Introduction: A well-trained and experienced staff in epidemiological studies is essential for the quality of the study implementation and the data and analyses collected from it. A broad understanding of Good Epidemiological Practice (GEP) can increase the motivation of staff to collect evaluable data. There are no special training opportunities for non-academic staff. This report describes the development and evaluation of an “EPI Study Nurse” (ESN) pilot course to train staff in epidemiological studies. Project description: The development of a concept for a pilot course was initiated by a project group from the study centers of the German National Cohort (NAKO) in early 2020. It was carried out in close collaboration with the Robert Koch Institute (RKI) and the professional societies “Deutsche Gesellschaft für Sozialmedizin und Prävention” (DGSMP), “Deutsche Gesellschaft für Epidemiologie” (DGEpi), and “Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V.” (GMDS). A training plan with 12 modules covering the relevant contents of the GEP was defined and a timetable was drawn up. Those responsible for the modules and teachers as well as participants in the pilot course were recruited through inquiries from the institutions mentioned above. After each module, the expectations and satisfaction of participants and teachers were surveyed. The pilot course was financed by the participating institutions from their own resources. Discussion: The pilot phase of the continuing education course was successfully implemented within one year (2022–2023) (preparation of a curriculum, registration of participants and recruitment of lecturers, organisation and execution of the course and final examination) and evaluated. A particular challenge was the definition of the module-specific timeframes for the lectures and group work as well as the targeted consideration of the different levels of experience of the participants. For future courses, it must be taken into account that administrative tasks in particular require considerable human resources (e.g., creating the curriculum, organizing and moderating the course) and financial resources (e.g., fees, travel expenses). The project was approved as part of the application for the third funding phase of the NAKO (June 2024 – April 2028) and the courses will be offered once a year.

Abstract Background During the COVID-19 pandemic, non-COVID-19 related healthcare utilization declined in Germany, resulting in care delay, including delays and cancellations of routine, chronic, and even acute care. The aim of this study was to investigate factors (i.e. regional differences and participant characteristics) associated with care delay during the pandemic in Germany using a cross-sectional survey. Methods In October 2022, a total of 117,466 participants from the German National Cohort (NAKO) study completed an online questionnaire on pandemic-related topics, including care delay during the COVID-19 pandemic. Regional differences and participant characteristics associated with care delay were assessed using (multilevel) logistic regression. Results One third of participants reported having experienced care delay. Care delay did not differ across the 13 federal states or 32 districts in Germany for which sufficient data were available. In the medical practice setting, care delay was nearly equally provider- and patient-related and was reported mostly for routine check-ups. In the hospital setting, care delay was predominantly provider-related and reported for newly occurring conditions. The odds for care delay were higher in females vs. males (odds ratio (OR): 1.30; 95% confidence interval (CI): 1.27–1.34), and in participants with vs. without chronic conditions (e.g. mental disorders, OR: 1.41, 95%CI: 1.36–1.46 or cardiovascular diseases, OR: 1.20 95%CI: 1.16–1.24) and decreased with age (e.g. 70 + vs. 50–59 years, OR: 0.59, 95%CI: 0.57–0.62). Conclusion Care delay during the COVID-19 pandemic depended on participant characteristics including age, sex, and preexisting chronic conditions but not on regional (i.e. state and district-level) differences in Germany.

Abstract Background The COVID-19 pandemic and accompanying social distancing measures might have caused adverse health consequences. We aimed to describe changes in participants’ self-rated health and mental health (depression, anxiety, and stress), and investigate factors associated with them. Methods We collected data from the German National Cohort (NAKO). We first described changes in participants’ self-rated health and mental health from the baseline examination (1 to 6 years earlier) to the early phase of the COVID-19 pandemic. We then applied the multinomial logistic regression model (self-rated health) and the quantile regression model (mental health) to investigate the potential factors associated with the health status and changes. Results After a median of 3.1 [2.1, 4.1] years from baseline to the early pandemic phase (N = 91,809), 39.3% of participants with good health and 69.7% with less good health status at baseline reported better health. However, the percentage of participants with high depression, anxiety, and stress scores (≥ 10) increased from 6.2%, 4.1%, and 4.3% to 8.6%, 5.6%, and 10.1%, respectively. In the multivariable models, we found that being younger, being male, highly educated, being employed, having higher life satisfaction at baseline, being more physically active, drinking heavily, and experiencing improved anxiety symptoms were associated with improved self-rated health. In contrast, smoking and having mental health disorders were all associated with worse self-rated health. Our results showed that being younger, being female, smoking, drinking heavily, and drinking more since baseline were associated with higher depression scores. Having had a coronavirus test was associated with worse self-rated health and more severe anxiety and stress. Conclusions During the early COVID-19 pandemic, many participants experienced improvements in self-rated health but suffered deterioration in mental health and physical activity engagement. Female participants, those who were physically inactive, and those with pre-existing mental disorders were more likely to report poorer health.

