Zusammenfassung Public Health in Deutschland steht angesichts geopolitischer Spannungen und bewaffneter Konflikte vor einem Dilemma zwischen der idealistischen, pazifistischen Perspektive der Ottawa-Charta und einer realpolitischen Perspektive, die Resilienz und Verteidigungsbereitschaft fordert. Public Health hat sich noch zu wenig mit den eigenen Aufgaben angesichts hybrider und militärischer Bedrohung befasst. Das erfordert selbstkritische Reflexion und nachholende Entwicklung in Lehre, Forschung und Praxis.

Estimating the contributing de facto population is essential for deriving per-capita rates in wastewater-based epidemiology (WBE), yet remains a major methodological challenge, particularly at the sub-sewershed scale. This pilot study uses sold-out football matches with well-documented, large-scale population fluctuations as a natural experiment to explore wastewater quality parameters as dynamic population normalization proxies in small-scale sub-sewersheds. Hourly wastewater samples (n = 24) were collected during pre-defined match periods from two sub-sewersheds with contrasting characteristics in the Ruhr area, Germany. Total nitrogen (TN), ammonium nitrogen (NH₄-N), chemical oxygen demand, and biochemical oxygen demand after five days were quantified as normalization proxies. Pharmaceutical compounds were used as exemplary human-specific biochemical markers to evaluate the feasibility of dynamic population normalization. Hourly mass loads were calculated using continuous flowmeter data, z-score standardised for temporal comparison, and used to estimate de facto populations from site-specific per-capita emission rates. All four wastewater quality parameters captured match-related population dynamics, with clearer signals in the smaller, stadium-dominated sub-sewershed. TN and NH₄-N provided the most comparable de facto population estimates in the larger sub-sewershed (mean de facto/de jure ratios of 1.04 for both), whereas all parameters substantially over- or underestimated the reference population in the smaller one. Dynamic normalization using TN and NH₄-N indicated that population influx, rather than elevated per-capita consumption, was the primary driver of match-related increases in pharmaceutical loads. Our results suggest that normalization proxy performance is sewershed-dependent, even at smaller spatial scales, and highlights the importance of context-specific proxy selection and subsequent validation in small-scale WBE.

Supplementary Figure from eQTL Set–Based Association Analysis Identifies Novel Susceptibility Loci for Barrett Esophagus and Esophageal Adenocarcinoma

Wastewater-based epidemiology (WBE) is a promising approach for assessing population-level exposures to toxicants and lifestyle factors. Our pilot investigated the spatial variability of biomarkers indicating exposure to nicotine and endocrine disrupting chemicals in municipal wastewater, taking into account important covariates, i.e. physicochemical wastewater parameters and sewershed characteristics. We also tested normalization by an endogenous population marker. Twenty-four-hour composite samples (n = 24) were collected in a volume-proportional manner using automated samplers from four wastewater treatment plants in Essen, Germany, over three weeks in late 2023. Substances of public health concern, previously already quantified in wastewater and expected to be present in high concentrations, were analyzed using SPE-LC-HRMS. Concentrations were normalized to the reported population (de jure) and the daily mass load of the catecholamine metabolite vanillylmandelic acid (VMA) as a proxy for the de facto population. Spatial variations were analyzed using multiple linear regression. Nicotine metabolites (cotinine, hydroxycotinine) and the industrial chemical Bisphenol A (BPA) were quantifiable in all wastewater samples. The population-normalized daily mass load of nicotine metabolites (median range: 0.6-1.6 g/d/1000 inh) and BPA (2.5-4.0 g/d/1000 inh) varied between the WWTPs, but the observed variation disappeared when adjusting for wastewater temperature (nicotine) and wastewater pH (BPA). Normalization to the VMA daily mass load resulted in different spatial patterns and increased the variance considerably. Our findings highlight the importance of adjusting for physicochemical characteristics when analyzing community-wide differences in exposure to toxicants and lifestyle factors via wastewater, to ensure accurate interpretations of the underlying drivers of these differences.

