Journal of Biological Rhythms

BackgroundThe mechanisms underpinning associations between sleep and psychiatric conditions are poorly understood, partly due to challenges with longitudinal sleep studies outside the laboratory. Children and young people with rare genetic conditions caused by micro-deletions or -duplications (Copy Number Variants or CNVs) have increased risk of disrupted sleep and poorer neurodevelopmental (ND) outcomes. The Sleep Detectives study aims to investigate this by tracking behavioural and neurophysiological signatures of sleep health in young people with ND risk or ND-CNVs. To optimally achieve this, we have worked with families with ND-CNVs and charity partners to co-design our tools, methods, study protocol, and materials. MethodWe established a Lived Experience Advisory Group (LEAP) with nine parents and 13 children and young people with ND-CNVs, alongside representatives of UK charities Max Appeal and Unique. Together, the research team and LEAP co-designed two in-person family workshops in which we collected feedback on the acceptability of sleep monitoring devices, the design of bespoke cognitive tasks, and overall study protocol. Informal interviews and surveys were conducted with LEAP members and researchers, to enable the team to reflect and learn from their Patient/Public Involvement (PPI) experiences. ResultsKey outputs included pre-workshop invitation and briefing materials and insights that iteratively refined the main study design, including the need for flexibility to increase accessibility, selection of sleep devices, customisation of cognitive tasks, and choice of language in documents. The PPI process was highly valued by LEAP members, workshop attendees, and the research team. One investigator described the PPI work as "reinvigorating my love of research by helping me focus on science that matters". Participating families also established peer support networks. ConclusionsInvolving families affected by ND-CNVs in co-designing the Sleep Detectives study maximised opportunities for acceptability, accessibility and scalability. The research team gained inspiration and deeper understanding of the impact of ND-CNVs on families. Families gained awareness about research, established connections with each other and peer support, and were enthusiastic about future research involvement. This experience empowered families to engage more deeply with the research process and helped the PPI work to be more impactful and inclusive. Plain English summaryChildren and young people with rare genetic conditions caused by small deletion or duplication of genetic material are more likely to experience sleep difficulties such as insomnia, restless sleep, and tiredness. They also show an increased likelihood of neurodevelopmental conditions such as learning disability and autism, and mental health issues such as anxiety. The Sleep Detectives team wanted to explore how these genetic conditions affect childrens sleep, cognition and psychiatric health. To make sure that the project design was well suited to the children and young people that would be invited to participate, the team worked closely with families to design the study. Parents and caregivers of affected children and young people were invited to join a Lived Experience Advisory Panel (LEAP), together with charity representatives and Sleep Detective researchers, to co-design two hands-on workshops, and advise on study design. Children and young people and parents/caregivers attending the workshops tried out and provided feedback on tools and devices that the research team were developing. They also advised on the arrangements and support families might need whilst taking part, and on the study protocol. This collaborative approach helped ensure the study design was optimally suited for the recruitment and participation of children and young people and their families. This report documents our public involvement work for the Sleep Detectives study, illustrating the difference the partnership between researchers and families has made to the project, and the wider benefits for all concerned.

BackgroundIn long-term care facilities (LTCFs), close-contact identification often relies on staff recall and monitoring records because residents may be unable to self-report reliably. How these different record-generation processes relate to proximity-based sensor measurements in routine LTCF workflow remain unclear, and how such differences may influence contact-based decision-making in outbreak response is not well understood. MethodsWe conducted a five-day observational study in a Japanese LTCF using ultra-wideband (UWB) indoor positioning. Twenty-seven participants wore UWB tags, including 16 residents and 11 staff members; 10 staff members completed questionnaires. We compared UWB-derived proximity with questionnaire-derived contacts from staff self-report and monitoring-based proxy records, and assessed directional discrepancies under multiple distance-time thresholds. ResultsQuestionnaire-based records and UWB-derived proximity showed different patterns of discrepancy across contact types. Within this facility, resident-related monitoring-based proxy records showed relatively small directional discrepancies, whereas staff self-reports tended to identify additional resident-staff contacts under the baseline threshold ([≤]1.0 m for [≥]15 min). Several alternative thresholds were associated with discrepancies closer to zero than the baseline, although the apparent ranking varied by summary metric. ConclusionsIn this single-facility observational study, different contact-list generation processes were associated with different patterns of discrepancy relative to a proximity-based operational measure. These findings support interpretation in terms of workflow-specific contact-list generation rather than a single universally optimal threshold and may help inform facility-level review of contact identification practices in LTCFs. These findings support aligning contact identification strategies with facility-specific workflows to improve the feasibility and effectiveness of IPC practices in LTCFs.

