A systematic review of fall prediction models for community-dwelling older adults: comparison between models based on research cohorts and models based on routinely collected data.

BACKGROUND: Prediction models can identify fall-prone individuals. Prediction models can be based on either data from research cohorts (cohort-based) or routinely collected data (RCD-based). We review and compare cohort-based and RCD-based studies describing the development and/or validation of fall prediction models for community-dwelling older adults. METHODS: Medline and Embase were searched via Ovid until January 2023. We included studies describing the development or validation of multivariable prediction models of falls in older adults (60+). Both risk of bias and reporting quality were assessed using the PROBAST and TRIPOD, respectively. RESULTS: We included and reviewed 28 relevant studies, describing 30 prediction models (23 cohort-based and 7 RCD-based), and external validation of two existing models (one cohort-based and one RCD-based). The median sample sizes for cohort-based and RCD-based studies were 1365 [interquartile range (IQR) 426-2766] versus 90 441 (IQR 56 442-128 157), and the ranges of fall rates were 5.4% to 60.4% versus 1.6% to 13.1%, respectively. Discrimination performance was comparable between cohort-based and RCD-based models, with the respective area under the receiver operating characteristic curves ranging from 0.65 to 0.88 versus 0.71 to 0.81. The median number of predictors in cohort-based final models was 6 (IQR 5-11); for RCD-based models, it was 16 (IQR 11-26). All but one cohort-based model had high bias risks, primarily due to deficiencies in statistical analysis and outcome determination. CONCLUSIONS: Cohort-based models to predict falls in older adults in the community are plentiful. RCD-based models are yet in their infancy but provide comparable predictive performance with no additional data collection efforts. Future studies should focus on methodological and reporting quality.

Optimal approaches for COVID-19 control: the use of vaccines and lockdowns across societal groups.

Background: By March 2023, the COVID-19 illness had caused over 6.8 million deaths globally. Countries restricted disease spread through non-pharmaceutical interventions (NPIs; e.g. social distancing). More severe "lockdowns" were also required to manage disease spread. Although lockdowns effectively reduce virus transmission, they substantially disrupt economies and individual well-being. Fortunately, the availability of vaccines provides alternative approaches to manage disease spread. Yet, vaccination programs take several months to implement fully, require further time for individuals to develop immunity following inoculation, may not have complete coverage and/or may be imperfectly efficacious against the virus. Given these aspects of a vaccination programme, it is important to understand how NPIs (such as lockdowns) can be used in conjunction with vaccination to achieve public health goals. Methods: We use mathematical methods to, investigate optimal approaches for vaccination under varying lockdown lengths and/or severities to prevent COVID-19-related deaths exceeding critical thresholds. Results: We find that increases in vaccination rate cause a disproportionate decrease in the length and severity lockdowns to keep mortality levels below a critical threshold. With vaccination, severe lockdowns can further reduce infections by up to 89%. Notably, we include simple demographics, modelling three groups: vulnerable, front-line workers, and non-vulnerable. We investigate the sequence of vaccination. One counter-intuitive finding is that even though the vulnerable group is high risk, demographically, this is a small group and critically, per person, vaccination therefore occurs more slowly. Hence vaccinating this group first achieves limited gains in overall disease control. Discussion: Importantly, we conclude that improved disease control may be best achieved by vaccinating the non-vulnerable group coupled with longer and/or more severe NPIs.

Assessing the lack of diversity in genetics research across neurodegenerative diseases: A systematic review of the GWAS Catalog and literature.

The under-representation of non-European cohorts in neurodegenerative disease genome-wide association studies (GWAS) hampers precision medicine efforts. Despite the inherent genetic and phenotypic diversity in these diseases, GWAS research consistently exhibits a disproportionate emphasis on participants of European ancestry. This study reviews GWAS up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. We conducted a systematic review of GWAS results and publications up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. Rigorous article inclusion and quality assessment methods were employed. Of 123 neurodegenerative disease (NDD) GWAS reviewed, 82% predominantly featured European ancestry participants. A single European study identified over 90 risk loci, compared to a total of 50 novel loci in identified in all non-European or multi-ancestry studies. Notably, only six of the loci have been replicated. The significant under-representation of non-European ancestries in NDD GWAS hinders comprehensive genetic understanding. Prioritizing genomic diversity in future research is crucial for advancing NDD therapies and understanding. HIGHLIGHTS: Eighty-two percent of neurodegenerative genome-wide association studies (GWAS) focus on Europeans. Only 6 of 50 novel neurodegenerative disease (NDD) genetic loci have been replicated. Lack of diversity significantly hampers understanding of NDDs. Increasing diversity in NDD genetic research is urgently required. New initiatives are aiming to enhance diversity in NDD research.

Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning.

BACKGROUND: Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complications, including levodopa-induced dyskinesia (LID). Despite continuous levodopa treatment, some patients do not develop LID symptoms, even in later stages of the disease. OBJECTIVE: This study explores machine learning (ML) methods using baseline clinical characteristics to predict the development of LID in PD patients over four years, across multiple cohorts. METHODS: Using interpretable ML approaches, we analyzed clinical data from three independent longitudinal PD cohorts (LuxPARK, n = 356; PPMI, n = 484; ICEBERG, n = 113) to develop cross-cohort prognostic models and identify potential predictors for the development of LID. We examined cohort-specific and shared predictive factors, assessing model performance and stability through cross-validation analyses. RESULTS: Consistent cross-validation results for single and multiple cohort analyses highlighted the effectiveness of the ML models and identified baseline clinical characteristics with significant predictive value for the LID prognosis in PD. Predictors positively correlated with LID include axial symptoms, freezing of gait, and rigidity in the lower extremities. Conversely, the risk of developing LID was inversely associated with the occurrence of resting tremors, higher body weight, later onset of PD, and visuospatial abilities. CONCLUSIONS: This study presents interpretable ML models for dyskinesia prognosis with significant predictive power in cross-cohort analyses. The models may pave the way for proactive interventions against dyskinesia in PD by optimizing levodopa dosing regimens and adjunct treatments with dopamine agonists or MAO-B inhibitors, and by employing non-pharmacological interventions such as dietary adjustments affecting levodopa absorption for high-risk LID patients.

Urban environment exposures, energy balance-related behaviors and their combination in preschoolers from three European countries.

BACKGROUND: Urban environments are characterized by many factors that may influence children's energy balance-related behaviors (EBRBs), but there is limited research on the impact of prospective exposure to multiple urban factors in preschoolers. We evaluated prospective associations between various urban exposures and EBRBs in preschoolers across Europe, with EBRBs considered both individually and combined into lifestyle patterns. METHODS: We used data from 4,073 preschoolers (aged 3-4 years) participating in three European cohorts from the EU Child Cohort Network: BiB (United Kingdom), EDEN (France), and INMA (Spain). Eighteen built and food environment, green spaces, road traffic and ambient air pollution exposures were characterized at residential addresses. Various EBRBs were considered as the outcomes including screen time, sleep duration and diet (fruit, vegetables, discretionary sweet foods, sweet beverages) individually and combined into unhealthy lifestyle patterns, using principal components analysis. Associations between urban exposures and outcomes were estimated using a single-exposure analysis and the deletion-substitution-addition algorithm was used to construct multi-exposure models. RESULTS: In multi-exposure models, greater walkability and smaller distance to the nearest road were associated with higher scores on the unhealthy lifestyle patterns. Likewise, greater walkability was associated with higher screen time and more frequent discretionary sweet food consumption. A smaller distance to the nearest road was also associated with lower sleep duration and more frequent sweet beverages consumption. On the other hand, higher levels of street connectivity showed an inverse association with the unhealthy lifestyle patterns. In the same vein, greater street connectivity was associated with decreased screen time. CONCLUSION: This comprehensive examination of multiple urban exposures indicates that residing in walkable environments and in close proximity to roads in densely-populated areas may not be advantageous for children EBRBs, while residing in neighborhoods with higher street connectivity appears to supposedly be beneficial.

Characteristics, consent patterns, and challenges of randomized trials using the Trials within Cohorts (TwiCs) design A scoping review.

