Demographic Research

Demographic shifts are reshaping population age structures worldwide, with implications for infectious disease dynamics. Since contact patterns, susceptibility and infectiousness often vary by age, the risk that pathogen introductions initiate a substantial outbreak depends on the populations age distribution and associated behavioural characteristics. We develop an age-structured mathematical model to estimate the risk that a single pathogen introduction leads to sustained transmission (the probability of a major outbreak) under long-term demographic transitions, incorporating changes in age-specific contact patterns and behavioural adaptation. Using the Republic of Korea (projected to become the worlds oldest population by 2050) as a case study, we show that population ageing generally reduces the probability of a major outbreak due to older individuals lower contact rates. However, this effect is attenuated for pathogens with increasing susceptibility or infectiousness with age, and if future older cohorts have higher contact levels than at present (e.g. through extended workforce participation in an ageing society). These findings demonstrate that, while outbreak risks are affected by demographic changes, they are further modified by associated behavioural responses, highlighting the importance of accounting for demographic and socio-behavioural context when assessing future infectious disease outbreak risks. Author SummaryIn the early stages of an infectious disease outbreak, the risk that initial cases lead to a substantial outbreak is shaped by a range of factors including the characteristics of the host population. Demographic changes, such as population ageing, are transforming societies worldwide, yet their implications for infectious disease emergence remain unclear. Here, we show that ageing populations reduce the likelihood that imported infections trigger major infectious disease outbreaks due to lower contact rates between individuals of older ages. However, this effect depends on how susceptibility, infectiousness and host behaviour vary with age. For example, increased social and economic activity among future older adults (due to a higher retirement age) could offset the decrease in the outbreak risk. These findings underscore the need to account for demographic and socio-behavioural factors, in addition to biological factors, when assessing future outbreak risks and designing robust public health strategies, particularly in societies undergoing rapid demographic change.

Evidence from many countries shows that later life cognitive health is shaped by childhood poverty. However, whether it is associated with neurodegenerative biomarkers measured in population settings remains unclear. Methods We conducted a pooled analysis of 5,473 adults aged [&ge;]50 years from Denmark, Sweden and Germany participating in Wave 6 (2015) of the Survey of Health, Ageing and Retirement in Europe. Neurodegenerative biomarkers (neurofilament light chain, glial fibrillary acidic protein and phosphorylated tau) were assayed from dried blood spots. Childhood poverty was constructed as a latent variable from retrospective life histories. Weighted Poisson regression models estimated associations adjusting for age, sex, education, marital status and wealth in later life. Marginal predictions along age and across country were derived. Results Childhood poverty was strongly associated with higher NfL concentrations ({beta}=1.66, p<0.001), but not with GFAP or p-tau217. Predicted values indicated substantially elevated NfL among the childhood poor (10.3 pg/mL vs 2.0 pg/mL for the non-poor). Age profiles showed widening disparities: the childhood poor in midlife exhibited higher NfL levels than the oldest old who grew up not poor. No consistent differences were observed for GFAP or p-tau217. Findings were robust and similar across all three countries with different histories and health systems. Conclusions Childhood poverty is associated with markedly elevated levels of NfL in later life, suggesting long-term neuroaxonal injury consistent with life course shaping of brain health. Moreover, the evidence implies substantial acceleration of neurobiological ageing. These findings emphasise the importance of early-life interventions for brain health in ageing populations.

Background: It is well-established that males have a higher mortality risk than females. Immune cells and their function are known to undergo characteristic changes during aging, and immune cells are known to have sex differences. Immune cells and their function have been linked to mortality risk, but no studies have investigated to what degree, if at all, Immune Cell Biomarkers (ICBs) contribute to the known differences in mortality risk by sex. Methods: Using participant data from the Health and Retirement Study (n = 8,822), we applied multivariable linear regressions adjusting for age, cytomegalovirus (CMV) serostatus, sex, and race/ethnicity to identify differences by sex in 48 immune cell biomarker (ICB, e.g. T cells, B cells, Monocytes, etc.) percentages and counts (measured in 2016). We studied how the associations between ICBs and mortality risk differ by sex using stratified Cox Proportional Hazard (CPH) models. We estimated how inclusion of sex explained the relationship between ICBs and all-cause mortality, and conversely, how inclusion of individual and all ICBs combined explain the relationship between sex and all-cause mortality using multivariable modeling approaches. Results: Differences in ICBs by sex range between 2-38% (39/48 statistically significant). 9 ICBs were significantly associated with mortality risk in the entire sample. While different ICBs were significantly associated with mortality risk in the stratified analyses, particularly with respect to monocyte, B cell, and NK cell populations, adjusting for sex modestly influenced the hazard ratios of the ICBs (sex: 8 ICBs, percent change <5.4%). Furthermore, individual and cumulative contributions of ICBs in explaining the differences in mortality risk by sex were not significant.