Study ObjectivesTo evaluate wearable sleep staging across sleep apnea severity, including very severe sleep apnea defined as an apnea-hypopnea index (AHI)[≥] 50 events/h, and to assess how training-set composition affects performance in this subgroup. MethodsWe analyzed 552 overnight recordings, 318 from the Sleep Lab Dataset and 234 from the Hospital Dataset. In the Hospital Dataset, 26.5% had very severe sleep apnea. We developed a deep learning model for sleep staging using RR intervals from wrist-worn photoplethysmography and three-axis accelerometry. Baseline performance was assessed by cross-validation under 5-stage and 4-stage staging. We examined night-level associations with AHI severity. We also compared the baseline model with an ablation model trained on the same number of recordings but with more Sleep Lab Dataset and lower-AHI Hospital Dataset recordings, evaluating both models in the very severe subgroup. ResultsIn 5-stage classification, Cohens kappa was 0.586 in the Sleep Lab Dataset and 0.446 in the Hospital Dataset. Under 4-stage staging, the gap narrowed, with kappa values of 0.632 and 0.525, respectively. In the Hospital Dataset, performance declined with increasing AHI severity. Among 62 recordings with very severe sleep apnea, reducing high-AHI representation in training lowered kappa from 0.365 to 0.303. ConclusionsWearable sleep staging performance declined across greater sleep apnea severity in this clinical cohort. Clinical utility may benefit from training data that better represent the target severity spectrum and from selecting staging granularity to match the intended use case. Statement of SignificanceRepeated laboratory polysomnography is impractical for long-term sleep apnea management. Wearable sleep staging could support scalable monitoring, yet its reliability in clinically severe sleep apnea has remained unclear. This study developed and evaluated a wearable sleep staging approach in both sleep-laboratory and hospital cohorts. The hospital cohort included many severe and very severe cases. Performance was lower in the hospital cohort and declined with greater sleep apnea severity. A coarser staging scheme reduced the gap between cohorts, and models trained without representative very severe cases performed worse in this target population. These findings highlight the value of severity-aware model development and motivate future multi-night home validation with reliability cues.

Loneliness--the perceived discrepancy between desired and actual social connection--is a common and aversive psychological state associated with a range of adverse health outcomes. Several theoretical models suggest that these associations may operate partly through health behaviors. In this preregistered study, we used data from the All of Us Research Program to evaluate associations of loneliness and functional rurality (FR), a study-specific contextual index of reduced neighborhood accessibility, with Fitbit-derived physical activity and sleep outcomes. Final samples included 16,912 participants for physical activity analyses and 13,937 for sleep analyses. In adjusted models, higher FR was associated with greater loneliness ({beta} = 0.061, 95% CI [0.045, 0.077], p = 9.63 x 10-14). FR and loneliness were independently associated with fewer daily steps and lower moderate-to-vigorous physical activity. Loneliness was also associated with shorter sleep duration, greater sleep duration variability, higher odds of short sleep, and higher odds of low sleep efficiency. FR was not associated with sleep duration or sleep duration variability but showed a small positive association with mean sleep efficiency and lower odds of low sleep efficiency. Interaction analyses provided little evidence that FR modified the associations of loneliness with most outcomes, although the FR x loneliness interaction was significant for sleep duration variability, indicating that loneliness was more strongly associated with irregular sleep duration in higher-FR contexts. Sensitivity analyses using stricter valid-day thresholds, winsorization, quartile-based exposure coding, and a backward 30-day window yielded directionally similar findings. These results suggest that FR and loneliness are independently associated with lower physical activity, whereas loneliness shows a more consistent relationship with adverse sleep patterns.

