine binary specifications in only 20 percent of systems for gender, 40 percent for attitude toward learning, 69 percent for reading enjoyment, and 72 percent for self-perceived competence. Just two of the 75 systems produced fully consistent results for all four predictors. Threshold level alone flipped conclusions in somewhere between 3 and 37 percent of countries depending on the factor. Much of this inconsistency reflects statistical power, since stricter thresholds shrink samples and smaller-effect predictors, notably gender and attitude toward learning, are the least stable. But the practical consequence does not depend on the cause: a researcher studying one country under one definition could legitimately conclude that a factor matters there when a defensible alternative would say it does not.

The most conceptually striking result came from a complementary interaction analysis that requires no thresholds at all. By modeling whether the socioeconomic gradient in achievement flattens at higher levels of each factor, the authors tested what the term protective factor actually implies. The findings complicate comfortable assumptions: the gradient was flatter, not steeper, among students with higher self-perceived reading competence and stronger attitudes toward learning, but it was significantly steeper, not flatter, among students who enjoyed reading more. In other words, reading enjoyment, though positively associated with achievement on average, was linked to wider rather than narrower socioeconomic gaps, a pattern that no threshold-based definition could ever detect. These moderation effects also varied in direction across countries, appearing in only a minority of systems individually.

The authors close with four practical recommendations: match the operationalization to the research question, report sensitivity analyses at a minimum of two thresholds, present cross-country rankings under multiple definitions, and document or pre-register operationalization decisions so findings can be interpreted in light of the choices that produced them. They caution that their analysis is cross-sectional and cannot establish causation, that their predictors were individual-level only, and that PISA’s socioeconomic index has itself attracted methodological criticism. Still, the broader message is hard to escape. Academic resilience, as measured in large-scale assessments, is not a fixed quantity waiting to be counted but a construct whose observed properties depend partly on how it is defined, and both researchers and policymakers ignore that dependence at their peril.

Subject of Research: How operationalization and threshold choices affect estimates of academic resilience and its protective factors across 75 education systems using PISA 2018 data.

Article Title: Academic resilience in 75 education systems: how operationalization and threshold choices shape findings on protective factors

Article References: Academic resilience in 75 education systems: how operationalization and threshold choices shape findings on protective factors. (n.d.). https://doi.org/10.1186/s40536-026-00318-6

Image Credits: AI Generated

DOI: 10.1186/s40536-026-00318-6

Keywords: academic resilience, PISA 2018, socioeconomic status, educational equity, large-scale assessment, protective factors, operationalization, thresholds, student motivation, expectancy-value theory, educational measurement, cross-national comparison

The research team, led by Annabel Wanza Mbithi of Chuka University together with Peter Kimanthi Mbaka and Kenkelvin Kimathi Mbaka, and including Victor Okoth Saoke of the University of Embu, set out to answer a deceptively simple question: what determines how much students say they participate in classroom activities, and do those determinants differ by gender? Participation in this context is not a vague aspiration but a measurable behaviour. It covers the frequency with which students answer questions, contribute to discussions, take part in group work and engage with the practical activities that teachers build into their lessons. Decades of international research have linked such engagement to achievement, retention and eventual transitions into further education and employment, making the classroom voice of individual students a surprisingly consequential variable.

To capture it, the researchers employed a cross-sectional descriptive survey design, a standard tool for taking a snapshot of a population at a single point in time. Working within public day secondary schools, schools that students attend during the day while living at home, they sampled 320 Form Three students, typically the penultimate year of Kenyan secondary education. The sampling strategy was both multistage and proportionate, meaning schools were selected in successive stages and the number of students drawn from each school reflected its share of the total enrolment. This design reduces the risk that a single large or atypical school would dominate the results. Data collection relied on structured questionnaires administered with the help of class teachers, and the study proceeded with ethical clearance from the Chuka University Ethics Committee, a research permit from the National Commission for Science, Technology and Innovation, and authorisation from the County Director of Education for Machakos County.