OBJECTIVE: Trials within Cohorts (TwiCs) is a pragmatic design approach that may overcome frequent challenges of traditional randomized trials such as slow recruitment, burdensome consent procedures, or limited external validity. This scoping review aims to identify all randomized controlled trials using the TwiCs design and to summarize their design characteristics, ways to obtain informed consent, output, reported challenges and mitigation strategies. STUDY DESIGN AND SETTING: Systematic search of Medline, Embase, Cochrane, trial registries and citation tracking up to December 2022. TwiCs were defined as randomized trials embedded in a cohort with post-randomization consent for the intervention group and no specific post-randomization consent for the usual care control group. Information from identified TwiCs were extracted in duplicate from protocols, publications, and registry entries. We analyzed the information descriptively and qualitatively to highlight methodological challenges and solutions related to non-uptake of interventions and informed consent procedure. RESULTS: We identified a total of 46 TwiCs conducted between 2005 and 2022 in 14 different countries by a handful of research groups. The most common medical fields were oncology (11/46; 24%), infectious diseases (8/46;17%), and mental health (7/46; 15%). A typical TwiCs was investigator-initiated (46/46;100%), publicly funded (36/46; 78%), and recruited outpatients (27/46; 59%). Excluding eight pilot trials, only 16/38 (42%) TwiCs adjusted their calculated sample size for non-uptake of the intervention, anticipating a median non-uptake of 25% (interquartile range 10%-32%) in the experimental arm. Seventeen TwiCs (45%) planned analyses to adjust effect estimates for non-uptake. Regarding informed consent, we observed three patterns: 1) three separate consents for cohort participation, randomization, and intervention (17/46; 37%); 2) combined consent for cohort participation and randomization and a separate intervention consent (10/46; 22%); and 3) consent only for cohort participation and intervention (randomization consent not mentioned; 19/46; 41%). CONCLUSIONS: Existing TwiCs are globally scattered across a few research groups covering a wide range of medical fields and interventions. Despite the potential advantages, the number of TwiCs remains small. The variability in consent procedures and the possibility of substantial non-uptake of the intervention warrants further research to guide the planning, implementation, and analysis of TwiCs.

Validation of the Health Assessment Tool (HAT) based on four aging cohorts from the Swedish National study on Aging and Care.

BACKGROUND: As global aging accelerates, routinely assessing the functional status and morbidity burden of older patients becomes paramount. The aim of this study is to assess the validity of the comprehensive clinical and functional Health Assessment Tool (HAT) based on four cohorts of older adults (60 + years) from the Swedish National study on Aging and Care (SNAC) spanning urban, suburban, and rural areas. METHODS: The HAT integrates five health indicators (gait speed, global cognition, number of chronic diseases, and basic and instrumental activities of daily living), providing an individual-level score between 0 and 10. The tool was constructed using nominal response models, first separately for each cohort and then in a harmonized dataset. Outcomes included all-cause mortality over a maximum follow-up of 16 years and unplanned hospital admissions over a maximum of 3 years of follow-up. The predictive capacity was assessed through the area under the curve (AUC) using logistic regressions. For time to death, Cox regressions were performed, and Harrell's C-indices were reported. Results from the four cohorts were pooled using individual participant data meta-analysis and compared with those from the harmonized dataset. RESULTS: The HAT demonstrated high predictive capacity across all cohorts as well as in the harmonized dataset. In the harmonized dataset, the AUC was 0.84 (95% CI 0.81-0.87) for 1-year mortality, 0.81 (95% CI 0.80-0.83) for 3-year mortality, 0.80 (95% CI 0.79-0.82) for 5-year mortality, 0.69 (95% CI 0.67-0.70) for 1-year unplanned admissions, and 0.69 (95% CI 0.68-0.70) for 3-year unplanned admissions. The Harrell's C for time-to-death throughout 16 years of follow-up was 0.75 (95% CI 0.74-0.75). CONCLUSIONS: The HAT is a highly predictive, clinically intuitive, and externally valid instrument with potential for better addressing older adults' health needs and optimizing risk stratification at the population level.

The Importance of Large-Scale Genomic Studies to Unravel Genetic Risk Factors for Autism.