During a migraine attack, patients with migraine experience non-persistent cognitive impairment. However, some studies discuss migraine also as a risk factor for dementia in later life. The evidence, particularly with regard to mild cognitive impairment (MCI) as a precursor to dementia, is controversial. The aim of this study is to investigate the risk of incident MCI after five years in initially cognitively healthy participants with vs. without migraine. 2476 participants of the second (t1) and third (t2) examination of the prospective, population-based Heinz Nixdorf Recall Study (t1: 2005-2009, Ø62.9 years; t2: 2010-2015, Ø68.1 years) with complete data on migraine status (t1), cognitive performance (T1&T2) and age-appropriate cognition (t1) were included. MCI (at t2) was defined according to Winblad et al. (2004); migraine (at t1) was defined as self-reported diagnosis. Log-linear regression analyses with Poisson distribution were used to calculate the relative risk (RR) for incident MCI with 95% confidence interval (CI) for migraine vs. no migraine (unadjusted; adjusted for age, sex, education, alcohol consumption, smoking status, body mass index, depression according to directed acylic graph). 328 (13.2%) of the 2476 participants reported a migraine. Overall, 28 (8.5%) participants with migraine vs. 239 (11.1%) without migraine met the criteria for MCI at t2. There was no increased risk of incident MCI (unadjusted: RR 0.77, 95% CI 0.52-1.14; adjusted: RR 0.77, 95% CI 0.52-1.16) in participants with migraine. Even though migraine attacks impair cognitive performance, our data show no longitudinal association between migraine and MCI as a precursor to dementia. In further analyses, a distinction should be made between migraine with and without aura.

Type 2 diabetes mellitus (T2DM) is considered a risk factor for dementia. The association of T2DM and mild cognitive impairment (MCI) is reported inconsistently and appears to be gender- and age-specific. The aim of the present study was to investigate the (gender- and age-specific) risk of incident MCI five years later in initially cognitively healthy participants with vs. without known T2DM. 1467 subjects of the second (t1) and third (t2) follow-up examination of the prospective, population-based Heinz Nixdorf Recall Study (t1: 2005-2009, Ø62.9 years; t2: 2010-2015, Ø68.1 years) with complete data regarding T2DM (t1), complete cognitive assessments (t1&t2) and with a cognitive performance within the age- and education-adjusted norm (cognitively healthy; t1) were included. MCI at t2 was defined present, if the cognitive performance was below the age- and education-adjusted norm in at least one cognitive domain with or without reported subjective cognitive decline. Known T2DM (t1) was defined as self-reported physician-confirmed diagnosis or use of antidiabetic medication (n = 145 (9.8%)). Using log-linear regression analyses with Poisson distribution, the relative risk (RR) for incident MCI with 95% confidence interval (CI) for T2DM vs. no T2DM was calculated (adjusted (adj.) for age, body mass index, smoking status according to directed acyclic graph; stratified by gender and age (50-65 years, middle-aged & 66-80 years, old-aged)). Overall, 57 (39.3%) participants with T2DM vs. 363 (27.5%) without T2DM met criteria for MCI at t2. There was an increased RR of incident MCI (adj.: RR 1.31, 95% CI 0.98-1.74) in participants with T2DM at t1. After stratification, the association was primarily present in middle-aged participants (adj.: RR 1.67, 95% CI 1.09-2.56 vs. RR 1.09, 95% CI 0.74.-1.60 in old-aged participants), especially in middle-aged men (adj.: RR 1.84, 95% CI 1.09-3.11 vs. RR 1.29, 95% CI 0.59-2.83 in middle-aged women). Our longitudinal data confirm T2DM as a risk factor for incident MCI, especially for men aged 50-65 years. Prevention of T2DM therefore could help to preserve cognitive performance and delay the development of dementia.

Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer's disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.

Wastewater-based epidemiology (WBE) offers valuable population-level health insights. Sampling within sewer systems enables small-scale differentiation, but requires accurate local population data. Allocating population data to sewersheds is complicated by mismatched administrative and sewershed boundaries, for which no established method exists. This study introduces and evaluates two methods for estimating sub-sewershed populations: Proportional Building-based Population Estimation (PBPE) and the Spatial Grid Population Estimation (SGPE). Both were compared with the reported population figures and the result of a simple overlay procedure. The methods were then applied to characterize populations in 195 sub-sewersheds in a large German metropolitan area. PBPE reallocates population data by weighting intersecting city sub-units based on the number of residential buildings, while SGPE uses inverse-distance weighting to interpolate population density based on residential land use across a hexagonal lattice. Despite different data requirements and methodologies, both estimators produced highly concordant results with strong correlations between estimated and reported population numbers (Pearson r: 0.97 for both) and between estimates for all population-related parameters (Pearson r range: 0.89-0.95). Median deviations were-0.6% (PBPE) and +3.3% (SGPE) for total population, and under 5% across age and socio-economic strata. The strong agreement confirms both estimators are reliable. PBPE shows lower deviations but requires detailed building data and is sensitive to missing structures and uniform-occupancy assumptions. SGPE works without exhaustive building footprints but depends on user-selected grid parameters. This study provides an empirical basis for improving small-scale WBE data use and interpretability in densely populated urban areas, facilitating an improved public health database.

