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Objective: To investigate the reliability of parental recall of birth weight, birth length and gestational age several years after birth., Methods: Parentally recalled birth parameters were obtained from the European multicentric cohort study IDEFICS (Identification and prevention of dietary- and lifestyle-induced health effects in children and infants) and compared to the corresponding data externally recorded in the child's medical check-up booklet. The agreement between the two sources was examined using Bland-Altman plots, intraclass correlation coefficients and Cohen's kappa for clinically relevant categories. Additionally, logistic regression models were used to identify factors related to parental recall accuracy., Results: A total of 4930 children aged 2 to 11 years were included. Accuracy of birth weight within 100 g was 88%, 94% of the recalled birth length was within 2 cm, and 99% of the parents could recall with 2 weeks accuracy how many weeks their child was delivered preterm. Discrepancies of more than two weeks or more than 100 g were more likely in parents of low or medium socioeconomic status. Non-biological parents were 3.4 times more likely to have a discrepancy of more than 100 g compared to biological mothers (95% CI 1.7-6.7). Moreover, parents were less likely to accurately recall their child's birth parameters with increasing number of children within a family., Conclusions for Practice: In general, parents' information matched well with the medical check-up booklet. However, accuracy varied among different groups which should be taken into consideration when using birth data recalled by parents in studies of child health., Competing Interests: Declarations Conflict of interest The authors declare that they have no competing interests. Ethical Approval The study has been approved by the appropriate institutional review boards of all eight study centers (1. Belgium: Ethics Committee of the Gent University Hospital, 15/10/2007, ref: No. EC UZG 2007/243 and 19/02/2013, No. B670201316342; 2. Cyprus: Cyprus National Bioethics Committee, 12/07/2007, ref: No. EEBK/EM/2007/16 and 21/Feb/2013, No. EEBK/ETI/2012/33; 3. Estonia: Tallinn Medical Research Ethics Committee (TMREC), 14/06/2007, ref: No. 1093 and 17/January 2013, No. 128; 4. Germany: Ethic Commission of the University of Bremen, 16/01/2007 and 11/12/2012; 5. Hungary: Medical Research Council, 21/Jun/2007, ref: 22–156/2007-1018EKU and 18/12/2012, 4536/2013/EKU; 6. Italy: Ethics Committee of the Local Health Authority (ASL) in Avellino, 19/06/2007, ref: No. 2/CE and 18/Sep/2012, No. 12/12; 7. Spain: Ethics Committee for Clinical Research of Aragon (CEICA), 20/06/2007, ref: No. PI07/13 and 13/Feb/2013, No. PI13/0012; 8. Sweden: Regional Ethics Research Board in Gothenburg, 30/07/2007, ref: No. 264–07 and 10/Jan/2013, No. 927–12). The study has been performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Consent to Participate Informed consent was obtained from all individual participants included in the study. Before children entered the study, parents provided written informed consent. Additionally, children gave oral consent for examinations and sample collection. Consent for Publication Not applicable., (© 2024. The Author(s).)

Introduction: Pharmacovigilance is vital for drug safety. The process typically involves two key steps: initial signal generation from spontaneous reporting systems (SRSs) and subsequent expert review to assess the signals' (potential) causality and decide on the appropriate action., Methods: We propose a novel discovery and verification approach to pharmacovigilance based on electronic healthcare data. We enhance the signal detection phase by introducing an ensemble of methods which generated signals are combined using Borda count ranking; a method designed to emphasize consensus. Ensemble methods tend to perform better when data is noisy and leverage the strengths of individual classifiers, while trying to mitigate some of their limitations. Additionally, we offer the committee of medical experts with the option to perform an in-depth investigation of selected signals through tailored pharmacoepidemiological studies to evaluate their plausibility or spuriousness. To illustrate our approach, we utilize data from the German Pharmacoepidemiological Research Database, focusing on drug reactions to the direct oral anticoagulant rivaroxaban., Results: In this example, the ensemble method is built upon the Bayesian confidence propagation neural network, longitudinal Gamma Poisson shrinker, penalized regression and random forests. We also conduct a pharmacoepidemiological verification study in the form of a nested active comparator case-control study, involving patients diagnosed with atrial fibrillation who initiated anticoagulant treatment between 2011 and 2017., Discussion: The case study reveals our ability to detect known adverse drug reactions and discover new signals. Importantly, the ensemble method is computationally efficient. Hasty false conclusions can be avoided by a verification study, which is, however, time-consuming to carry out. We provide an online tool for easy application: https://borda.bips.eu., Competing Interests: Author RL was employed by Techniker Krankenkasse – TK. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Dijkstra, Schink, Linder, Schwaninger, Pigeot, Wright and Foraita.)

Childhood obesity is a complex disorder that appears to be influenced by an interacting system of many factors. Taking this complexity into account, we aim to investigate the causal structure underlying childhood obesity. Our focus is on identifying potential early, direct or indirect, causes of obesity which may be promising targets for prevention strategies. Using a causal discovery algorithm, we estimate a cohort causal graph (CCG) over the life course from childhood to adolescence. We adapt a popular method, the so-called PC-algorithm, to deal with missing values by multiple imputation, with mixed discrete and continuous variables, and that takes background knowledge such as the time-structure of cohort data into account. The algorithm is then applied to learn the causal structure among 51 variables including obesity, early life factors, diet, lifestyle, insulin resistance, puberty stage and cultural background of 5112 children from the European IDEFICS/I.Family cohort across three waves (2007-2014). The robustness of the learned causal structure is addressed in a series of alternative and sensitivity analyses; in particular, we use bootstrap resamples to assess the stability of aspects of the learned CCG. Our results suggest some but only indirect possible causal paths from early modifiable risk factors, such as audio-visual media consumption and physical activity, to obesity (measured by age- and sex-adjusted BMI z-scores) 6 years later., (© 2024. The Author(s).)