ObjectiveLong term monitoring of obstructive sleep apnea (OSA) severity may be relevant for several clinical applications. We developed a method for estimating the apnea-hypopnea index (AHI) using wrist-worn, reflective photoplethysmography (PPG). ApproachA neural network was developed to detect respiratory events using PPG and PPG-derived sleep stages as input. The development database encompassed retrospective data from three polysomnographic datasets (N=3111), including a dataset with concurrent reflective PPG recordings from a wrist-worn device (N=969). The model was pre-trained with (transmissive) finger-PPG signals from all overnight recordings and then fine-tuned to wrist-PPG characteristics using transfer learning. Validation was performed on the test portion of the development set and on a fourth, external hold-out dataset containing both wrist-PPG and PSG data (N=171). Performance was evaluated in terms of AHI estimation accuracy and OSA severity classification. Main ResultsThe fine-tuned wrist-PPG model demonstrated strong agreement with the PSG-derived gold-standard AHI, achieving intra-class correlation coefficients of 0.87 in the test portion of the development set and 0.91 in the external hold-out validation set. Diagnostic performance was high, with accuracies above 80% for all severity thresholds. SignificanceThe study highlights the potential of reflective PPG-based AHI estimation, achieving high estimation performance in comparison with PSG. These measurements can be performed with relatively comfortable sensors integrated in convenient wrist-worn wearables, enabling long-term assessment of sleep disordered breathing, both in a diagnostic phase, and during therapy follow-up.

Objective: Skin sympathetic nerve activity (SKNA) has emerged as a promising non-invasive surrogate measure of sympathetic drive, but its relevant physiological characteristics remain ill-defined. This observational study aims to investigate its regulatory patterns during rest and Valsalva maneuver (VM) in healthy participants. Method: Using a two-layer strategy integrating signal analysis and physiological modelling, we analyzed data recorded from 41 subjects performing repeated VMs. The observational layer includes time-domain feature comparisons using linear mixed-effect models, and time-varying spectral coherence analysis. The mechanistic layer proposes a mathematical model to investigate whether baroreflex and respiratory modulation are sufficient to reproduce the observed HR and average SKNA (aSKNA) dynamics. Main Results: Mean integrated SKNA (iSKNA) showed more significant change than HRV for VM induced effects. We also found mean iSKNA increase during VM varies with BMI and sex. The coherence analysis indicated that iSKNA strongly synchronized with EDR under resting conditions. The proposed model successfully reproduced main characteristics of aSKNA dynamics, yielding a high median Pearson correlation coefficient of 0.80 ([Q1, Q3] = [0.60, 0.91]). In contrast, HR dynamics were only partially captured, with a median PCC of 0.37 ([Q1, Q3] = [0.16, 0.55]). These results likely suggest SKNA provides a more direct representation of sympathetic burst dynamics during VM in healthy subjects. Significance: This study provides convergent evidence that SKNA reflects known autonomic regulatory influences in healthy subjects. These findings strengthen the physiological interpretability of SKNA while clarifying its appropriate use as a practical biomarker of sympathetic function.

BackgroundHigh workload among healthcare workers has increasingly been correlated with poor patient outcomes, inefficient operational and financial outcomes, and burnout. Despite growing literature exploring causes of attending physician workload, there is limited understanding of trainee-specific measures. ObjectiveWe aimed to characterize elements contributing to trainee workload and perceived challenges and satisfiers to the trainee workday as a foundation for better understanding and measuring trainee work experience. MethodsInternal Medicine and Medicine-Pediatrics residents at an academic medical center were invited to participate in focus groups discussing contributors to inpatient workload and work experience between March and April 2024. A qualitative content analysis identified key metrics of trainee workload and work experience, which were then consolidated into overarching domains. A structured, multi-round rating process ranked the perceived relevance of each metric. ResultsTwenty residents participated across six focus groups. Analysis of focus groups yielded 297 workload metrics across 28 unique domains. Seventeen domains had metrics identified as highly relevant (median 6-7; IQR < 1) including autonomy, communication, disruptions, task switching, documentation, emotional burden, patient factors, professional fulfillment, rounding, teaming, and work-life balance. ConclusionsResident physicians highlighted complex interactions between clinical factors, work design, and psychosocial dynamics that contribute to their sense of workload. This creates opportunities to develop unique measures of workload to understand the trainee experience better. Further studies are needed to capture the generalizability of these findings and the relationship between these workload domains and patient, organizational, and trainee outcomes with the aim of implementing evidence-based work design.