Intrinsic capacity (IC) summarizes functional health across multiple domains in healthy aging research, yet evidence on whether IC can be measured and tracked before older age remains limited. Using data from the 1958 British birth cohort at ages 50 and 62 (N = 7,804), we examined whether IC could be measured as a coherent, valid and longitudinally comparable construct from midlife to early old age. A second-order model applied to 30 indicators across sensory, cognitive, physical, psychological and vitality domains supported a five-domain IC construct, with scalar invariance across sweeps enabling comparison of scores over time. IC scores showed graded associations with self-rated health and chronic disease burden in the expected directions. Mean IC declined by 6.3 points on a 0-100 scale from age 50 to 62. These findings establish a basis for studying IC trajectories from midlife, before functional decline is usually clinically apparent.

BackgroundFathers adolescent smoking and overweight affect respiratory health in offspring, suggesting that paternal puberty exposures may influence offspring biological ageing through preconception epigenetic mechanisms. MethodsWe analyzed epigenetic age acceleration using four validated epigenetic clocks derived from blood DNA methylation in 892 RHINESSA offspring (mean age 27 years), linked to parental data on smoking and body shapes from RHINE/ECRHS. Linear regression examined parental smoking initiation ([&le;]15 or >15 years) and overweight body shape (childhood/puberty or age 30) in relation to offspring epigenetic age acceleration, adjusting for offspring sex, age and parental socioeconomic status. Sensitivity analyses accounted for offspring smoking and BMI. ResultsPCHorvath ({beta} 1.53; 95% CI 0.02, 2.9), PCGrimAge (1.21; 0.03, 2.1), DunedinPACE (0.04; -0.001, 0.1) and PCPhenoAge (1.92; -0.3, 4.2) were accelerated in daughters of fathers who started smoking [&le;]15 years. Likewise, PCHorvath (2.25; 1.2, 3.3), PCGrimAge (1.36; -0.2, 2.9), DunedinPACE (0.07; 0.01, 0.1) and PCPhenoAge (3.11; 1.8, 4.4) were accelerated in daughters and sons of fathers who had been overweight in childhood and puberty. These results remained largely unchanged after additional adjustments or stratification in sensitivity analyses. No associations were found for maternal smoking or overweight in puberty. ConclusionsEpigenetic ageing is accelerated in offspring of fathers who smoked or were overweight in puberty, independent of offspring lifestyle. These findings suggest that adolescent boys environment and lifestyle may be critical for next-generation health. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/26352444v1_fig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1eea189org.highwire.dtl.DTLVardef@1af41f4org.highwire.dtl.DTLVardef@1132932org.highwire.dtl.DTLVardef@f5ba2c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Graphical abstract Legend to graphical abstract Figure Fathers smoking or overweight during puberty was associated with accelerated epigenetic aging in offspring (n=892), independent of the offsprings own lifestyle. No such pattern was observed for maternal puberty exposures, or when paternal exposures occurred after puberty. Male puberty may be a critical window for next-generation health. C_FIG