Autism spectrum disorder (ASD) is a common and highly heritable neurodevelopmental disorder. During the last 15 years, advances in genomic technologies and the availability of increasingly large patient cohorts have greatly expanded our knowledge of the genetic architecture of ASD and its neurobiological mechanisms. Over two hundred risk regions and genes carrying rare de novo and transmitted high-impact variants have been identified. Additionally, common variants with small individual effect size are also important, and a number of loci are now being uncovered. At the same time, these new insights have highlighted ongoing challenges. In this perspective article, we summarize developments in ASD genetic research and address the enormous impact of large-scale genomic initiatives on ASD gene discovery.

Breast cancer stage and molecular subtype distribution: real-world insights from a regional oncological center in Hungary.

OBJECTIVE: Examining the distribution of breast cancer (BC) stage and molecular subtype among women aged below (< 45 years), within (45-65 years), and above (> 65 years) the recommended screening age range helps to understand the screening program's characteristics and contributes to enhancing the effectiveness of BC screening programs. METHODS: In this retrospective study, female patients with newly diagnosed BC from 2010 to 2020 were identified. The distribution of cases in terms of TNM stages, severity classes, and subtypes was analysed according to age groups. RESULTS: A total of 3282 women diagnosed with BC were included in the analysis. Among these cases 51.4% were detected outside the screening age group, and these were characterized by a higher TNM stage compared to those diagnosed within the screening age band. We observed significantly higher relative frequency of advanced BC in the older age group compared to both the screening age population and women younger than 45 years (14.9% vs. 8.7% and 7.7%, P < 0.001). HR-/HER2- and HER+ tumours were relatively more frequent among women under age 45 years (HR-/HER2-: 23.6%, HER2+: 20.5%) compared to those within the screening age range (HR-/HER2-: 13.4%, HER2+: 13.9%) and the older age group (HR-/HER2-: 10.4%, HER2+: 11.5%). CONCLUSIONS: The findings of our study shed light on potential areas for the improvement of BC screening programs (e.g., extending screening age group, adjusting screening frequency based on molecular subtype risk status) in Hungary and internationally, as well.

Dietary atherogenicity and thrombogenicity indexes predicting cardiovascular mortality: 50-year follow-up of the Seven Countries Study.

BACKGROUND AND AIM: To study the relationships of an Atherogenicity Index (ATI) and a Thrombogenicity Index (THI), with 50-year mortality from coronary heart disease (CHD), other heart diseases of uncertain etiology (HDUE) and cerebrovascular disease or stroke (STR), in 16 international cohorts of middle-aged men. METHODS AND RESULTS: Foods from a dietary survey in subsamples of men in each cohort of the Seven Countries Study (SCS) were chemically analyzed for several types of fatty acids that were converted into ATI and THI identifying each of 16 cohorts. Ecological correlations of the ATI and THI were calculated with the three fatal CVD conditions and with all-cause mortality at 25 and 50 years. Correlation coefficients (Rs) were positive and highly significant between ATI and THI versus CHD mortality, with levels ranging from 0.79 to 0.97, depending on the duration of follow-up and the choice of 10 or of 16 cohorts. This was not the case for HDUE and STR mortality for which Rs were variable and not significant. A strong direct association was also found with all-causes deaths at 25 and 50-years. ATI and THI were also directly related with dietary saturated fat and cholesterol levels and inversely with the Mediterranean Adequacy Index (a score identifying the Mediterranean diet). CONCLUSION: These findings indicate that CHD has a different relationship with dietary lipids intake than HDUE and STR. This suggests that HDUE and STR have different underlying pathways or are different diseases.

Divergence in Chinese Sexual Attitudes: An Age-Period-Cohort Analysis.

A crucial component of comprehending societal change is understanding how sexual attitudes have evolved over time. The substantial and typical changes in China have created an ideal quasi-experimental design and a wealth of empirical data for tracking the evolution of sexual attitudes. However, existing research has failed to adequately analyze the temporal trends in Chinese sexual attitudes. This study employed an age-period-cohort framework to investigate changes in public sexual attitudes, including premarital sex, extramarital sex, and homosexuality. And it further delved into these attitudes in light of two unique aspects of Chinese society: urban-rural divide and political status. It explored the contributing elements and potential processes of changing public sexual attitudes in China using data from seven waves of national social survey conducted from 2010 to 2021. The findings indicated that public sexual attitudes became more conservative with age; the period effect exhibited a fluctuating upward trend, indicating a general increase in acceptance of the three sexual attitudes; notable differences in sexual attitudes among cohorts were identified. The divergence in sexual attitudes was significantly influenced by urban-rural divide and political status.