Background/Objective: Common measures of physical activity (PA) based on duration and intensity do not fully capture its complexity. Adding additional PA components of muscle strength, mechanical strain, and turning actions, can provide a more complete view of activity behavior. Furthermore, PA behaviors differ between men and women. Therefore, the goal of this study is to identify and cluster similar long-term PA patterns over time for each PA component, examined separately for men and women. Methods: We used data from 4963 participants (52% women; mean age 66 years, SD = 8.6) of the Longitudinal Aging Study Amsterdam (1992 to 2019). PA component scores were assigned to self-reported activities, and Sequence Analysis with Optimal Matching was used to identify and cluster similar activity patterns over a period of 10 years, separately for each component and stratified by sex. Results: PA components varied by sex and displayed a unique mix of trajectories, including predominately low, medium, or high activity, increasing or decreasing patterns, and trajectories characterized by early or late mortality. Importantly, trajectories remained independent, indicating that changes in one PA component were not linked to changes in others. Conclusion: Older men and women follow distinct and independent long term PA trajectories across components, underscoring that PA behaviour cannot be described by a single dimension. Significance/Implications: The observed independence and heterogeneity of trajectories suggest that muscle strength, mechanical strain, and turning actions capture meaningful and distinct aspects of PA that are not reflected by traditional measures alone. Future PA-strategies could incorporate these dimensions and acknowledge sex-specific patterns to better reflect natural movement. The independence of components suggests that future interventions should target multiple dimensions, as changes in one component may not translate to others. Such an approach may support more tailored and sustainable PA interventions in later life.

Introduction: Herpes simplex virus type 1 (HSV-1) is highly prevalent worldwide, making accurate serological testing essential for both clinical diagnosis and epidemiological surveillance. Automated chemiluminescent immunoassays (CLIAs) offer operational advantages over enzyme-linked immunosorbent assays (ELISAs); however, their diagnostic performance relative to Western blot (WB) confirmation in high-prevalence settings remains insufficiently characterized. Hypothesis/Gap Statement: The comparative diagnostic accuracy of CLIA- and ELISA-based assays for HSV-1 IgG detection, when benchmarked against a WB reference standard in endemic populations, remains unclear. Aim: This study aimed to evaluate HSV-1 IgG seroprevalence and diagnostic performance of one CLIA and two ELISA platforms using Western blot as the reference method. Methodology: Four hundred archived serum samples from adult male craft and manual workers in Qatar were tested using the Mindray CL-900i CLIA, HerpeSelect ELISA, NovaLisa ELISA, and Euroimmun Western blot. Seroprevalence, diagnostic accuracy, and interassay agreement were assessed using WB as the reference standard, with equivocal and indeterminate results excluded from analysis. Results: HSV-1 IgG seroprevalence estimates were comparable across assays: HerpeSelect 72.5%, Mindray 70.5%, NovaLisa 66.3%, and Western blot 66.5%, with no statistically significant differences (all p > 0.05). The Mindray CLIA demonstrated the highest diagnostic performance (sensitivity 95.7%, specificity 88.9%, accuracy 93.4%) and strong agreement with Western blot ({kappa} = 0.85). HerpeSelect showed substantial agreement ({kappa} = 0.81), while NovaLisa exhibited lower specificity. Conclusion: CLIA- and ELISA-based assays produced comparable HSV-1 seroprevalence estimates in this high-prevalence population; however, diagnostic accuracy varied across platforms. The CLIA platform demonstrated the strongest agreement with Western blot, supporting its use in high-throughput settings, while confirmatory testing remains important to minimize misclassification.