A polygenic score (PGS) for Alzheimer's disease (AD) was derived recently from data on genome-wide significant loci in European ancestry populations. We applied this PGS to populations in 17 European countries and observed a consistent association with the AD risk, age at onset and cerebrospinal fluid levels of AD biomarkers, independently of apolipoprotein E locus (APOE). This PGS was also associated with the AD risk in many other populations of diverse ancestries. A cross-ancestry polygenic risk score improved the association with the AD risk in most of the multiancestry populations tested when the APOE region was included. Finally, we found that the PGS/polygenic risk score captured AD-specific information because the association weakened as the diagnosis was broadened. In conclusion, a simple PGS captures the AD-specific genetic information that is common to populations of different ancestries, although studies of more diverse populations are still needed to better characterize the genetics of AD.

Objectives:Polygenic hazard score (PHS) models can be used to predict the age-associated risk for complex diseases, including Alzheimer's disease (AD). In this study, we present an improved PHS model for AD that incorporates a large number of genetic variants and demonstrates enhanced predictive accuracy for age of onset in European populations compared to alternative models. Methods:We used the genotyped European Alzheimer & Dementia Biobank (EADB) sample (n=42,120) to develop and evaluate the performance of the PHS model. We developed a PHS model building on 720 genetic variants, including Apolipoprotein E (APOE) ε2 and ε4 alleles. We used Elastic Net-regularized Cox regression approach to develop the PHS model. Results:The new PHS model (EADB720) improved prediction accuracy compared to alternative models in European populations, with the Odds Ratio OR80/20 from the highest quintile of risk (80th risk percentile and above) to the lowest quintile of risk (20th risk percentile and below) varying between 5.10 and 13.15 within the range of age of onset from 65 - 85 years. Our model also improved risk stratification across ε3/3 individuals of European ancestry (OR80/20 ranges from 1.95 to 3.52). It was also successfully validated in independent datasets (HUSK, DemGene and ADNI) by achieving OR80/20 up to 10.00 in each independent dataset. Conclusion:Our EADB720 model significantly improves the accuracy of age-associated risk of AD across European populations (pval<0.03). Accurately predicting the age of onset of AD is of large clinical importance to implementing new AD medication and early intervention in clinical settings.

In humans, night shift work is a major reason for chronodisruption, may affect health and increase the risk of a metabolic syndrome, but results obtained so far are ambiguous. In this population-based, cross-sectional study, PRESENT and FORMER shift workers were compared to age- and sex-matched controls, who never worked in shift with regard to body mass index, waist-hip-ratio total, high-density lipoprotein and low-density lipoprotein, cholesterol and C-reactive protein. Moreover, association with sex, length of shift work and medication were investigated. The present results do not support the hypothesis that night shift work per se is associated to an increased risk of metabolic syndrome, and cardiovascular and immune malfunctions: no differences were found in mean anthropomteric and blood values between present or former shift workers and respective matched controls. When analyzing the proportion of participants showing values beyond the clinically relevant cut-offs, no general effect of shift work was observed, but the data may suggest an interaction between shift work and sex. These divergent results may be due to differences in the socio-economic status, the health care system and the shift schedule. All these parameters need to be considered in future studies addressing the impact of night shiftwork on human health.

Older adults exhibit greater heterogeneity than younger adults in behavior, cognition, and brain, which may be influenced by a range of factors, including lifestyle. While previous studies have assessed brain heterogeneity by evaluating the dissimilarity of individual brain connectivity, further empirical evidence is needed to understand the factors behind brain heterogeneity in older adults. Using data from the 1000BRAINS study (N = 461, aged 55-85 years), we analyzed the individual variability (IV) of the functional (IVFC) and structural (IVSC) connectivity across 421 brain regions. We aimed to explore the relationship between network-wise and region-wise brain connectivity IV (i.e., both IVFC and IVSC), lifestyle, including psycho-social factors (e.g., self-reported smoking, physical activity, alcohol consumption, and social integration), and cognitive function via partial least squares correlation, stratifying analyses by age subgroups (55-64, 65-74, and ≥ 75 years), separately. Our results showed that higher connectivity IV was linked to lower social integration and/or higher smoking, and lower cognitive performance (e.g., episodic memory and executive control). For the network-wise analysis, we observed contributions from both IVFC and IVSC across eight networks, especially IVSC in the salience and ventral attention networks. Region-wise, significant contributions came primarily from the connectivity IV of specific brain regions (e.g., inferior frontal gyrus, right anterior cingulate cortex). This result pattern varied by age group. Connectivity IV was positively correlated with smoking in the age 65-74 group and negatively correlated with alcohol consumption in the age ≥ 75 years group. Overall, IVSC contributed more than IVFC with age. These findings suggest that unhealthy lifestyle and social isolation might be associated with differences in neural resources, which may be linked to increased individual brain heterogeneity and, in turn, to lower cognitive performance in older adults, supporting the revised Scaffolding Theory of Aging and Cognition (STAC-r).