The Asian population in Los Angeles is among the largest and most heterogeneous in the U.S. This is true culturally and health-wise. Older Asians have differing risks for cardiovascular and cardiometabolic disease, depending on their ethnicity, health literacy, and lifestyle choices. This pilot examines several of these factors in a small but diverse group of older Asian adults who attended community health events from 2024-2025. Self-reported and biometric data were collected at five such events hosted by the Asian Pacific Health Corps at UCLA. The pilot generated health literacy and lifestyle (HLL) scores for all participating attendees and explored how they relate to their socio-demographics, healthcare habits, and predictions of their own health data. Overall, there were significantly more females than males with higher HLL scores (p = 0.027). College education (p = 0.028) and "normal" ranges for biometric data (e.g., blood pressure, BMI, blood glucose, cholesterol) were related to higher median HLL scores. With a few exceptions, fewer than 50% accurately predicted their biometric numbers regardless of HLL scores, suggesting a disconnect between perception and reality, and that better provider-patient communication may help foster greater patient understanding about their chronic conditions. These HLL score distributions indicate that educational attainment, better awareness of one's health, and high health literacy are individual factors that may influence older Asians' understanding and potential approach to managing their health conditions.

Mark-recapture analyses on the delineation of natural populations between areas often assume random sampling, with a between/within (B/W) area resighting ratio that declines towards zero as the population components of two areas become more-and-more isolated from one another, with fewer-and-fewer individuals mixing between areas. I use an individual based population model split in two areas to simulate this result, analysing also for the potential effects of the space-time fidelity of the mark-recapture sampling in the areas. I find that small B/W resighting ratios--that traditionally is taken as evidence of population isolation--can easily be observed within a completely mixing population if a random sampling scheme is restricted in space and/or time. Random sampling within restricted areas and time windows is not sufficient to estimate mixing rates and population isolation between areas, unless the resighting rates are analysed by a method that accounts both for the space-time fidelity of the scientific sampling scheme and the space-time fidelity of the distributional behaviour of the individuals in the population.

1Although resources are typically distributed continuously in space, species distributions often organize into discrete clusters. In his seminal paper [36], Turing demonstrated that such clusters can spontaneously arise in population densities, even when populations evolve in environments with continuously varying conditions. This phenomenon is known as Turing instability. In this work, we focus on two models grounded in population dynamics: a one-dimensional model based on the nonlocal Fisher-KPP equation, and a two-dimensional model involving an environmental gradient. We show that phenotypic clusters (sometimes referred to as "species") emerge in these models. We prove that they do not emerge because of Turing instability, but because of stochasticity, and that they disappear when stochasticity is reduced. First, for both models, we start our simulations with initial populations uniformly distributed in the state space. We show that phenotypic clusters quickly emerge and that the distances between them depend on the population size, that is, on the degree of stochasticity. Next, we start from already clearly defined phenotypic clusters. We identify three regimes in the connection between population size, the initial distances between clusters, and the distances between clusters at equilibrium. Last, on the two-dimensional model, we relax the hypothesis of complete clonality by varying the effective recombination rate, explore its effect on phenotypic clustering, and show that phenotypic clustering decays drastically with slight recombination.

Biomarker measurements can assist with disease diagnosis and the assessment of disease risks, with the most recent measurements usually used by disease-risk models. However, a growing number of studies suggest that in addition to a biomarkers value, its inherent variability, estimated from several measurements over many days or years in an individual, can convey independent prognostic information about disease risks. Variance estimates require an individuals biomarker data to have been measured a sufficient number of times, ideally across a long time period, and are usually only available in a hospital setting or clinical trial. Furthermore, a single biomarker measurement will involve a combination of measurement-error, natural short-term variation over a daily time-period, variation over time periods of weeks and months, and slower age-dependent changes over several years. This paper develops a statistical method that accounts for these latter concerns, and applies it to Clinical Practice Research Datalink (CPRD) data collected by UK General Practitioners. It studies the associations between cardiovascular health outcomes and the within-person variances of eight routinely measured biomarkers. This involved Sequential Monte Carlo modeling to convert an individuals biomarker measurements (collected over months or years), into estimates for the biomarkers mean, linear age-dependent slope, within-person variance, and a variance due to variation on a daily time period or measurement errors. The result is a proof-of-principle that UK primary care Electronic Health Records (from CPRD) can be effectively used for this purpose. After adjusting for mean biomarker values, clear associations were found between mortality or cardiovascular disease risks and within-person variances for 6 of 8 biomarkers.