BACKGROUND:Chronic kidney disease (CKD) can be asymptomatic for many years and is often diagnosed late. Given the availability of new treatments, the early identification of relevant findings from screening of the kidney markers estimated glomerular filtration rate (eGFR) and albuminuria in the general population is becoming increasingly important. METHODS:In the NAKO study, self-reported medical diagnoses of kidney disease in 195 182 participants were compared with relevant findings from screening biomarkers (eGFR < 60 mL/min/1.73 m² and albuminuria). For the purpose of comparison, various equations for assessing kidney function were evaluated as well. RESULTS:2% of the participants reported having received a medical diagnosis of kidney disease, and 2% had an eGFR below 60 mL/min/1.73 m². There was, however, little overlap between these two groups: more than 80% of participants with an eGFR between 30 and 59 mL/min/1,73 m²) did not report any diagnosis of kidney disease. The additional inclusion of data on albuminuria did not materially affect this discrepancy: 6213 persons (17.5% of the cohort) with an abnormal eGFR or urinary albumin-to-creatinine ratio (UACR) did not report any diagnosis of kidney disease. Even among participants whose eGFR was in the range of 30-59 mL/min/1.73 m² and whose UACR was above 300 mg/g, less than half reported having a medically diagnosed kidney disease. CONCLUSION:These findings indicate a low level of awareness regarding the possible presence of CKD in the general population. Many people with abnormal screening findings needing further investigation due to their potential clinical relevance are unaware that they might be suffering from a kidney disease. As more effective treatments for kidney disease are now available, these findings indicate a need for structured screening and evaluation strategies to promote kidney health.

Childhood maltreatment (CM) is associated with adult cardiovascular disease (CVD) risk. Systolic (SBP) and diastolic (DBP) blood pressure (BP), key markers of CVD risk, exhibit age- and sex-dependent variability, which was insufficiently accounted for in previous studies on the CM-BP relationship. This study therefore aimed to assess age- and sex-specific associations between CM and adult BP-based outcomes and hypertension using cross-sectional data from the population based German National Cohort (NAKO). Complete data were available for 150,983 participants (49.3

Background The nasal microbiome plays an important role in respiratory and systemic health, but data from large adult population cohorts remain scarce. We analyzed nasal microbiota from 2,070 adults aged 21–73 years in the population-based German National Cohort (NAKO) to characterize community composition and identify host factors associated with variation in the anterior nares’ microbiome. Microbial profiles were obtained using 16S rRNA gene sequencing, and associations with host characteristics—including sex, age, body composition, tobacco smoking, pulmonary function, household context, and self-reported physician diagnoses—were evaluated using a two-stage regression framework, beta diversity analyses, and complementary Latent Dirichlet Allocation (LDA) community modeling. Results Despite detecting 358 genera across the cohort, more than 90% of all sequencing reads were assigned to only 15 genera. These core genera showed distinct associations with host physiology and lifestyle. Sex and body mass index were the strongest correlates of alpha and beta diversity, while pulmonary function and tobacco smoking were associated with differences in the relative abundance of several commensal taxa, including Lawsonella , Cutibacterium , and Dolosigranulum . Age was not related to overall diversity but exhibited characteristic shifts in community composition. Antibiotic use within the previous 12 months was associated with lower levels of multiple commensal genera and higher relative abundance of Staphylococcus . LDA-derived sub-communities largely mirrored the genus-level associations and indicated that these patterns reflect transitions between recurrent nasal community types rather than isolated changes in single taxa. Conclusions This nationwide study provides a detailed characterization of nasal microbiome patterns in the general adult population (up to 73 years) of Germany and highlights that multiple host factors are associated with both taxon-specific and community-level variation. The findings offer a reference for future investigations into the role of the nasal microbiome in respiratory and systemic health.