Despite Germany's robust economy, comprehensive social welfare system, and the country ranking third among Organisation for Economic Co-operation and Development countries in terms of per-capita health spending, its health indicators still lag behind those of other European nations. Germany also has one of the highest prevalences of major modifiable risk factors for non-communicable diseases within the EU. This Health Policy provides an overview of the development, structures, and actors in public health in Germany, highlighting possible explanations for the country's underperforming health indicators and suggesting a way forward. This Health Policy is structured along the essential public health operations. We identify the absence of a strong central institution for public health, inadequate funding for disease prevention and health promotion, and little interoperability in data collection as major challenges. The country's decentralised governance structure allows flexibility, especially at the community level, but leads to scattered responsibilities and little coordination between sectors. We also note the absence of a public health strategy. The current system's focus on curative care and individualised medicine has led to a neglect of disease prevention and health promotion. Furthermore, the country's strong economic interests and powerful lobbies have hindered the implementation of effective public health policies. To address these challenges, we recommend developing a public health identity, creating a comprehensive public health strategy, fostering a culture of health promotion and disease prevention that encompasses all areas and does not shy away from tackling the commercial determinants of health, and strengthening the connection between medicine, public health practice, and research.

Introduction:As studies on the association between type 2 diabetes mellitus (T2DM) and mild cognitive impairment (MCI), including amnestic (aMCI) and non-amnestic (naMCI) subtypes, vary by sex and age, we investigated the sex- and age-specific effects of T2DM on incident MCI after five years in a population-based sample. Methods:A total of 145 participants with T2DM and 1322 without T2DM were included. MCI was defined using established criteria excluding subjective cognitive decline. Adjusted relative risks (aRRs) were calculated considering age, education, body mass index, smoking, and alcohol intake, and stratified by sex and age (middle-aged: 50-65 years; old-aged: 66-80 years). Results:MCI occurred in 39.3% (n = 57) of participants with T2DM versus 27.5% (n = 363) without (aRR: 1.29, 95% confidence interval [CI]: 0.97-1.73). Middle-aged men showed an association with naMCI (aRR: 2.35, 95% CI: 1.26-4.39) and middle-aged women with aMCI (aRR: 2.05, 95% CI: 0.58-7.21). Discussion:T2DM increases MCI risk, particularly in middle-aged individuals with poorly controlled T2DM, emphasizing the need for prevention strategies. Highlights:Longitudinal results from the population-based Heinz Nixdorf Recall study in Germany.Incident mild cognitie impairment (MCI) was more common in type 2 diabetes mellitus (T2DM; 39% vs 28%).T2DM affects incident MCI and subtypes in middle-aged, not old-aged; stronger in men with poorly controlled T2DM.Importance of enhancing age- and sex-specific prevention at the population level.

The reliable assessment of characteristics of shift-work exposure remains a critical methodological issue in epidemiological studies. A working group of the International Agency for Research on Cancer developed recommendations for the assessment of shift-work. These were translated into a detailed interview for the 10-year follow-up of the Heinz Nixdorf Recall (HNR) cohort. This study investigated the agreement of shift-work characteristics between three different assessments that were administered in interviews at two time points. At the study baseline (2000-2003), 4,814 participants were enrolled, and brief shift-work information was collected for 2,121 working participants (1,244 men and 877 women aged 45-75 years). Of 2,613 cohort members in the prospective 10-year follow-up between 2011 and 2013, 2,444 (also non-working) individuals participated in detailed shift-work interviews that consisted of (a) key summary questions and (b) period-based shift-work histories. participants' shift-work exposures up to the study baseline were compared in 1,217 subjects who were interviewed during both the baseline and the follow-up. Within the follow-up, participant responses to key summary questions were compared with calculated parameters from period-based histories. Agreement was measured by simple agreement (%), Gwet's agreement coefficient 1 (Gwet's AC1), and intraclass correlation coefficients (ICC) with 95% confidence intervals (CI). Beta-regression models were applied to investigate potential associations between age and sex with the reliability of shift-work characteristics. A high level of agreement was found between ever having worked shift-work (ever shift-work) and duration that each participant worked shift-work (duration of shift-work) reported during baseline and at follow-up (ever shift-work until study baseline in men: Gwet's AC1 = 0.77 (CI 0.72-0.82)). When comparing key summary questions and detailed shift-work histories, the duration of shift-work showed a high level of reliability that marginally decreased with age (in women ICC = 0.96 (CI 0.95-0.97), linear effect of age groups on µ: p = 0.08). Participants had problems remembering more detailed shift-work information. Ever shift-work and duration of shift-work can be assessed with key summary questions but reliability slightly decreases with age.