Cohort Differences in Physical Health and Disability in the United States and Europe.

OBJECTIVES: Declines in mortality have historically been associated with improvements in physical health across generations. While life expectancy in most high-income countries continues to increase, there is evidence that younger generations, particularly in the United States, are less healthy than previous generations at the same age. We compared generational trends in physical health in the United States, England, and continental Europe to explore whether other regions have experienced a similar pattern of worsening health across cohorts. METHODS: Using data from nationally representative studies of adults aged ≥50 years from the United States (Health and Retirement Study, n = 26,939), England (English Longitudinal Study of Ageing, n = 14,992) and 11 continental European countries (Survey of Health, Ageing and Retirement in Europe, n = 72,595), we estimated differences in the age-adjusted prevalence of self-reported chronic disease and disability and observer-measured health indicators across pseudo-birth cohorts (born <1925, 1925-1935, 1936-1945, 1946-1954, 1955-1959). RESULTS: Age-adjusted prevalence of doctor-diagnosed chronic disease increased across successive cohorts in all regions. Trends in disability prevalence were more regionally varied. Still, in both the United States and Europe, we observed a structural break in disability trends, with declines observed in prewar cohorts slowing, stalling, or reversing for cohorts born since 1945. DISCUSSION: In all regions, we found evidence for worsening health across cohorts, particularly for those born since 1945. While more chronic disease in younger cohorts need not necessarily translate to worse quality of life or higher rates of functional limitation, there is some suggestion that worsening chronic disease morbidity may be spilling over into worsening disability.

Birth-cohort patterns of e-cigarette and other tobacco use among adolescents in the US.

BACKGROUND: E-cigarette use has increased considerably among US adolescents. While many studies have described cross-sectional prevalence trends of youth e-cigarette use, less is known about cohort or generational initiation and use patterns. METHODS: We used data from the US National Youth Tobacco Survey (NYTS) from 2014 to 2022 and age-period-cohort models to analyze age-specific patterns of e-cigarette use initiation and prevalence by cohort and calendar. For comparison, we also examined initiation and prevalence for cigarettes, cigars, and smokeless tobacco, using NYTS data from 1999 to 2022. RESULTS: Age-specific e-cigarette initiation and prevalence varied considerably by calendar year and birth cohort. There was a rapid increase in e-cigarette initiation and prevalence starting with the 1995 birth cohort, peaking with the 2005 birth cohort, and showing signs of decline with more recent cohorts. In contrast, there were substantial continuous reductions in cigarette, cigar, and smokeless use initiation and prevalence by birth cohort. While the reductions in cigarette smoking started with the 1980s birth cohorts, cigar and smokeless initiation and prevalence did not decrease until the 1990-1995 cohorts. CONCLUSIONS: Despite their recent emergence, e-cigarette use has varied considerably across US adolescent cohorts. After early increases, e-cigarette use and initiation peaked with the 2005 birth cohort. These patterns are in contrast with the continuous decreases by cohort in cigarette, cigar, and smokeless use and initiation. As the tobacco product landscape continues to evolve, it will be essential to monitor patterns of use of adolescent and young adult cohorts as they age into adulthood.

Prenatal Urban Environment and Blood Pressure Trajectories From Childhood to Early Adulthood.

Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

Evaluation of Salivary Biomarkers and Spirometry for Diagnosing COPD in Non-Smokers and Smokers of Polish Origin.