Abstract Background While statins are typically prescribed to reduce the risk of cardiovascular diseases, they may also offer protection against influenza. We investigated the effect of statins on influenza and related respiratory outcomes in older adults not receiving influenza vaccination in the UK. Method We aggregated annual cohorts from 2010 to 2018 comprising UK patients registered in primary care within the UK Clinical Practice Research Datalink, aged ≥65 years on the1st September index date without influenza vaccination two years prior to index. We compared patients who had initiated statins by the index date to those with no recorded statin prescription. Outcomes were acute respiratory infection (ARI), influenza and pneumonia, diagnosed in hospital. Using the prior event rate ratio study design, we adjusted for measured and unmeasured confounding bias, by utilizing data for each outcome recorded in the 1y period prior to index. Results Data on 213,372 patients were included for study. Following statin initiation, there was a significant reduction in pneumonia (hazard ratio (HR)= 0.86, 95%CI: 0.78, 0.94) and general ARI (HR=0.83, 95%CI: 0.76, 0.89) diagnosed in hospital, but not for influenza (HR=0.63, 95%CI 0.21, 1.93). Conclusion In unvaccinated older adults, statin initiation was associated with a reduced risk of pneumonia and other acute respiratory infections diagnosed in hospital. These findings are consistent with, but do not establish, a protective effect of statins on severe respiratory infection.

Mass gathering events (MGEs) play a critical role for infectious disease dynamics on a population level as they provide opportunities for superspreading; however, underlying mechanisms remain insufficiently understood. We analyzed nationwide GPS-based, individual-level location data from mobile phone users in Germany between April and August 2024 with 16 m spatial precision. Potentially infectious contacts were inferred from close co-location and linked to contact settings using OpenStreetMap data. Various MGEs, including EURO 2024 matches, major concerts, festivals, and fairs were compared using a common contact metric. Non-football events generated substantially more contacts than football events. While overall national contact numbers remained stable, MGEs produced so-called “small-world” contacts which gather people from distant locations into close proximity and could strongly enhance infectious disease dynamics. Crucially, most high-risk contacts occurred within two hours before the event, not at the event itself, and concentrated in public transport, leisure, and event-adjacent areas. Our work provides the first systematic and comparative evaluation of contact exposure across various types of MGEs and contact settings. Event-type-specific dynamics, particularly indirect and mobility-driven contacts, critically shape infection risk. These insights can inform accurate transmission modeling, targeted intervention and event-management strategies.

BACKGROUND:The German National Cohort (NAKO Gesundheitsstudie) is a prospective cohort study with 205 053 participants. Its goal is to identify risk factors for chronic diseases, including cancer. METHODS:We describe the methods of ascertaining cancer cases in NAKO (i.e., linkage with cancer registries and self-reporting), the incidence and prevalence figures obtained so far, and the ratios of observed to expected (O/E) case numbers. RESULTS:Case ascertainment identified 2774 existing cancer cases diagnosed within the five years prior to study enrollment and 4295 new cancer cases diagnosed up to five years after enrollment. Cancers of the breast, prostate, lung, and colorectum made up 55% of the incident cases. Fewer incident cases were found than would have been expected on the basis of incidences in the general population (O/E ratio 0.80, 95% confidence interval [0.76;0.83] for the first two-years of prospective follow-up); the O/E ratio varied across tumor sites (breast 1.02, prostate 1.12, lung 0.38, colorectum 0.62). Possible explanations include healthy volunteer bias, delayed reporting, as well as incomplete data collection from registries and self-reporting. CONCLUSION:Rising case numbers for the most common types of cancer are expected in the next few years and will enable comprehensive epidemiological analysis of the risk factors of cancer.