The analytical centrepiece of the study is a Poisson regression model, a statistical technique chosen because the outcome of interest, counts of participation, is a non-negative integer rather than a continuous measure. Where ordinary linear regression assumes a normally distributed dependent variable, Poisson regression models count data directly, estimating how each explanatory factor changes the expected rate of participation. The researchers screened their candidate predictors for multicollinearity before inclusion, a standard safeguard against the distorted estimates that arise when explanatory variables overlap too heavily. The model was estimated separately for girls and boys, an approach that allowed the team to test not just whether participation levels differed by gender, but whether the underlying economic machinery of participation itself worked differently for each group.

The headline result is that it does. For girls, the strongest and most counterintuitive finding concerned parents’ disposable income: rather than boosting participation, higher disposable income was significantly associated with reduced participation in classroom activities. All other variables in the girls’ model, including the cost of education and family structure, showed no statistically significant effects. For boys, the picture looked markedly different. The cost of education emerged as a significant brake, with rising educational costs reducing the likelihood of participation, while two factors pushed in the opposite direction: students’ expectations of future employment and the number of siblings in the household both significantly increased boys’ participation. The remaining variables in the boys’ model, including parents’ disposable income, showed no significant influence. These gendered patterns held even as overall participation levels themselves also differed between girls and boys.

The counterintuitive income effect for girls invites careful interpretation. In low-resource households, disposable income may flow toward priorities that compete with girls’ schoolwork, or it may correlate with household arrangements in which daughters shoulder more domestic labour regardless of financial comfort. It is also possible that the relationship reflects how income interacts with expectations: families with more resources may channel girls toward different futures, or simply express their support in ways that do not translate into classroom assertiveness. The authors are careful not to overclaim a mechanism, but the practical implication is clear. Financial capacity alone does not guarantee that girls will find their voice in class, and programmes that hand money to households without attending to gender norms inside them may leave the participation gap intact.

The findings for boys are more intuitively legible. When school feels expensive, participation falls, consistent with a long body of evidence showing that educational costs, even in nominally free systems, filter down into engagement as families weigh marginal spending against competing needs. Kenya’s system of day secondary schools nominally benefits from public subsidies, yet levies, materials, uniforms and transport continue to strain household budgets in semi-arid districts like Mwala. The positive effect of sibling count on boys’ participation is intriguing and may reflect peer-like dynamics at home, shared study habits, or the confidence that comes from growing up in a crowded, verbally competitive household. Meanwhile, boys who expect employment after school participate more, exactly as human capital theory would predict: when education is perceived as an investment with a payoff, students invest effort in it.

That theoretical framing runs throughout the paper. The authors situate their work in the human capital tradition that views education as an investment whose returns justify present costs, and in expectancy-value accounts of motivation, which hold that students engage when they both value the outcome and expect to succeed in attaining it. Previous studies, from active-learning classrooms in higher education to analyses of gendered participation in online discussions, have documented persistent gender gaps in who speaks and how often, typically attributing them to classroom demography, confidence and social roles. What this study adds is an economic layer grounded in one of the contexts where those gaps matter most: resource-constrained rural secondary schools where household poverty, family size and labour expectations press directly on adolescent learners.

The policy implications the authors draw are correspondingly targeted. They call for gender-responsive interventions rather than blanket programmes, arguing that what lifts boys’ engagement, such as reducing the visible costs of schooling, may not address the specific barriers facing girls, and vice versa. They point toward strengthened school-based support systems, including guidance and counselling structures that can help students connect classroom effort to credible career pathways, and they urge that career guidance be enhanced so that employment expectations, which appear to energise participation, are realistic and widely shared across genders. For policymakers in Kenya’s Ministry of Education and for the international organisations tracking progress toward the Sustainable Development Goal on quality education, the study offers granular evidence that engagement, not merely enrolment, is where gender inequality now does much of its damage.