Sex work is diverse and includes a broad range of people and settings. Over the last thirty years, a large proportion of public health emergencies of international concern (PHEIC) have involved infections transmitted through sexual or close contact and in sexual networks (WHO 2024). Sex workers can face increased disadvantage in relation to these public health emergencies. Given the significant health inequalities sex workers can face, they should be eligible to receive targeted and tailored health support to reduce health protection risks (Hester 2019; Jeal and Salisbury 2004a). However, they are often not explicitly eligible for targeted and tailored support due to a lack of information on incidence, prevalence of disease, and even more basic data such as reliable estimates of the number of sex workers in the UK. Accordingly, the aim of this paper is to determine a population size estimate, with uncertainty, that is more robust than those currently available. In this study, we apply Bayesian Evidence Synthesis to bring together historic estimation efforts with recent ONS National Population Estimates and Genito-Urinary Medicine Clinics Attendance Data (GUMCAD) from the UK Health Security Agency (UKHSA). A key feature of our model is the embedding of uncertainty from each input study in model priors, hence propagating it through to our final estimate. The Bayesian evidence synthesis model estimated a total of 84,000 sex workers in the United Kingdom (95% credible interval: 49,000-130,000), representing 0.121% of the current UK population.

Infectious disease time series often show signs of epidemic transitions, such as the peaks and troughs of the time series. In these time series, key system parameters can lead to catastrophic changes in the dynamical system behaviour (often called critical transitions). Modellers have increasingly shown that early warning signals can anticipate these transitions, both critical and non-critical, in infectious disease time series. Existing methods, however, generally focus on univariate time series data, or ignore spatiotemporal patterns that may be present as a disease spreads through a population. Recent ecological literature developments expand existing temporal and spatial methods to consider the covariance matrix of multiple, related time series. However, many of these proposed signals still make an assumption of stationary time series/system equilibrium. Whilst often true in ecological modelling, disease systems are seldom at equilibrium. In this paper, we propose the usage of the eigendecomposition of the non-stationary covariance matrix as a more suitable early warning signal for epidemiological data. We first analyse the expected trends in the eigenvalues and eigenbasis of the covariance matrix on approach to a transition. Next we apply these methods to a spatially-structured susceptible-infectious-recovered model to explore how the eigenbasis may provide extra information to modellers. Finally, we test these methods on SARS-CoV-2 case data during the 2020-2021 pandemic period in England.

This report presents findings from a baseline cross sectional survey of autistic adults and adults with intellectual and developmental disabilities (IDD) connected to Our Stomping Ground (OSG), a nonprofit organization in northern Virginia committed to supported independent living. The survey was administered in 2022 and 2023 as the first wave of a planned longitudinal study, with the primary goal of establishing a comparable starting point between two groups: adults who were living, or preparing to live, independently in an OSG apartment building, and adults with disabilities who were continuing to live at home with family. A total of 76 adults completed the survey out of 98 potential participants. The two groups were well-matched at baseline across a wide range of characteristics, which is exactly what a sound longitudinal design requires. This comparability means that when follow up data are collected, any observed differences between the groups can be more confidently attributed to the experience of independent living rather than to pre-existing differences. These findings provide the empirical foundation for the longitudinal phase of this study and offer a meaningful snapshot of the health, well-being, and support needs of autistic adults and adults with IDD at a pivotal life stage.

Lower cognitive ability measured in childhood or late adolescence has been consistently associated with higher mortality risk across adulthood. However, this evidence largely relies on single assessments, leaving it unclear to what extent mortality risk reflects cognitive differences established early in life versus developmental divergence during adolescence - a period of substantial neurocognitive plasticity. Using two nationally representative Swedish cohorts comprising 9,412 males born in 1948 and 1953, we linked cognitive ability assessed in primary school at age 13 years and military conscription at age 18 years to all-cause and cause-specific mortality recorded in nationwide registers through 2025. We decomposed late-adolescent cognitive ability into childhood cognitive level and adolescent cognitive change and evaluated their independent associations with mortality. Childhood cognitive level (HR = 0.81; 95% CI, 0.78-0.85) and adolescent cognitive change (HR = 0.84; 95% CI, 0.79-0.89) independently predicted lower mortality risk, also after adjustment for parental education. Childhood cognitive level and adolescent cognitive change showed partially distinct cause-specific patterns. Childhood cognitive level was most strongly associated with mortality from intrinsic causes, whereas adolescent cognitive change showed relatively stronger associations with external causes, particularly accidental deaths. Although adolescent cognitive change was associated with psychosocial factors including education and psychiatric diagnosis at conscription, its association with mortality persisted after adjustment for these factors. These findings suggest that cognitive development during adolescence carries independent prognostic information regarding long-term survival beyond cognitive level established by late childhood, highlighting adolescence as a consequential period for lifelong health.