Background For early detection of breast cancer, clinical palpation of the breast is offered yearly to all women aged 30 and older, and the German Mammography Screening Programme (MSP) offers biennial mammograms to all women aged 50 to 75 years. We investigated the utilization of both screening methods across various migrant groups in Germany, as well as the effect of German language proficiency. Methods Cross-sectional data on participation frequencies from the baseline examination (2014 to 2019) of more than 100,000 women of the German National Cohort study (NAKO) were analysed by migrant status. Adjusted logistic regression analyses were conducted for palpation and MSP to compare screening uptake among six migrant groups, and non-migrant population. Results Palpation of the breast was less frequently utilized in all migrant groups with odds ratios ranging from 0.5 (95% CI 0.4-0.6) for Turkish women to 0.9 for women from western countries (95% CI 0.7-1.1) compared to autochthone Germans. Lower German language proficiency further decreases its use. In contrast, odds ratios for MSP participation did not differ substantially compared to Germans ranging from 0.8 to 1.2. German language proficiency had little effect on MSP participation. Discussion In contrast to earlier studies, our findings suggest that MSP participation and motivation does not significantly differ by migration status or language skills. This may indicate that information on MSP is broadly accessible through established invitation procedures in Germany. However, lower uptake of breast palpation by a physician in some migrant populations highlights potential gaps in broader preventive care engagement.

The parametrisation of contact behaviour is crucial for infectious disease transmission models. Contact information derived from self-reported surveys and from co-location in space and time (GPS-based) may reflect different dimensions of contact behaviour, which might be associated with distinct epidemiological risks depending on the contagion of interest. This study explores whether and how contacts measured using these distinct approaches exhibit similar or complementary contact patterns.We compare the mean number of contacts and the mean excess number of contacts (i.e. the ratio of mean squared contacts to mean contacts) from the COVIMOD survey and NETCHECK GPS co-location data between April 2020 and December 2021. While mean contacts measure contact intensity, mean excess contacts reflect dispersion, which is important for understanding superspreading behaviour. Mean contacts were considerably higher in co-location data (11.04; 95%CI 10.90–11.19) than in survey data (3.38; 95%CI 3.30–3.47); however, both data sources correlated well with each other. Mean excess contacts were similar during periods of strict non-pharmaceutical interventions (NPIs) but diverged when NPIs were lifted, with co-location data values rising more markedly. Setting-specific contact patterns also differed, potentially due to methodological differences in setting classification and data capture. Furthermore, regional variation was more pronounced in co-location data, with densely populated city-states showing higher contact numbers.Comparative insights from the two data sources demonstrate that GPS-based and survey-based contact data capture complementary and distinct aspects of human interaction. Combining both sources could provide a more comprehensive picture of human interactions relevant to infectious disease modelling.

BACKGROUND:Synthetic data hold substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns. However, many current methods suffer from limited quality, high computational demands, and complexity for non-experts. Furthermore, common evaluation strategies for synthetic data often fail to directly reflect statistical utility and measure privacy risks sufficiently. Against this background, a critical underexplored question is whether synthetic data can reliably reproduce key findings from epidemiological research while preserving privacy. METHODS:We propose adversarial random forests (ARF) as an efficient and convenient method for synthesizing tabular epidemiological data. To evaluate its performance, we replicated statistical analyses from six epidemiological publications covering blood pressure, anthropometry, myocardial infarction, accelerometry, loneliness, and diabetes, from the German National Cohort (NAKO Gesundheitsstudie), the Bremen STEMI Registry U45 Study, and the Guelph Family Health Study. We further assessed how dataset dimensionality and variable complexity affect the quality of synthetic data, and contextualized ARF's performance by comparison with commonly used tabular data synthesizers in terms of utility, privacy, generalization, and runtime. RESULTS:Across all replicated studies, results on ARF-generated synthetic data consistently aligned with original findings. Even for datasets with relatively low sample size-to-dimensionality ratios, replication outcomes closely matched the original results across descriptive and inferential analyses. Reduced dimensionality and variable complexity further enhanced synthesis quality. ARF demonstrated favourable performance regarding utility, privacy preservation, and generalization relative to other synthesizers and superior computational efficiency. CONCLUSIONS:In summary, ARF reliably generates high-quality synthetic data that replicate diverse epidemiological analyses while offering a competitive privacy-utility trade-off.