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory condition with global implications. Accurate and timely diagnosis is critical; however, traditional diagnostic methods (based on spirometry) show limitations, prompting the search for predictive biomarkers and modern diagnostic techniques. This study explored the validation of COPD-related biomarkers (C-reactive protein, procalcitonin, neutrophil elastase, and alpha-1 antitrypsin) in saliva. A diverse cohort, including healthy non-smokers, healthy smokers, and COPD patients of Polish origin, underwent spirometry and marker analysis. The data correlated with clinical factors, revealing noteworthy relations. Firstly, salivary biomarker levels were compared with serum concentrations, demonstrating notable positive or negative correlations, depending on the factor. Further analysis within healthy individuals revealed associations between biomarker levels, spirometry, and clinical characteristics such as age, sex, and BMI. Next, COPD patients exhibited an enhanced concentration of biomarkers compared to healthy groups. Finally, the study introduced a breathing assessment survey, unveiling significant associations between self-perceived breathing and spirometric and tested parameters. Outcomes emphasized the relevance of subjective experiences in COPD research. In conclusion, this research underscored the potential of salivary biomarkers as diagnostic tools for COPD, offering a non-invasive and accessible alternative to traditional methods. The findings paved the way for improved modern diagnostic approaches.

Core data set para la generación de datos de la vida real en esclerosis múltiple: adaptación de una iniciativa global para América Latina / Core data set for real world data in multiple sclerosis: customization for latin america from a global task force recommendation

Introducción: Los objetivos primarios del core data set son reducir la heterogeneidad y promover la armonización entre las fuentes de datos en la esclerosis múltiple (EM), reduciendo así el tiempo necesario para ejecutar esfuerzos en la recolección de datos de vida real. Recientemente, un grupo liderado por la Multiple Sclerosis Data Alliance ha desarrollado un core data set para la recolección de datos del mundo real en EM a nivel global. Nuestro objetivo ha sido adaptar y consensuar este conjunto de datos globales a las necesidades de América Latina para que pueda ser implementado por los registros ya desarrollados y en proceso de desarrollo en la región. Material y métodos. Se conformó un grupo de trabajo regionalmente y se adaptó el core data set creado globalmente (proceso de traducción al español, incorporación de variables regionales y consenso sobre variables que se iban a utilizar). El consenso se obtuvo a través de la metodología Delphi remoto de ronda de cuestionarios y discusión a distancia de las variables del core data set. Resultados: Veinticinco profesionales de América Latina llevaron adelante el proceso de adaptación entre noviembre de 2022 y julio de 2023. Se estableció un acuerdo sobre un core data set de nueve categorías y 45 variables, versión 2023, con la sugerencia de implementarlo en registros desarrollados o en vías de desarrollo y cohortes de EM en la región. Conclusión: El core data set busca armonizar las variables recolectadas por los registros y las cohortes de EM en América Latina con el fin de facilitar dicha recolección y permitir una colaboración entre fuentes. Su implementación facilitará la recolección de datos de vida real y la colaboración en la región.(AU)

Introduction: The primary objective of the core data set is to reduce heterogeneity and promote harmonization among data sources in EM, thereby reducing the time needed to execute real life data collection efforts. Recently, a group led by the Multiple Sclerosis Data Alliance has developed a core data set for collecting real-world data on multiple sclerosis (MS) globally. Our objective was to adapt this global data set to the needs of Latin America, so that it can be implemented by the registries already developed and in the process of development in the region. Material and methods: A working group was formed regionally, the core data set created globally was adapted (translation process into Spanish, incorporation of regional variables and consensus on variables to be used). Consensus was obtained through the remote Delphi methodology of a round of questionnaires and remote discussion of the core data set variables. Results: A total of 25 professionals from Latin America carried out the adaptation process between November 2022 and July 2023. Agreement was established on a core data set of nine categories and 45 variables, version 2023 to suggest its implementation in developed or developing registries, and MS cohorts in the region. Conclusion: The core data set seeks to harmonize the variables collected by registries and cohorts in MS in Latin America in order to facilitate said collection and allow collaboration between sources. Its implementation will facilitate real life data collection and collaboration in the region.(AU)

Towards an understanding of multi-generational higher education cohorts in gamified entrepreneurship education.