Atherosclerosis is a systemic vascular process linked to cardiovascular, cognitive and renal outcomes. DNA methylation (DNAm)-based scores of atherosclerosis may capture cumulative biological processes underlying vascular aging. Here, we examined associations of DNAm scores for coronary artery calcification (DNAm-CAC) and carotid plaque (DNAm-cPlaque), derived from a large study of imaging-based subclinical atherosclerosis, with prevalent and incident outcomes in two population-based cohorts of older adults: the Health and Retirement Study (HRS; n = 3,875) and The Irish Longitudinal Study on Ageing (TILDA; n = 487). Higher DNAm scores were associated with adverse cardiometabolic profiles and socioeconomic indicators. In HRS, higher DNAm-CAC was associated with prevalent cardiovascular disease (odds ratio per SD, 1.16; 95% confidence interval (CI), 1.07-1.26), lower cognitive function ({beta} = -0.50, 95% CI -0.68 to -0.32) and lower estimated glomerular filtration rate (eGFR; -1.7 ml min-1 1.73 m-2, 95% CI -2.6 to -0.8) in unadjusted models. After adjustment for demographic and clinical risk factors, DNAm-CAC ({beta} = -0.29, 95% CI -0.46 to -0.13) and DNAm-cPlaque ({beta} = -0.24, 95% CI -0.42 to -0.06) remained associated with lower cognitive function, and DNAm-cPlaque was associated with incident cognitive impairment or dementia (hazard ratio per SD, 1.16; 95% CI, 1.01-1.32). Associations were attenuated after further adjustment for race/ethnicity and socioeconomic indicators. In TILDA, higher DNAm-cPlaque was associated with worse cognitive performance (incidence rate ratio, 1.11; 95% CI, 1.01-1.21), increased risk of incident cardiovascular disease (hazard ratio, 1.18; 95% CI, 1.00-1.42) and lower eGFR, with consistent associations observed for DNAm-CAC. These findings suggest that DNAm-based scores of atherosclerosis capture systemic vascular processes linked to multiple age-related outcomes across populations. Further work is needed to clarify the biological pathways reflected by these scores and their relation to cumulative and socially patterned vascular risk.