BACKGROUND:Understanding human ageing across multiple organs is essential for characterising individual health trajectories and identifying abnormal ageing processes. Multi-organ imaging provides an opportunity to quantify biological ageing beyond chronological age. The aim of this study is to assess organ-specific and whole-body ageing patterns and their associations with disease and lifestyle factors. METHODS:In this large-scale study, we evaluate biological ageing patterns using 70,000 MRI scans from the UK Biobank and the German National Cohort. We employ 3D ResNet-18 models to predict chronological age from various body regions (brain, heart, liver, spine, lungs, muscle, and intestine) and the whole body. From these predictions, we derive "age gaps" relative to a strictly healthy reference cohort, which enables the identification of accelerated ageing patterns. We then evaluate associations with chronic diseases and lifestyle factors, and a virtual ageing framework was developed to explore counterfactual scenarios by substituting anatomical regions across subjects, quantifying local impacts on global biological age. RESULTS:Here we show significant associations between detected accelerated ageing and specific chronic diseases, including multiple sclerosis and chronic obstructive pulmonary disease, as well as lifestyle factors such as smoking and physical activity. Virtual substitution of anatomical regions demonstrates that local substitutions can influence global ageing patterns. CONCLUSIONS:This study demonstrates that multi-organ imaging enables the detection of abnormal ageing patterns at both local and global levels. The presented framework provides a foundation for improved risk stratification and supports the development of personalised approaches to health assessment and disease prevention.

Objective: To describe the ophthalmic examination protocol within the German National Cohort (NAKO) / NAKO Gesundheitsstudie, to report the baseline profile of participants undergoing ophthalmological assessment, and to illustrate the potential of these data as a population-based open resource for artificial intelligence (AI) research in eye health. Design: Baseline analysis of ophthalmic data within the nationwide, population-based multicenter prospective NAKO study. Participants: 48,460 adults in the ophthalmological level 2 module of 205,053 adults enrolled in NAKO, aged 19-74 years, with mean age 48.9 ± 12.5 years and 52.7% male. Methods: All participants underwent standardized assessments of a wide range of biomedical examinations and detailed questionnaire-based data collection, including non-dilated color fundus imaging, visual acuity testing, recording of a brief ocular history. Ocular and systemic health measures were summarized using descriptive statistics. Fundus image quality and morphological features (e.g. cup-to-disc ratio, ateriole-to-venule-ratio) were assessed using open-source deep learning models. Standard deep learning architectures were trained on the fundus images to predict age, sex and blood pressure. Main Outcome Measures: Percentage of fundus images graded as good quality; mean absolute error for age and blood pressure prediction; accuracy for sex prediction. Results: The analysis includes 48,460 participants who successfully completed the level 2 ophthalmological baseline examination across 18 study sites in Germany. Mean visual acuity (logMAR) was 0.01 ± 0.20 (left eye) and 0.03 ± 0.21 (right eye). Self-reported ocular disease prevalence was 4.2% for cataract, 2.0% for glaucoma, and 0.9% for macular degeneration. 68.2% of fundus images were classified as gradable as a consensus of four deep learning-based quality grading models Morphological features such as cup-to-disc ratio and arteriole-to-venule-ratio showed systematic differences across age groups. Standard deep learning architectures showed comparative performance to the state-of-the-art for age, sex and blood pressure prediction (2.96 MAE for age prediction, 0.84 accuracy for sex prediction, 10.78 and 7.01 MAE for systolic and diastolic blood pressure prediction). Conclusions: NAKO provides a large-scale, nationwide population-based resource with visual acuity measurements and systemic health indicators, as well as color fundus images in about 50,000 NAKO participants. The data sets the ground for studying eye health in the general adult population in Germany and can serve as a strong foundation for developing and validating AI tools in eye health research. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This project was conducted with data from the German National Cohort (NAKO; www.nako.de; Application No. NAKO-590 and NAKO-810). The NAKO is funded by the Federal Ministry of Research, Technology and Space (BMFTR; project funding reference numbers: 01ER1301A/B/C, 01ER1511D, 01ER1801A/B/C/D and 01ER2301A/B/C), federal states of Germany and the Helmholtz Association, the participating universities and the institutes of the Leibniz Association. We thank all participants who took part in the NAKO study and the staff of this research initiative. The project was additionally funded by the Hertie Foundation. PB is a member of the Excellence Cluster 2064 "Machine Learning - New Perspectives for Science" and the NAKO AI expert group. AS and MU are members of the NAKO retina expert group and the NAKO ophthalmic competence unit. AB is a member of the Digital Clinician Scientist Program at University Medical Center Hamburg-Eppendorf (UKE). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This project was conducted with data from the German National Cohort (NAKO; www.nako.de; Application No. NAKO-590 and NAKO-810). The study protocol of NAKO was approved by the ethics committees of all participating institutions, and all participants provided written informed consent in accordance with German legal and data protection requirements. It is conducted in accordance with the Declaration of Helsinki and national standards for good clinical and epidemiological practice. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data is accessible to researchers through the official NAKO Transfer Hub (https://transfer.nako.de), subject to application and approval by the NAKO Use and Access Committee, under established governance and data protection frameworks.