The research also speaks to a broader shift in education economics across the developing world. With primary and secondary enrolment having expanded dramatically across East Africa in recent decades, attention has moved from getting children into school to measuring what happens once they are there. Studies of this kind, which treat participation as a countable, modelable behaviour with identifiable economic determinants, are part of a growing toolkit for that task. The authors acknowledge the limits of a cross-sectional design, which captures association rather than proven causation and reflects a single sub-county at a single moment. Data will be made available on request, and the team is transparent that self-reported participation carries its own measurement challenges. Yet within those limits, the message is striking and portable well beyond Mwala: the same classroom contains students whose willingness to engage is being pulled by different economic strings, and any serious effort to close gender gaps in learning must read those strings separately, one group of learners at a time.

The study’s setting matters for interpreting its results. Mwala Sub-County lies in a semi-arid agroecological zone where household incomes depend heavily on rain-fed agriculture, making family finances vulnerable to seasonal shocks that can ripple directly into schooling decisions. Public day secondary schools serve the majority of students in such areas precisely because they allow learners to remain at home, but that arrangement also means classroom engagement is tightly coupled to what happens within the household each evening, from chores to paid work.

Methodologically, the choice to model participation counts separately by gender reflects a growing recognition in education research that pooled samples can mask offsetting effects. A factor that suppresses engagement among girls while boosting it among boys might appear insignificant in a combined model, hiding precisely the dynamics that gender-responsive policy needs to target. The multistage, proportionate sampling of 320 Form Three students strengthens the representativeness of the estimates within the sub-county, though the authors note that self-reported participation and the cross-sectional design limit causal claims.

The emphasis on employment expectations also aligns with expectancy-value frameworks of motivation, which hold that effort follows from believing both that success is possible and that it leads to valued outcomes. In contexts where visible pathways from school to work are unevenly distributed by gender, career guidance becomes not an accessory but a core lever for equitable engagement.

Subject of Research: Gendered socioeconomic determinants of student participation in classroom activities in Kenyan public day secondary schools

Article Title: Gendered determinants of students’ perceived participation in classroom activities: evidence from public day secondary schools in South Eastern Kenya

Article References: Mbithi, A. W., Mbaka, P. K., Mbaka, K. K., & Saoke, V. O. (2026). Gendered determinants of students’ perceived participation in classroom activities: evidence from public day secondary schools in South Eastern Kenya. SN Social Sciences, 6(9), Article 423. https://doi.org/10.1007/s43545-026-01720-1

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01720-1

Keywords: gender differences, classroom participation, Poisson regression, cost of education, employment expectations, Kenya, secondary education, socioeconomic status, girls' education, educational equity, human capital, school engagement

Sleep has increasingly been recognized as a pillar of public health, as central to long-term wellbeing as diet or exercise. Chronic short sleep has been tied to obesity, type 2 diabetes, cardiovascular disease, and impaired immune function, while excessively long sleep and prolonged daytime napping have been associated in prior research with inflammation, metabolic disturbance, and elevated mortality risk. Yet the reasons why sleep quality varies so dramatically across communities have remained elusive. Scientists have long observed that residents of disadvantaged neighborhoods sleep worse on average, but identifying the behavioral machinery behind that association has proven difficult. The new study set out to test whether two of the most consequential daily behaviors—moderate-to-vigorous physical activity and sedentary time spent watching television—act as pathways connecting neighborhood conditions to sleep outcomes.

To do so, the research team, led by Kosuke Tamura of the National Institute on Minority Health and Health Disparities, tapped one of the largest prospective cohort studies ever assembled in the United States. Their analytical sample included 233,335 participants from the NIH-AARP Diet and Health Study, a collaboration between the National Institutes of Health and AARP that has followed hundreds of thousands of older American adults for decades. Participants self-reported their nightly sleep duration, allowing the researchers to classify short sleep as less than seven hours, optimal sleep as seven to eight hours, and long sleep as nine or more hours. They also reported how much time they typically spent napping during the day, with long napping defined as an hour or more, and how much time they devoted to moderate-to-vigorous physical activity and television viewing.