Abstract Importance: Irregular sleep-wake patterns have been associated with poor health and cognitive outcomes, yet evidence linking 24-hour sleep-wake regularity to cognitive decline or dementia remains inconsistent. Particularly, regularity can be measured as regularity of rest-wake, sleep-wake or overall 24-hour activity, but it is unclear which aspects are most relevant for cognitive aging. Objective: To assess associations of rest-wake, sleep-wake, and 24-hour activity regularity with cognitive decline and dementia risk. Design: Observational prospective study comprised of six US and European cohorts: MrOS (sleep study between 2003-2005, mean follow-up: 7.1 years), Rotterdam Study (2004-2007, 11.6 years), MESA (2010-2013, 8.2 years), MAP (2005-2018, 7.2 years), Whitehall II (2012-2013, 6.9 years), and UKB (2013-2015, 7.9 years). Setting: Cohort-specific estimates were pooled using random-effects meta-analysis. Analyses were done between June 2025 and March 2026. Participants 74,733 dementia-free adults with multi-day actigraphy were included across cohorts: MrOS (age: 67-96 years, female:0%), MESA (54-95y, female:54.6%), Rotterdam Study (46-98y, female:55.0%), MAP (56-100y, female:77.1%), Whitehall II (59-83y, female:25.9%), and UKB (55-78y, female:55.5%). Exposure: Day-to-day rest-wake regularity (Rest Regularity Index, RRI), day-to-day sleep-wake regularity (Sleep Regularity Index, SRI), and 24-hour activity regularity (Interdaily Stability, IS) were derived from multi-day actigraphy. Main Outcome: Outcomes were risk of dementia and changes in global cognition. Results: Across six cohorts, 1,906 dementia cases occurred among 74,733 participants. After adjusting for demographics, health behaviors, depressive symptoms and cardiovascular comorbidities, each 1-SD higher regularity score was associated with an 9-14% lower dementia risk (pooled hazard ratios: RRI 0.86 95%CI: [0.79-0.95]; SRI 0.87[0.79-0.97]; IS: 0.91[0.88-0.95]). Associations were approximately linear. Age-stratified analyses showed directionally stronger associations among adults aged < 65, although meta-regression did not support an interaction(p > 0.55). Greater regularity was associated with modestly slower decline in global cognition (pooled {beta} per 1-SD higher score of RRI per year: 0.003, 95%CI [0.001-0.006]). Conclusions & Relevance: Greater regularity of rest-wake, sleep-wake, and 24-hour activity rhythms was associated with lower dementia risk and modestly slower global cognitive decline. These findings suggest that 24-hour sleep-wake regularity is a relevant behavioral marker of cognitive aging and may inform future efforts to identify or intervene on early risk.

Minimum viable populations (MVPs) are population levels large enough to surmount risk from demographic, environmental, and genetic stochasticity. MVPs are estimated by biologists to guide conservation practices. However, MVPs are generally estimated for a target population without regard for how they interact with intra- and inter-species population dynamics in the broader ecological community. Thus, how and why population dynamics interact with MVPs imposed by conservation biologists remain unclear. When MVPs are imposed on a continuous population model, traditional analyses fail to capture the range of possible outcomes those MVPs create. Here, we describe viability space decomposition (VSD) as a mathematical tool to systematically analyze the potential crossing of MVPs during population dynamics. We demonstrate that different extinction and survival outcomes can be recovered from a model with imposed MVPs using three VSD concepts in junction with a traditional phase portrait: mortality manifolds which separate conditions that lead to different existential outcomes, ordering manifolds which determine the order of extinction events for multiple populations, and collapse manifolds which determine the survival or extinction of one species given the loss of another. We employ these methods with a standard consumer-resource model, and the methods can be scaled to systems with more species. VSD is a useful tool for conservation biologists and community ecologists concerned with boundary crossing problems in any dynamical system.

Background: The Dementia Supporter Initiative is a national public education program in Japan that aims to foster positive attitudes and appropriate understanding of dementia to support people with Alzheimer's disease and related dementia in the community. However, its influence on the community as a whole remains unclear. Objective: This study examined the relationship between dementia supporter training and residents' attitudes and recognition related to dementia at the municipal level. Methods: This ecological cross-sectional study linked municipal-level data from the Japan Gerontological Evaluation Study 2022 wave with publicly available information on the number of dementia supporters. Residents' beliefs and attitudes toward dementia and recognition of dementia consultation services were assessed by mail questionnaires and aggregated at municipal level. The proportion of dementia supporters in each municipality was calculated as of September 2022. Results: Data from 69 municipalities were analyzed. The mean proportion of dementia supporters was 13.47% (2.62-44.85). A higher proportion of dementia supporters was positively correlated with community support-seeking for a family member with dementia (r = 0.328) and recognition of dementia consultation services (r = 0.501). Regression analysis adjusted for municipal covariates also showed their positive associations (per 10-percentage-point increase: coef. = 1.44, p = 0.047; coef. = 3.12, p < 0.001, respectively). No associations were observed with residents' positive attitudes and appropriate understandings of dementia. Conclusions: Wider dissemination of dementia supporters may contribute to better recognition of community support resources, but may be insufficient to influence broader public attitudes and understanding of dementia at the community level.