Structural brain alterations associated with depression and anxiety are subtle, heterogeneous, and difficult to characterize. We applied autoencoder-based normative modeling to contrastively learned structural MRI representations from two large population-based cohorts (German National Cohort, N ≈ 29,000; UK Biobank, N ≈ 25,000) to quantify individual deviations from normative brain structure across symptom dimensions of depression, anxiety, and, for contextualization, alcohol use.Deviation magnitude increased with symptom severity for depressive and anxiety symptoms and was most pronounced in individuals with high alcohol use. Directional analyses revealed shared deviation patterns for depression and anxiety that were largely distinct from alcohol-related deviations, and these patterns generalized across cohorts. These affective-symptom-related patterns implicated distributed regional brain-structural variation. Individual deviation profiles improved classification of symptomatic status beyond demographic covariates, with gains concentrated at higher symptom severity.Together, these findings indicate that affective symptoms are associated with reproducible, dimensional patterns of regional brain-structural deviation that extend beyond normative population variability, supporting transdiagnostic models of internalizing psychopathology.

Background Since there is little data on the use of health services by minor patients diagnosed with gender dysphoria (GD), we performed an analysis of German claims data to compare characteristics of gender health service utilization in minors and adults. Method We investigated trends in health service utilization, hormonal treatment initiation, and sex ratios for GD between 2010 and 2021. We compared the age groups of minors and young adults, as well as patients assigned female and male at birth. Results Within the study period, GD incidence changed from 14 to 48 per 100,000 insured persons (RR per year = 1.12, 95% CI = 1.11-1.13) in minors and from 12 to 39 per 100,000 (RR = 1.15 per year, CI = 1.14-1.16) in adults. The majority of minors (72%) as well as adults (67%) in this study were patients assigned female at birth. The proportion of patients who started hormonal treatments within two years after initial diagnosis was relatively higher in those assigned female at birth (34%) than among those assigned male at birth (20%) among minors, but relatively lower in those assigned female at birth (50%) than among those assigned male at birth (63%) among adult patients. Interpretation The incidence of health service utilization for GD under the age of 30 has increased substantially since 2010. However, similar time trends and sex ratios in adults (18-30 y) and adolescents (13-17 y) indicate that the reported trends are not specific to adolescents.

BACKGROUND:Polypharmacy is associated with adverse events, impaired quality of life, and increased mortality, but population-based studies that include both prescribed and over-the-counter (OTC) drugs are scarce. METHODS:We analyzed baseline data from the German National Cohort Study (NAKO), Germany's largest population-based cohort study (recruitment 2014-2019, subjects aged 19-74 at baseline). We determined the prevalence of polypharmacy (defined as the reported regular use of ≥5 prescribed or OTC drugs) and hyperpolypharmacy (≥10 drugs), stratified by sex and age. Determinants of polypharmacy were estimated with logistic regression. RESULTS:Out of 203 765 subjects (mean age 49.8 years, 50.4% female), polypharmacy was present in 6869 women (6.7%, 95% confidence interval [6.5%; 6.8%]) and 8126 men (8.0% [7.9%; 8.2%]), hyperpolypharmacy in 505 women (0.5% [0.45%; 0.54%]) and 722 men (0.7% [0.67%; 0.77%]). Both were more prevalent at older ages. Diabetes mellitus and chronic cardiovascular conditions were strong determinants of polypharmacy, and cardiovascular drugs were the most commonly reported type. CONCLUSION:Polypharmacy was common in the NAKO, particularly in older subjects, men, and people with cardiovascular disease. The appropriateness of drug use could not be assessed in this study. Future studies should examine inappropriate polypharmacy and evaluate risk factors and deprescribing strategies.