ObjectivesAlarm fatigue is a patient safety concern in ICUs, yet no validated instrument exists to assess alarm fatigue among healthcare professionals in non-Western settings. This study aimed to cross-culturally adapt the Charite Alarm Fatigue Questionnaire (CAFQa) into Japanese and evaluate its reliability and validity among ICU nurses and physicians. MethodsThe Japanese CAFQa was cross-culturally adapted following the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines, including forward translation, back-translation, expert panel review, and cognitive interviews. A multicenter cross-sectional validation study was performed across eight ICUs at five hospitals in Japan. A total of 129 participants (103 nurses and 26 physicians) completed the Japanese CAFQa, the NIOSH Brief Job Stress Questionnaire, and the Insomnia Severity Index (ISI). Structural validity, internal consistency, test-retest reliability (n = 102), convergent validity, and known-groups validity were assessed. ResultsCFA confirmed the two-factor structure with acceptable fit (CFI = 0.922, RMSEA = 0.041, SRMR = 0.076), with standardized factor loadings ranging from 0.33 to 0.82. The two factors were not correlated (r = 0.05). Cronbachs alpha was 0.688 for the overall scale, 0.805 for Alarm Stress, and 0.649 for Alarm Coping. Test-retest ICCs ranged from 0.616 to 0.753. The CAFQa total score correlated with the NIOSH total (r = 0.261) and the ISI total (r = 0.338). Healthcare professionals with [&ge;]4 years of ICU experience had higher Alarm Coping scores than those with 1-3 years (median 7.0 vs 6.5), and physicians scored higher on Alarm Coping than nurses (median 8.0 vs 7.0). ConclusionsThe Japanese CAFQa demonstrated acceptable structural validity, reliability, and convergent and known-groups validity, providing the first validated tool for quantitatively measuring alarm fatigue in Japan. Implications for Clinical PracticeThe Japanese CAFQa enables ICU managers to quantify alarm fatigue at individual and unit levels, identify high-risk staff, and evaluate the effectiveness of alarm management interventions.

PurposeNavigational ability develops throughout childhood alongside the maturation of brain regions supporting egocentric and allocentric processing. In Autism Spectrum Disorder (ASD), atypical hippocampal development may impact flexible spatial memory; however, findings on navigational ability in autistic children remain inconsistent. This study aimed to compare both objective and perceived navigation ability in children with ASD and typically developing (TD) peers. MethodTwenty-six children with high-functioning ASD and twenty-five age- and gender-matched TD children (M_age = 12.04 years, SD = 1.64) completed a battery of navigational tasks from the Spatial Performance Assessment for Cognitive Evaluation (SPACE), including Path Integration, Egocentric Pointing, Mapping, Associative Memory, and Perspective Taking. Perceived navigation ability was assessed using the Santa Barbara Sense of Direction (SBSOD) scale. ResultsNo significant group differences were observed across any objective navigation tasks. However, children with ASD reported significantly lower perceived navigation ability compared to TD peers. ConclusionThese findings suggest a dissociation between perceived and actual navigational ability in ASD. By early adolescence, objective navigation performance appears intact, potentially reflecting sufficient maturation of underlying neural systems or the presence of compensatory mechanisms. The results underscore the importance of incorporating objective, task-based measures when assessing cognitive abilities in autistic populations.

Wastewater surveillance (WWS) is established as a vital tool for monitoring polio and SARS-CoV-2 with potential to improve surveillance for many other infectious diseases. This study evaluated the feasibility of detecting measles virus (MeV) RNA in wastewater as part of a national WS preparedness trial in Brisbane, Australia, from March to June 2025. Composite and passive sampling methods were employed in parallel at three wastewater treatment plants serving populations between 230,000 and 584,000. Nucleic acids were extracted and analyzed using RT-qPCR targeting MeV N and M genes to distinguish wild-type and vaccine strains. MeV RNA were detected in both 24-hour composite and passive samples on May 26 to 27, 2025 from the largest catchment of 584,000 which also included an international airport. No measles cases were reported in this city or region within 4 weeks of the WS detections. These were confirmed as vaccine-derived measles virus (MeVV) strain via specific RT-qPCR assay. Extraction recoveries varied (11.5% to 70.5%), with passive sampling showing higher efficiency. This is the first report of use of passive samples for detection of MeV. These findings are consistent with other studies reporting WWS results of both MeVV genotype A and wild type genotype B and/or D. It demonstrates the potential for sensitive MeV WWS with rapid differentiation of MeVV from wild type MeV shedding, including in airport transport hubs and with different sample types. Use of WWS could strengthen measles surveillance by enabling rapid detection of MeV RNA and supporting outbreak preparedness and response. This requires optimised methods which are specific to or differentiate wild-type MeV from MeVV. Furthermore, the successful detection of MeV using passive sampling in this study highlights its potential for deployment in diverse global contexts which may include non-sewered settings.