INTRODUCTION: Postmenopausal estrogen decline may contribute to Alzheimer's disease (AD) risk, but longitudinal evidence linking circulating estrogens to cerebrospinal fluid (CSF) biomarkers is lacking. METHODS: We analyzed 866 female participants from the European Prevention of AD Longitudinal Cohort Study with baseline serum estradiol and estrone measured by liquid chromatography tandem mass spectrometry and repeated CSF measurements of amyloid-beta (A{beta})42, phosphorylated (p) Tau181, and total (t) Tau. RESULTS: Neither estradiol nor estrone was associated with longitudinal A{beta}42. Higher estradiol was associated with lower baseline tau and slower tau increases over time. Baseline estradiol-tau associations were stronger in apolipoprotein E (APOE) {epsilon}4 carriers, though APOE{epsilon}4 did not modify longitudinal associations. Amyloid positivity did not moderate hormone-tau associations but was associated with steeper tau increases over time. Estrone showed no significant associations. DISCUSSION: These findings suggest a more consistent relationship between estradiol and tau-related rather than amyloid-related pathology.

Background: Circadian rest-activity rhythms weaken with age, but whether sleep disorders modify this trajectory is unknown. Methods: We analyzed wrist accelerometry data from 4,386 participants aged 6-80 years in the 2011-2012 National Health and Nutrition Examination Survey (NHANES). Circadian features were extracted using cosinor analysis and nonparametric methods; a Circadian Disruption Index (CDI) was constructed from five standardized components. Survey-weighted regression with natural cubic splines and Wald F-tests tested age-by-sleep-disorder interactions using Taylor series linearization for variance estimation. Results: Doctor-diagnosed sleep disorder (N = 360, 8.2%) was associated with significantly different age-related trajectories of amplitude (F(2,17) = 11.24, p = 0.0008) and MESOR (F(2,17) = 8.22, p = 0.0032), both surviving Bonferroni correction (p < 0.006). CDI was higher in those with a sleep disorder (0.290 vs. 0.131, p < 0.001) and was independently associated with higher BMI (beta = 1.33 kg/m2, p < 0.001), higher HbA1c (beta = 0.089%, p = 0.004), greater diabetes prevalence (beta = 3.8 percentage points, p < 0.001), and worse depressive symptoms (beta = 0.43 PHQ-9 points, p = 0.020). Sensitivity analyses using a broader sleep problem exposure did not replicate these interactions. Conclusions: Doctor-diagnosed sleep disorders are associated with an altered age-related decline in circadian amplitude and mean activity level. CDI was independently linked to cardiometabolic and depressive outcomes, supporting a mechanistic connection between clinically significant sleep pathology and circadian disruption across the lifespan.

Background The study aimed to estimate healthcare costs associated with malnutrition in Swedish older adults. Methods We conducted a cohort study using data from the population-based Swedish National Study on Aging and Care in Kungsholmen (SNAC-K, N = 2982), a geriatric inpatient cohort of complex patients (N = 7680), and a cohort of individuals with cognitive impairment from the Swedish Register of Cognitive/Dementia Disorders (SveDem, N = 64192). At risk of malnutrition and malnutrition were ascertained by the Mini-Nutritional Assessment in SNAC-K and the geriatric inpatient cohort. In SveDem, body mass index was used for identifying malnutrition. Healthcare resource use was derived from regional and national registers. Associations between malnutrition and healthcare costs in 2024 Swedish kronor (SEK) were analyzed using two-part models and generalized linear regression models, adjusting for demographic and clinical factors. Findings In the community, at risk of malnutrition and malnutrition were associated with an increase in annual healthcare costs of 2267 SEK (95% CI: 64,4469) and 1846 SEK (95% CI: -6802,10493), respectively. In geriatric patients, healthcare costs over 6 months in individuals at risk of malnutrition and individuals with malnutrition were 60205 SEK (45613,74798) and 86619 SEK (68362,104875) higher than those without malnutrition. In people with cognitive impairment, malnutrition was associated with higher annual healthcare costs (22170 SEK, 95% CI: 15152,29188). Interpretation Both at risk of malnutrition and malnutrition are associated with higher healthcare costs in Swedish older adults. The study findings are important for informing future economic evaluations of malnutrition interventions in Swedish older adults.