The increasing inclusion of gamified courses in entrepreneurship programmes in higher education have left gaps in understanding the critical essentials of the multi-generational student cohort undertaking these programmes. In this paper, we interrogate the educational experiences of multi-generational higher education students in a core gamified entrepreneurship course in an undergraduate business school programme. The research analyzed 392 course feedback responses from three generations (X, Y and Z) of a multi-generational cohort. The study developed and validated a behaviour-results model for gamified entrepreneurship courses leading to student entrepreneurial intention and entrepreneurial orientation, and disaggregated student engagement into it's multiple dimensions of cognitive, behavioural and emotional. The model also validated six dimensions of individual entrepreneurship orientation. Using the model, the study found differences in the component variables based on student Generations X, Y, and Z. Also, student cognitive and behavioural engagement led to entrepreneurial intention which also influenced student entrepreneurial orientation. There were marked differences in student grit, cognitive engagement, and emotional engagement between Generations X and Z. Furthermore, generational differences existed amongst Generation Z and Y, and also for Generation Z and X in student entrepreneurial intention. The study also confirmed the difference in entrepreneurial orientation between Generations X and Z. Additionally, the study found that there is a need to contextualize student engagement facilitators such as results demonstrability of the business simulation platform, student grit and user characteristics as they have selective effects on student cognition, behavioural and emotional engagements in a multi-generational student cohort of Generation X, Y and Z.

Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts.

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

Children's behavioural and emotional wellbeing during the COVID-19 pandemic: Findings from the Born in Bradford COVID-19 mixed methods longitudinal study.

Background: The COVID-19 pandemic led to a multitude of immediate social restrictions for many across the world. In the UK, the lives of children and young people were quickly impacted when COVID-19 restrictions led to school closures for most children and restrictions on social interactions. The Born in Bradford COVID-19 longitudinal research study explored the impact of the COVID-19 pandemic on the lives of children and their families living in Bradford. Methods: Surveys were administered during the first wave of the pandemic (March to June 2020) and compared to findings from before the pandemic. The current study examined the social and emotional wellbeing of children from before to during the pandemic, measured using the parent completed Strengths and Difficulties questionnaire (SDQ). Regression analyses looked at associations between a range of social determinants of health and changes in SDQ scores. Results: The results showed that those children most likely to experience difficulties during the pandemic were boys, younger children, those from White British ethnicity (compared to Pakistani heritage children) and those living in the most deprived areas. There were associations between experiencing difficulties and: food insecurity; financial worry; getting below recommended levels of physical activity; and having less than the recommended amount of sleep. Conclusions: The effect of COVID-19 restrictions are likely to have had negative consequences on children that could, in time, have long-lasting impacts on the health, wellbeing and development of children in the UK.

The COVID-19 pandemic caused immediate and long-lasting social restrictions to be implemented here in the UK and across the world. In the UK, children and young people were quickly affected by these restrictions that led to school closures and other restrictions that prevented these individuals from socialising in person with one another. This study explored the impact that the pandemic had on the wellbeing of children by comparing data from before the pandemic with data collected during the pandemic. The data that has been collected looks at the behavioural strengths and difficulties that children are displaying. Our exploration found that children that were most likely to experience difficulties during the pandemic were boys, younger children, those who were White British and those who lived in the most deprived areas. The effect of the COVID-19 restrictions are likely to have had a negative impact on children and young people which in time may impact the health and development of children living here in the UK.

Understanding the impact of maternal and infant nutrition on infant/child health: multiethnic considerations, knowledge translation, and future directions for equitable health research.

A mother's intrauterine environment influences her health and that of her offspring, at birth and in the future. Herein, we present an overview of our Canadian Institutes of Health Research (CIHR)-funded grant "Understanding the impact of maternal and infant nutrition on infant/child health"-set within The NutriGen Birth Cohort Alliance. NutriGen is a consortium of four Canadian prospective birth cohorts representing >5000 mother-child pairs of diverse ethnic groups including South Asians, White Europeans, and Indigenous peoples. We summarize our objectives and main findings on outcomes of maternal diet, gestational diabetes, birth weight, cardiometabolic health, the microbiome, and epigenetic modifications. We append this work with 10 key messages when conducting multiethnic research and review our knowledge translation products. We describe the clinical impact of our research on maternal and child health and conclude with future directions on biomarker discovery, expansion to other ethnic groups, and interventions for high-risk populations.