BACKGROUND:During a migraine attack, patients with migraine experience non-persistent cognitive impairment. However, some studies discuss migraine also as a risk factor for dementia in later life. The evidence, particularly with regard to mild cognitive impairment (MCI) as a precursor to dementia, is controversial. The aim of this study is to investigate the risk of incident MCI after five years in initially cognitively healthy participants with vs. without migraine. METHOD:2476 participants of the second (t1) and third (t2) examination of the prospective, population-based Heinz Nixdorf Recall Study (t1: 2005-2009, Ø62.9 years; t2: 2010-2015, Ø68.1 years) with complete data on migraine status (t1), cognitive performance (T1&T2) and age-appropriate cognition (t1) were included. MCI (at t2) was defined according to Winblad et al. (2004); migraine (at t1) was defined as self-reported diagnosis. Log-linear regression analyses with Poisson distribution were used to calculate the relative risk (RR) for incident MCI with 95% confidence interval (CI) for migraine vs. no migraine (unadjusted; adjusted for age, sex, education, alcohol consumption, smoking status, body mass index, depression according to directed acylic graph). RESULT:328 (13.2%) of the 2476 participants reported a migraine. Overall, 28 (8.5%) participants with migraine vs. 239 (11.1%) without migraine met the criteria for MCI at t2. There was no increased risk of incident MCI (unadjusted: RR 0.77, 95% CI 0.52-1.14; adjusted: RR 0.77, 95% CI 0.52-1.16) in participants with migraine. CONCLUSION:Even though migraine attacks impair cognitive performance, our data show no longitudinal association between migraine and MCI as a precursor to dementia. In further analyses, a distinction should be made between migraine with and without aura.

Wastewater analysis is a promising approach to obtaining population-based health information. It has proven useful for different applications, including monitoring illicit drugs or assessing population-level exposure to chemicals. Studies have often analysed samples from wastewater treatment plants, which does not allow for small-scale intra-sewershed differentiations needed for a detailed assessment of the target population. The small-scale approach offers various benefits, but a comprehensive review of its application to chemicals has not yet been undertaken. This scoping review aims to provide a detailed overview of the current knowledge on wastewater analysis of chemical markers of public health concern, including methodological aspects. We conducted a systematic database search for peer-reviewed articles. Data were analysed using quantitative summaries and qualitative narrative synthesis. Out of 2283 articles, 99 studies were included. Most were published after 2010. The studies analysed wastewater from different settings, with a focus on points of interest such as healthcare and education facilities, and few studies at neighbourhood-level. Pharmaceuticals, industrial and environmental chemicals and stimulants were most commonly investigated. While most studies reported their sampling mode, few provided detailed specifications. Small-scale sampling sites were characterized to varying degrees, with many studies reporting only a single characterization criterion. Advancing the area of research of small-scale wastewater analysis requires consistent and transparent methodological reporting and a more detailed sampling site characterization. Wastewater analysis of chemical markers of public health concern at small spatial scales shows great potential for further public health applications, including occupational health and monitoring chemical exposure in schools.

Among the more than 90 identified genetic risk loci for late-onset Alzheimer's disease (AD) and related dementias, the apolipoprotein E gene (APOE) ε2/ε3/ε4 polymorphism remains the longstanding benchmark for genetic disease risk with a consistently large effect across studies1-10. Despite this massive signal, the exact mechanisms for how ε4 increases and for how ε2 decreases dementia risk is not well-understood. Importantly, recent trials of anti-amyloid therapies suggest less efficacy and higher risks of severe side effects in s4 carriers11-13, hampering the treatment of those with the highest unmet need. To improve our understanding of the genetic architecture of AD in the context of its main genetic driver, we performed genome-wide association studies (GWASs) stratified by ε4 and ε2 carrier status. Such insights may help to understand and overcome side effects, to impact clinical trial enrolment strategies, and to create the scientific basis for targeted mechanism-driven therapies in neurodegenerative diseases.