Neighborhood socioeconomic status was measured using a standardized index derived from census variables, a composite that captures the economic and social resources of the areas where participants lived. The researchers then applied formal mediation analysis, a statistical technique that partitions the total association between an exposure and an outcome into direct and indirect components. In this case, the question was whether the relationship between lower neighborhood socioeconomic status and poor sleep traveled through physical activity or television viewing. Because conventional confidence intervals can be unreliable in mediation settings, the team used bootstrap-generated bias-corrected confidence intervals, a resampling method that provides more robust estimates of statistical uncertainty. All models were adjusted for age, sex, racial and ethnic group, education, and marital status, helping to isolate the contribution of the neighborhood itself from individual-level characteristics.

The results were consistent and telling. Lower neighborhood socioeconomic status was associated with short sleep, long sleep, and long napping, and both physical activity and television viewing emerged as significant mediators of all three associations. The mediated odds ratios were modest in magnitude—ranging from 1.002 to 1.011 for the physical activity pathway and from 1.003 to 1.033 for the television pathway, all statistically significant at the five percent level—but the sheer scale of the cohort lends the pattern considerable weight. The strongest mediated effect appeared for long napping through television viewing, hinting that sedentary screen time may be an especially important behavioral link between disadvantaged surroundings and disrupted sleep rhythms. The logic of the mechanism is intuitive: residents of lower-income neighborhoods often have fewer safe parks, sidewalks, gyms, and recreational facilities, which discourages physical activity, while the same environments may encourage more time spent indoors in front of the television—a pattern of behavior that, in turn, displaces sleep, fragments rest, and promotes daytime drowsiness.

Perhaps the most striking aspect of the study, however, was its exploratory examination of racial and ethnic differences. When the researchers stratified their mediation analyses by group, the pathways diverged in revealing ways. Among White adults, lower neighborhood socioeconomic status was associated with short sleep, long sleep, and long napping, mediated through both physical activity and television viewing—the full pattern seen in the overall sample. Among Black adults, the associations were narrower: lower neighborhood socioeconomic status related to long sleep through television viewing, and to long napping through both physical activity and television viewing. Among Hispanic adults, lower neighborhood socioeconomic status was linked to long sleep, mediated through physical activity, while among adults in other racial and ethnic groups, the association appeared only for long napping, mediated through television viewing. These subgroup findings, which the authors describe cautiously as suggestive rather than definitive, underscore that the same neighborhood disadvantage can translate into different behavioral and sleep consequences depending on the population and its social context.

The authors emphasize that the study is cross-sectional, meaning that neighborhood characteristics, behaviors, and sleep were all measured at the same point in time. That design limits causal inference: it is possible, for instance, that poor sleep reduces energy for physical activity or increases time spent passively watching television, rather than the reverse. Self-reported sleep and activity measures also introduce the possibility of misclassification, since people are notoriously imprecise at estimating their own habits. The cohort, moreover, consists predominantly of older adults, and sleep architecture and activity patterns change with age, so the findings may not generalize to younger populations. Residual confounding—by shift work, chronic illness, caregiving responsibilities, or unmeasured neighborhood features such as noise, light pollution, and crime—cannot be ruled out entirely, even with the study’s careful statistical adjustments.

Even so, the scale and consistency of the results make a compelling case that neighborhood disadvantage operates on sleep through modifiable daily behaviors. If the pathways identified here hold up in longitudinal and interventional research, they point to concrete targets for public health action. Investments in safe recreational infrastructure, walkable streets, and community exercise programs could raise physical activity levels in disadvantaged areas, while initiatives to reduce sedentary screen time—particularly prolonged evening television viewing—might simultaneously protect sleep. The authors conclude that efforts to improve lower socioeconomic status neighborhoods in ways that encourage physical activity and reduce sedentary time are warranted to improve sleep health, framing sleep not as a private matter of personal discipline but as an environmental outcome that communities can shape.

The broader significance of the work lies in its reframing of sleep inequality. For years, public health campaigns have urged individuals to sleep more and sit less, as if behavior occurred in a vacuum. This study, leveraging one of the largest cohorts in American epidemiology, demonstrates that the places people live exert a measurable pull on the routines that govern rest. The behavioral chain from neighborhood to activity to sleep offers a mechanism, and mechanisms are the raw material of policy. As cities grapple with entrenched disparities in chronic disease, the humble hours of sleep—and the neighborhood conditions that quietly erode them—may deserve a far more prominent place on the agenda.