BackgroundThe World Health Organization has developed several global template protocols for epidemiological investigations, including for household transmission investigations (HHTIs). These investigations facilitate rapid characterisation of novel or re-emerging respiratory pathogens and support evidence-based public health actions. Beyond technical readiness, community buy-in is central to the feasibility and acceptability of HHTIs. Research is needed to determine the perceived legitimacy among the community to inform local protocol adaptation and development of implementation plans that consider community attitudes and needs. MethodsIn 2025, we conducted a convenience survey of community members living in Victoria, Australia to explore: their understanding of emerging respiratory diseases; their willingness to take part in public health surveillance activities such as HHTIs; the acceptability of clinical and epidemiological data collection and respiratory/blood sample collection as main components of HHTIs, and; participant comfort towards including their companion animals in HHTIs. ResultsWe received 282 survey responses, of which 235 were included in the analysis dataset. Compared to the general Victorian population, our participants included a higher proportion of participants who reported being female, tertiary-educated, of Aboriginal and/or Torres Strait Islander heritage, born in Australia and speaking only English at home. Participants indicated overall high levels of comfort and acceptability towards participation in HHTIs, particularly in relation to clinical and epidemiological data collection, with lesser but still high levels of comfort with providing multiple respiratory specimens in a 14-day period. Participants were least comfortable with other specimens such as urine and blood. Involving companion animals in HHTIs was similarly acceptable as human-focused components. ConclusionsDespite our survey population being non-representative of the general Victorian population, our findings provide valuable descriptive insights into the acceptability of HHTIs in Victoria, Australia from which to benchmark future local and international surveys and community engagement activities.

We used 2492 whole genome sequences from Laos to investigate the molecular epidemiology of SARS-CoV-2 from 2021 through 2024, covering the major waves of COVID-19 disease in Laos including time periods of travel restrictions and after relaxation of travel across international borders. We identify successive waves of COVID-19 caused by shifts in the dominant lineage, beginning with the Alpha variant in April 2021 and continuing through the Delta and Omicron variants. We quantify a shift from a small number of viral introductions responsible for widespread transmission in early waves to a larger number of introductions for each variant after travel restrictions were lifted, and identify potential routes of introduction into the country. Our study underscores the importance of genomic surveillance to public health responses to characterize viral transmission dynamics during pandemics.

BackgroundTimely cancer diagnosis in children and adolescents is critical to improving outcomes, yet substantial variation in diagnostic intervals persists across cancer types and care settings. We aimed to quantify time to diagnosis and assess variations by patient, demographic, and system-level factors. MethodsWe conducted a retrospective population-based study of children and adolescents aged 0-19 years diagnosed with one of 12 common cancers between 2010 and 2022 in Quebec, Canada. The diagnostic interval was defined as the time from first cancer-related healthcare encounter to diagnosis. We calculated medians and interquartile ranges (IQR) overall and by cancer type and used multivariable quantile regression to identify factors associated with time to diagnosis at the 25th, 50th, and 75th percentiles. ResultsAmong 2,927 individuals with cancer, diagnostic intervals varied by cancer type and age. Median intervals were longest for carcinomas (100 days; IQR 33-192) and shortest for leukemias (8 days; IQR 3-44). Compared with children living in Montreal, living in regional areas and other large urban centres was associated with longer 50th and 75th percentiles of time to diagnosis for hepatic and central nervous system (CNS) tumours. Diagnostic intervals were shorter in the post-pandemic period (2020-2022) across several cancer sites, with CNS tumours showing reductions across all quantiles. InterpretationDiagnostic timeliness differed by cancer type, age, and rurality, but not by sex, material, or social deprivation. The shorter diagnostic intervals observed in the post-pandemic period suggest that pandemic-related changes in care pathways may have expedited diagnosis for some cancers.