The relationship between childhood maltreatment (CM) and obesity is nuanced, and recent evidence suggests stronger associations between CM and obesity-related traits in females compared to males. This study aims to validate and extend these findings in a large sample from the German National Cohort (NAKO). The NAKO is a population-based cohort study including 204,744 adults. For the present analyses, 151,143 individuals (74,596 female) were included. CM was assessed using the Childhood Trauma Screener (CTS). From the CTS, an overall severity score (CTS sum score), a cumulative CM score (number of CM subtypes with at least moderate severity), and five CTS subtypes were considered as exposures. Obesity-related traits included anthropometric (height, weight, body mass index [BMI], waist circumference [WC]) and body fat markers (relative fat mass [rFM], subcutaneous [SAT], visceral adipose tissue [VAT]). Sex-stratified linear and logistic regression models were adjusted for age, education, and examination center to associate CTS-based scores with obesity-related traits. Associations of the CTS sum score with weight, BMI, WC, rFM, and SAT were stronger in females compared to males, while similar associations were observed for VAT. In both sexes, most obesity-related traits exhibited dose-response relationships with increasing numbers of CM subtypes. Compared to unexposed females, females with exposure to ≥3 CM subtypes had a higher risk for obesity (i.e., BMI ≥ 30 kg/m2; OR = 1.56; 95% CI: 1.43, 1.71) and high WC (i.e., WC ≥ 88 cm; OR = 1.39; 95% CI: 1.29, 1.50). In males, exposure to ≥3 CM subtypes was also associated with increased obesity risk (OR = 1.51; 95% CI: 1.32, 1.72) and high WC (i.e., WC ≥ 102 cm; OR = 1.31; 95% CI: 1.18, 1.44). Physical and emotional abuse exhibited the strongest average associations and were associated with the most outcomes. Associations of CM exposure with adult anthropometric and body fat markers are stronger in females compared to males.

INTRODUCTION:The Lifestyle for Brain Health (LIBRA) index evaluates modifiable dementia risk, mainly in midlife and older adults. We examined the frequency of LIBRA factors and their individual and combined associations with cognitive functioning across adulthood (20-75 years), considering age, sex, and socioeconomic status (SES). METHODS:Data came from the population-based German National Cohort (NAKO baseline; n = 149,948). We calculated proportions for LIBRA factors, tested frequency trends, and analyzed cross-sectional associations with cognitive functioning using cluster-adjusted regression controlling for confounders. RESULTS:Behavioral and psychosocial risks (smoking, physical inactivity, depression) were more common in younger adults, while cardiovascular risks (hypertension, coronary heart disease, hypercholesterolemia) predominated in older age. Men had higher LIBRA scores. Higher scores were consistently linked to lower cognitive functioning and lower SES across age groups. DISCUSSION:Dementia risk factors were frequent and already associated with poorer cognition in younger adults, underscoring the need for early, targeted, and equity-oriented prevention.

Objectives Global prevalence of young-onset type 2 diabetes (YOT2D)— diagnosis age 20 – 45—is rising. While clinical drivers such as obesity are known, the role of socio-cultural factors in European high-income settings remain underexplored. We investigated the associations of socioeconomic position (SEP), migration background, and social networks with prevalent YOT2D within the German National Cohort (NAKO). Study design Matched case-control study within the NAKO baseline cohort (recruitment period 2014 – 2019). Methods We matched 808 YOT2D cases in 1:5 ratio to 4035 controls by sex, age, and study center. We applied conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for parental diabetes, lifestyle factors, and body mass index (BMI). We also performed stratified analyses by BMI (cut-off 25 kg/m2) to examine if associations varied across adiposity levels. Results In multivariable-adjusted analyses, low education (OR 2·13, 95%CI 1·44 – 3·15) and poverty-risk household income (OR 2·13, 95%CI 1·54 – 2·94) were associated with two-times higher odds of YOT2D compared to high-status counterparts. First-generation migrants showed higher odds of YOT2D (OR 1·61, 95%CI 1·27 – 2·04) relative to non-migrants. Notably, the association between low education and YOT2D was evident only among individuals with BMI ≥25 kg/m2 (OR 1·76, 95%CI 1·46 – 2·11) but not among those with BMI <25 kg/m2 (OR 0·94, 95%CI 0·70 – 1·27). Conclusions Our results highlight that YOT2D prevalence is associated with socioeconomic disadvantage and migration history. These findings emphasize the urgent need for targeted strategies that address health inequities faced by younger, socioeconomically vulnerable populations.