Beyond its behavioral findings, the study contributes to a growing literature on social determinants of sleep by treating neighborhood socioeconomic status as an exposure in its own right, distinct from individual income or education. The standardized index drawn from census variables reflects shared community resources rather than personal finances, aligning the work with a broader research movement that examines place-based influences on cardiometabolic and behavioral health.

The use of the NIH-AARP cohort also situates the results within a particularly valuable data resource, one that has enabled investigators to examine how lifestyle and environmental factors relate to disease outcomes across very large samples of older adults. The intramural support from the National Institute on Minority Health and Health Disparities and the National Heart, Lung, and Blood Institute reflects federal interest in understanding how structural conditions shape health behaviors. As an open-access publication, the article allows other researchers to scrutinize the mediation methods and subgroup analyses in full.

Subject of Research: How neighborhood socioeconomic status influences sleep health through physical activity and television viewing in a large U.S. cohort.

Article Title: The association between lower neighborhood socioeconomic status and sleep health mediated by physical activity and TV viewing: Findings from a large U.S. cohort

Article References: Tamura, K., Xiao, Q., Moniruzzaman, M., Deng, Y., Liao, L. M., Jones, R. R., & Powell-Wiley, T. M. (2026). The association between lower neighborhood socioeconomic status and sleep health mediated by physical activity and TV viewing: Findings from a large U.S. cohort. Journal of Activity, Sedentary and Sleep Behaviors. https://doi.org/10.1186/s44167-026-00114-1

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00114-1

Keywords: neighborhood socioeconomic status, sleep health, physical activity, television viewing, sedentary behavior, daytime napping, health disparities, NIH-AARP Diet and Health Study, mediation analysis, racial and ethnic differences, association, between

The study was led by researchers from Geneva University Hospitals and involved data from two major longitudinal cohorts: 8,511 participants in the English Longitudinal Study of Ageing, or ELSA, and 22,605 participants in the Canadian Longitudinal Study on Aging, or CLSA. All participants were between 50 and 85 years old. Rather than examining health at a single point in time, the researchers analyzed repeated measurements collected over several years to estimate how physical abilities changed as participants aged. This longitudinal design allowed the team to distinguish between having a lower level of function and experiencing a faster decline, two processes that are often combined in conventional health comparisons.

Researchers evaluated several indicators of physical capability. Walking speed provided a measure of mobility and overall neuromuscular performance, while grip strength served as an established marker of muscle function, frailty risk, and future disability. Lung function was assessed using forced expiratory volume, or FEV, which reflects how much air a person can forcefully exhale in a specified period. The analysis also considered hearing and self-reported difficulty with everyday activities such as dressing, bathing, and eating. These tasks are important because they capture the practical consequences of ageing: whether people can remain independent, move safely through their environment, and manage basic routines without assistance.

To model the trajectories, the investigators used mixed-effects statistical models. These models can account for repeated observations from the same individual while also estimating average patterns across an entire population. The researchers included age, age squared, and birth year to represent both the gradual and potentially nonlinear nature of ageing. Sex, race, height, wealth, and the interaction between wealth and age were also incorporated. The wealth-by-age interaction was particularly important because it tested whether socioeconomic position was associated not merely with different starting points, but with different rates of decline. Additional analyses adjusted for chronic diseases, body weight, and health-related behaviors including smoking, allowing the researchers to determine whether these factors fully explained the observed inequalities.

They did not. Across both countries, people with less wealth tended to show lower physical function and larger losses over time. The pattern was most apparent for walking speed and the ability to perform daily activities, suggesting that financial disadvantage may accumulate into a growing loss of physical independence. The wealth gradient was also visible in grip strength and lung function, although the size and direction of some associations varied by sex and country. Because the study was observational, it cannot establish that low wealth directly causes faster ageing. Wealth may influence housing, nutrition, working conditions, neighborhood safety, healthcare access, stress exposure, and opportunities for physical activity, while early-life circumstances and unmeasured health factors may influence both wealth and later function.