BackgroundThe rapid growth of the worlds urban population has contributed to the expansion of informal urban settlements in many cities across the world. In these settings, lack of safe sanitation combined with high population density and poverty contributes to heightened health risks for often vulnerable populations. The aim of this study was to evaluate the effect of a shared, onsite sanitation intervention on the nutritional status of children in Maputo, Mozambique. MethodsThe Maputo Sanitation (MapSan) trial was a controlled before-and-after study to evaluate the effect of a shared, onsite sanitation intervention on child health in Maputo, Mozambique. Here, we report the effects on childhood stunting, wasting and underweight, and height-for-age, weight-for-height and weight-for-age z-scores. Children were enrolled aged 1-48 months at baseline and outcomes were measured before and 12 and 24 months after the intervention, with concurrent measurement among children in a comparable control arm. The primary analysis was intention-to-treat. The trial was registered at ClinicalTrials.gov, number NCT02362932. ResultsWe enrolled 757 and 852 children in the intervention and control groups respectively. There was no evidence for an effect of the intervention on any outcome at 12 or 24 months of follow-up except for wasting where there was very weak evidence for an effect (adjusted prevalence ratio: 0.497; 95% CI: 0.22-1.11; p=0.09). In two exploratory analyses - one including only those children born into compounds post-intervention and a second excluding children in control compounds which had independently improved their sanitation facilities during follow-up - we found that stunting increased in the intervention group whilst wasting decreased. ConclusionsThis study contributes to the growing evidence on the role of sanitation in shaping child health outcomes in informal urban settlements. We found no evidence for an effect on stunting and weak evidence for an effect on wasting. More research is needed to understand how sanitation can reduce childhood undernutrition in complex urban environments.

Wearable-derived physiological features have been associated with disease risk, but most current studies focus on single conditions, limiting understanding of cross-disease patterns. This study adopts a trans-diagnostic approach to examine whether wearable data capture shared and condition-specific physiological signatures across multiple chronic conditions spanning physical and mental health, and then evaluates the utility of these features for disease classification. A total of 9,301 patients with at least 21 days of consecutive FitBit data from the All of Us Controlled Tier Dataset version 8 were analyzed. Disease subcohorts included cardiovascular disease (CVD), diabetes, obstructive sleep apnea (OSA), major depressive disorder (MDD), anxiety, bipolar disorder, and attention-deficit/ hyperactivity disorder (ADHD), chosen based on prevalence and relevance. Logistic regression and XGBoost models were fitted for each disease subcohort versus the control cohort. We found that compared to using just baseline demographic and lifestyle features, incorporating wearable-derived features enabled improved classification performance in all subcohorts for both models, except for ADHD where improvement was mainly observed for ROC-AUC in logistic regression model likely due to the smaller sample size in ADHD subcohort. The largest performance gains were observed in MDD (increase in ROC-AUC of 0.077 for Logistic regression, 0.071 for XGBoost; p < 0.001) and anxiety (increase in ROC-AUC of 0.077 for logistic regression, 0.108 for XGBoost; p < 0.001). This study provides one of the first comprehensive transdiagnostic evaluations of wearable-derived features for disease classification, highlighting their potential to enhance risk stratification in the real-world setting as a practical complement to clinical assessments and providing a foundation to explore more fine-grained wearable data. Author summaryWearable devices such as fitness trackers and smartwatches are becoming increasingly popular and affordable, providing continuous measurements of heart rate, physical activity, and sleep. Alongside the growing digitization of health records, this creates new opportunities for large-scale, real-world health studies. In this study, we analyzed wearable-derived physiological patterns across a range of chronic conditions spanning both physical and mental health to better understand how these signals relate to disease risk. We found that incorporating wearable-derived heart rate, activity and sleep features improved disease risk classification across several conditions, with particularly strong gains for major depressive disorder and anxiety. By examining how individual features contributed to model predictions, we also identified meaningful associations between physiological signals and disease risk. For example, both duration and day-to-day variation of deep and rapid eye movement (REM) sleep were associated with increased risk in certain conditions. Our study supports the development of real-time, automated tools to assess disease risk alongside clinical care.

Childhood socioeconomic position (SEP) can have lifelong effects on health. Many studies have used adult height as a surrogate marker for early-life conditions. In this study, we derived the non-genetic component of height, calculated as the residual from sex-specific standardized height regressed on genetically predicted height, as a surrogate for childhood SEP, using data from the Hispanic Community Healthy Study/Study of Latinos (2008-2011). A positive residual would indicate favorable early-life conditions promoting growth, while a negative residual indicates early-life adversity that may stunt the development. The height residual was associated with early-life variables such as parental education, year of birth, US nativity and age at first migration to the US (50 states/DC), supporting the validity of height residual as a surrogate for early-life conditions. Furthermore, a height residual was positively associated with better cardiovascular health (CVH) and cognitive function among middle-aged and older adults. Interestingly, among <35 years old, the height residual was negatively associated with the "Lifes Essential 8" clinical CVH scores. These results suggest the non-genetic component of height as a surrogate for childhood environment, with predictive value for CVH and cognitive function.