The contrast between England and Canada was one of the study’s most striking findings. Although both countries provide universal healthcare and have broadly comparable levels of income inequality, the gaps associated with wealth were consistently larger in England for several measures of functional ageing. For walking speed, the researchers estimated an apparent age difference of roughly 15 years between the least and most wealthy groups in England, compared with approximately nine years in Canada. These estimates do not mean that a person’s chronological age has changed, or that every individual in a wealth group follows the same trajectory. Instead, they compare predicted levels of function across socioeconomic groups and express the difference in terms of the age at which similar performance is typically observed.

The researchers also identified important differences between women and men. Among the least wealthy participants, women experienced greater difficulties with mobility and daily activities than men in the same socioeconomic group. At the same time, women in this group showed better lung function than their male counterparts. This divergence illustrates why broad measures of disadvantage can conceal meaningful differences within populations. Physical function is shaped by the interaction of sex, occupational history, health behaviors, disease patterns, social roles, and exposure to economic hardship. The authors describe their approach as intersectional because it examines how these dimensions combine rather than treating all disadvantaged adults as a single, uniform category.

The findings carry implications for public health policy because functional decline is closely connected to falls, disability, institutional care, social isolation, and healthcare use. Interventions that begin only after severe disability appears may miss the period when differences are still modifiable. Policies supporting secure housing, adequate income, nutritious food, safer neighborhoods, accessible transportation, preventive healthcare, and opportunities for lifelong physical activity could help reduce the conditions that accelerate loss of function. The results also suggest that universal healthcare alone may not eliminate health inequalities. Medical treatment is only one influence on ageing; the social and physical environments in which people live may determine whether they can maintain strength, mobility, and independence over decades.

Silvia Stringhini, the study’s senior author, said the larger wealth gaps observed in England were unexpected and that the comparison could not yet explain why the two countries diverged. Stephanie Schrempft, the first author, emphasized that lower wealth was associated not simply with worse health at a given age, but with losing physical independence more rapidly. The authors caution that their analysis could not fully account for childhood conditions or access to private healthcare, and that the results should not be interpreted as proof of a direct causal pathway from wealth to ageing. Further cross-country research is now planned to investigate which structural factors may be responsible for the different trajectories.

The study offers a measurable way to understand socioeconomic inequality as a time-related process. Two people who are the same chronological age may have very different levels of mobility, strength, respiratory capacity, and ability to manage daily life, and those differences can widen as they grow older. By tracking these changes in large populations, researchers can move beyond the question of who is healthier at one moment and ask how social conditions influence the pace of functional ageing. The evidence from England and Canada indicates that reducing inequality will require more than encouraging individual lifestyle changes. It will also require structural policies aimed at preventing disadvantage from becoming a faster loss of physical capability and independence.

Subject of Research: People

Article Title: Socioeconomic inequalities in functional ageing trajectories in England and Canada: A comparative longitudinal cohort study

News Publication Date: August 13, 2026

Web References: https://plos.io/4wbNOyC; https://doi.org/10.1371/journal.pmed.1004833

References: Schrempft S, Vereecke S, Nehme M, Schmidt KL, Guessous I, Kobor MS, et al. (2026). “Socioeconomic inequalities in functional ageing trajectories in England and Canada: A comparative longitudinal cohort study.” PLOS Medicine 23(8): e1004833.

Image Credits: Schrempft S, et al., 2026, PLOS Medicine, CC BY 4.0

Keywords: ageing, healthy ageing, socioeconomic inequality, wealth, physical function, mobility, walking speed, grip strength, lung function, disability, England, Canada, longitudinal study, public health, PLOS Medicine

Natural menopause occurs when menstrual periods stop permanently without surgery, chemotherapy, or other medical intervention. Although menopause typically occurs later in life, premature menopause is generally defined as occurring before age 40, while early menopause occurs between ages 40 and 45. The new study used a broader research definition of early natural menopause, including women whose menopause occurred before age 48. These conditions affect an estimated 6% of women worldwide and have previously been linked to increased risks of cardiovascular disease, dementia, and premature death.