BackgroundAccelerometer-derived behavioral phenotype captures multidimensional aspects of human behavior extending well beyond physical activity, encompassing light exposure, step counts, physical activity patterns, sleep, and circadian rhythms. Whether these five domains constitute a unified behavioral architecture underlying cancer risk and whether circadian organization and light exposure confer incremental predictive value beyond movement volume alone remains to be comprehensively established. MethodsWe conducted an accelerometer-wide association study (AWAS) encompassing the complete accelerometer-derived behavioral exposome across five behavioral domains in UK Biobank participants with valid wrist accelerometry data. Incident solid cancers were designated as the primary endpoint, with prespecified site-specific solid cancers and hematological malignancy as secondary outcomes. Cox proportional hazards models with age as the timescale were used. The minimal covariate set served as the primary reporting tier, followed by sensitivity analyses additionally adjusting for adiposity/metabolic factors, independent activity patterns, shift work history, and accelerometry measurement quality. Nominal statistical significance was defined as two-sided P < 0.05 ResultsAmong 89,080 participants, 6,598 incident solid cancer events were observed over a median follow-up of 8.39 years. In the minimally adjusted model, the pan-solid-tumor association atlas was dominated by signals from activity volume, inactivity fragmentation, and circadian rhythm. Higher overall acceleration (HR per SD: 0.91, 95% CI: 0.89-0.94) and higher daily step counts (HR: 0.93, 95% CI: 0.90-0.95) were independently associated with reduced solid cancer risk, while inactivity fragmentation metrics were consistently linked to higher risk. Notably, circadian rhythms, most prominently cosinor mesor (Midline Estimating Statistic of Rhythm under cosinor model), emerged as leading inverse risk signals, underscoring the independent contribution of circadian behavioral architecture. Site-specific analyses revealed pronounced heterogeneity across tumor sites. Lung cancer exhibited a robust inverse activity-risk gradient, while breast cancer showed reproducible associations with MVPA. Most strikingly, nocturnal light exposure demonstrated a tumor-site-specific association confined to pancreatic cancer, a signal absent across all other sites examined. Associations for uterine cancer were predominantly inactivity-related and substantially attenuated following adjustment for adiposity and metabolic factors. ConclusionsAcross five accelerometer-derived behavioral domains, solid cancers as a whole were most consistently associated with a high-movement, low-fragmentation, and circadian-coherent behavioral profile. While site-specific heterogeneity exists, the broad cancer risk landscape is dominated by movement volume, inactivity fragmentation, and circadian rhythmicity. Light exposure, although more localized in its contribution, demonstrates a potentially novel and specific association with pancreatic cancer risk. These findings support a five-domain behavioral exposome framework for cancer epidemiology and, importantly, position circadian rhythm integrity and nocturnal light exposure as critically understudied dimensions warranting dedicated mechanistic investigation.

Background: Dengue is rapidly emerging in parts of Europe. How households value vector control attributes, and whether inferences depend on decision models or message framing, is unclear. Methods: We conducted a split-ballot online experiment among adults in Italy and France, as well as a hotspot subsample from Marche, Italy. National samples included 1,505 respondents in Italy and 1,501 in France; 183 respondents were recruited in Marche. Participants were randomised to a discrete choice experiment (random utility maximisation) or a regret-based choice experiment (random regret minimisation) and to one of three pre-task messages (control, loss aversion, community values). Each respondent completed 12 choice tasks comparing two dengue control programmes and an opt-out. We estimated mixed logit and mixed random-regret models with random parameters and treatment effects. Results: Across frameworks, nearby cases and high mosquito prevalence were the dominant drivers of programme uptake, whereas cost and operational burden were secondary. In pooled analyses, loss-aversion messaging increased the weight on high mosquito prevalence in both models (from 0.483 to 0.547 in the utility model; from 0.478 to 0.557 in the regret model). Cost effects were small nationally but larger in the hotspot subsample. Conclusions: Risk salience dominates preferences for dengue vector control in these European settings. Random utility and random regret models yield consistent rankings of attributes but differ in behavioural interpretation and some secondary effects; messaging effects were modest and context dependent.