The researchers analyzed health and social data from nearly 20,000 women with early natural menopause. Rather than examining a single social factor in isolation, they created a cumulative measure based on 14 social determinants of health. Participants were then classified into favorable, intermediate, or unfavorable groups according to their overall social circumstances. This approach was designed to capture the reality that disadvantage rarely occurs one factor at a time: unemployment may coincide with lower income, unstable housing, limited education, reduced access to healthcare, and chronic psychosocial stress.

Social determinants of health include the conditions in which people are born, grow up, learn, work, live, worship, spend leisure time, and age. These circumstances can influence exposure to stress, environmental hazards, health information, nutritious food, preventive medicine, and high-quality medical care. They can also shape whether a person is able to follow treatment recommendations or obtain timely evaluation for symptoms. By combining multiple determinants into a single risk profile, the researchers sought to measure the cumulative biological and social pressure that may influence health after early menopause.

Participants were followed for a median of 10.8 years, allowing the investigators to examine health outcomes over a substantial period. The analysis showed that women in more disadvantaged social circumstances experienced significantly worse health trajectories than those with more favorable circumstances. Their risks were elevated for all-cause mortality, meaning death from any cause, and for cardiovascular disease, which includes conditions affecting the heart and blood vessels. The study also identified a pronounced association between cumulative disadvantage and incident dementia, referring to newly diagnosed disease during follow-up.

Among the 14 social variables examined, unemployment showed the strongest independent association with both all-cause mortality and incident dementia. The finding does not establish that unemployment directly causes either outcome, but it highlights employment status as a potentially important marker of broader economic and psychological strain. Loss of work can reduce income, health insurance, social connection, daily structure, and access to services. Long-term unemployment may also contribute to chronic stress and depression, biological processes that have been associated with inflammation, impaired cardiovascular health, and cognitive decline.

Early loss of ovarian function may provide part of the biological context for these findings. Estrogen influences vascular function, lipid metabolism, bone health, and several processes involved in brain maintenance. When estrogen exposure declines earlier than expected, women may spend more years with potential vulnerability to cardiovascular and neurological disease. Social adversity could intensify that vulnerability through factors such as hypertension, poor sleep, chronic inflammation, smoking, limited physical activity, or delayed medical care. The study’s results suggest that biological risk and social conditions may interact rather than operate independently.

The researchers found no significant association between the social-determinants-of-health measures and incident cancer in this group. That contrast is important because it indicates that the effects of social disadvantage were not uniform across every major health outcome. The results instead point to a particularly strong relationship with mortality, cardiovascular disease, and dementia. Because the study was observational and based on statistical associations, the findings cannot prove a direct causal pathway. Differences in health behaviors, access to treatment, pre-existing illness, and other unmeasured factors may also have influenced the results.

The authors argue that social history should become a routine component of care for women with premature or early menopause. A clinical assessment could include employment and financial security, education, housing, transportation, social support, access to healthcare, and exposure to discrimination or chronic stress. Identifying these issues early could help clinicians connect patients with cardiovascular screening, mental-health services, employment or social assistance, and strategies to protect cognitive health. “Disrupting this complex interaction will require a routine, comprehensive assessment of social determinants of health as a fundamental principle” in menopause care, said Stephanie Faubion, medical director for The Menopause Society. The study underscores that early menopause is not only a reproductive milestone but also a potential signal for long-term health monitoring—especially when it occurs alongside persistent social disadvantage.

Subject of Research: People

Article Title: Combined social determinants of health, mortality, and adverse health outcomes in early natural menopause

News Publication Date: 12-Aug-2026

Web References: https://menopause.org; https://menopause.org/wp-content/uploads/press-release/MENO-D-26-00058.pdf

References: Menopause. DOI: 10.1097/GME.0000000000000002866

Keywords: early natural menopause, premature menopause, social determinants of health, unemployment, cardiovascular disease, dementia, mortality, women’s health, socioeconomic disadvantage, healthy aging

Neonatal intensive care is among the most technologically advanced forms of medicine. Infants in NICUs may require mechanical ventilation, incubators that regulate temperature and humidity, continuous heart and oxygen monitoring, intravenous nutrition, specialized medications and repeated laboratory testing. These interventions can be lifesaving, particularly for babies born extremely prematurely or with serious medical complications. Yet the financial consequences of receiving this care are not experienced equally by every household, even when families receive treatment in the same health-care system.

The researchers’ focus is direct medical out-of-pocket spending: the money families must pay themselves for medical services connected to a NICU admission. This can include deductibles, copayments, coinsurance and other forms of cost sharing that remain after insurance has paid its portion. Unlike the total hospital charge or the amount reimbursed by an insurer, out-of-pocket cost reflects the portion that reaches a family’s own budget. For households already coping with an unexpected high-risk birth, even relatively small individual charges can accumulate rapidly.

The study is designed not only to document these expenses, but also to explore the structural forces behind differences in cost burden. In health economics, structural contributions refer to the way institutions and systems distribute risk and resources. Insurance design, employment-linked coverage, household income, geographic location, hospital characteristics and access to public assistance can all affect how much a family ultimately pays. Two infants with similar clinical needs may therefore generate very different financial experiences for their parents, depending on the architecture of coverage surrounding them.

That distinction matters because the effects of a NICU admission are not limited to the newborn’s medical condition. Parents may need to travel long distances to reach a specialized hospital, arrange accommodation near the facility, pay for transportation or meals, and take unpaid leave from work. These expenses may not always appear in estimates of direct medical out-of-pocket costs, but they can intensify the economic shock associated with a prolonged admission. The medical bill is only one component of the broader financial strain that can accompany neonatal illness.

A central question raised by the analysis is whether the families with the fewest financial resources are also the ones most exposed to high cost sharing. A payment that is manageable for a high-income household may consume a substantial share of a lower-income family’s monthly budget. Economists often describe this pattern as a disproportionate cost burden: the absolute amount paid may not be the highest, yet the payment represents a greater fraction of household resources. This distinction can reveal inequities that remain hidden when researchers look only at average dollar amounts.

The findings are expected to be relevant to health-policy debates about medical debt, insurance protection and the financial consequences of premature birth. If structural factors account for meaningful differences in family payments, reducing inequality may require more than improving clinical care. Potential responses could include limits on neonatal cost sharing, stronger protections against unexpected bills, expanded eligibility for public coverage and assistance with transportation or family support services. The analysis may also help hospitals and policymakers identify families at risk of financial hardship while an infant is still receiving care.

The issue has significance beyond individual hospitalizations because NICU care can influence a family’s financial stability long after discharge. Parents may face follow-up appointments, medications, developmental assessments and specialist care for children who experienced complications of prematurity or serious illness. Medical expenses can overlap with reduced work hours, job loss or the need for one parent to become a full-time caregiver. A short period of intensive treatment can therefore produce a long economic aftershock, particularly when families lack savings or paid leave.

By placing family payments at the center of neonatal research, Gorka, Profit and Phibbs emphasize a dimension of NICU care that is often absent from clinical success measures. Survival, complications and length of stay remain essential indicators, but they do not fully describe the experience of families navigating intensive care. Understanding who pays the most, why they pay it and how those payments relate to broader social structures could help redefine quality in neonatal medicine. The study’s message is potentially viral because it connects cutting-edge life-saving technology with a simple but consequential question: when medicine saves a baby, how much of the cost is left for the family to survive?

Subject of Research: Direct medical out-of-pocket costs of neonatal intensive care admissions and structural factors contributing to differences in financial burden among NICU families.

Article Title: Who pays the most for neonatal intensive care? An analysis of the out-of-pocket cost burden borne by NICU families

Article References: Gorka, N., Profit, J. & Phibbs, C.S. “Who pays the most for neonatal intensive care? An analysis of the out-of-pocket cost burden borne by NICU families.” Journal of Perinatology (2026). https://doi.org/10.1038/s41372-026-02869-6

Image Credits: AI Generated

DOI: 10.1038/s41372-026-02869-6

Keywords: neonatal intensive care, NICU, out-of-pocket costs, medical expenses, health-care inequality, premature birth, financial burden, insurance, neonatal health, health policy