Digital public health has received a significant boost in recent years, especially due to the demands associated with the COVID-19 pandemic. In this report, we provide an overview of the developments in digitalization in the field of public health in Germany since 2020 and illustrate these with examples from the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH).The following topics are central: How do digital survey methods as well as digital biomarkers and artificial intelligence methods shape modern epidemiology and prevention research? What is the status of digitalization in public health offices? Which approaches to health economics evaluation of digital public health interventions have been utilized so far? What is the status of training and further education in digital public health?The first years of the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH) were also strongly influenced by the COVID-19 pandemic. Repeated population-based digital surveys of the LSC indicated an increase in use of health apps in the population, for example, in applications to support physical activity. The COVID-19-pandemic has also shown that the digitalization of public health enhances the risk of misinformation and disinformation., (© 2024. The Author(s).)

Aims/hypothesis: There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution., Methods: Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin., Results: A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10 -8 ). Two variants associated with low z-insulin (P15, p value <5×10 -6 ) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin., Conclusions/interpretation: The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations., (© 2023. The Author(s).)

Aims: Atrial fibrillation (AF) is a risk factor for brain infarction, which can lead to epilepsy. We aimed to investigate whether treatment of AF with direct oral anticoagulants (DOACs) affects the risk of epilepsy in comparison to treatment with the vitamin K antagonist phenprocoumon (PPC)., Methods and Results: We performed an active comparator, nested case-control study based on the German Pharmacoepidemiological Research Database that includes claims data from statutory health insurance providers of about 25 million persons since 2004. In 2011-17, 227 707 AF patients initiated treatment with a DOAC or PPC, of which 1828 cases developed epilepsy on current treatment with an oral anticoagulant. They were matched to 19 084 controls without epilepsy. Patients with DOAC treatment for AF had an overall higher risk of epilepsy with an odds ratio of 1.39, 95% CI (1.24; 1.55) compared to current PPC treatment. Cases had higher baseline CHA2DS2-VASc scores and more frequently a history of stroke than controls. After excluding patients with ischaemic stroke prior to the diagnosis of epilepsy, the risk of epilepsy was still higher on DOACs than on PPC. In contrast, within a cohort of patients with venous thromboembolism, the risk of epilepsy on treatment with DOACs was less elevated [adjusted odds ratio 1.15, 95% CI (0.98; 1.34)]., Conclusion: In patients with AF initiating oral anticoagulation, treatment with a DOAC was associated with an increased risk of epilepsy compared to the vitamin K antagonist PPC. Covert brain infarction may explain the observed elevated risk of epilepsy., Competing Interests: Conflict of interest: The funder of the study, Federal Joint Committee in Germany, had no influence on the design and conduct of the study, the interpretation of the data, or the decision to publish. K.P., R.F., A.V., I.P., and T.S. are working at an independent, non-profit research institute, the Leibniz Institute for Prevention Research and Epidemiology—BIPS. Unrelated to this study, BIPS occasionally conducts studies financed by the pharmaceutical industry. Almost exclusively, these are post-authorization safety studies requested by health authorities. The design and conduct of these studies as well as the interpretation and publication are not influenced by the pharmaceutical industry. No financial relationships with any organizations that might have an interest in the submitted work in the previous three years; No other relationships or activities that could appear to have influenced the submitted work., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Substantial opportunities for global health intelligence and research arise from the combined and optimised use of secondary data within data ecosystems. Secondary data are information being used for purposes other than those intended when they were collected. These data can be gathered from sources on the verge of widespread use such as the internet, wearables, mobile phone apps, electronic health records, or genome sequencing. To utilise their full potential, we offer guidance by outlining available sources and approaches for the processing of secondary data. Furthermore, in addition to indicators for the regulatory and ethical evaluation of strategies for the best use of secondary data, we also propose criteria for assessing reusability. This overview supports more precise and effective policy decision making leading to earlier detection and better prevention of emerging health threats than is currently the case., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Purpose: In Germany, record linkage of claims and cancer registry data is cost- and time-consuming, since up until recently no unique personal identifier was available in both data sources. The aim of this study was to evaluate the feasibility and performance of a deterministic linkage procedure based on indirect personal identifiers included in the data sources., Methods: We identified users of glucose-lowering drugs with residence in four federal states in Northern and Southern Germany (Bavaria, Bremen, Hamburg, Lower Saxony) in the German Pharmacoepidemiological Research Database (GePaRD) and assessed colorectal and thyroid cancer cases. Cancer registries of the federal states selected all colorectal and thyroid cancer cases between 2004 and 2015. A deterministic linkage approach was performed based on indirect personal identifiers such as year of birth, sex, area of residence, type of cancer and an absolute difference between the dates of cancer diagnosis in both data sources of at most 90 days. Results were compared to a probabilistic linkage using "direct" personal identifiers (gold standard)., Results: The deterministic linkage procedure yielded a sensitivity of 71.8% for colorectal cancer and 66.6% for thyroid cancer. For thyroid cancer, the sensitivity improved when using only inpatient diagnosis to define cancer in GePaRD (71.4%). Specificity was always above 99%. Using the probabilistic linkage to define cancer cases, the risk for colorectal cancer was estimated 10 percentage points lower than when using the deterministic approach., Conclusions: Sensitivity of the deterministic linkage approach appears to be too low to be considered as reasonable alternative to the probabilistic linkage procedure., (© 2022 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19-74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2-3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4-5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years., (© 2022. The Author(s).)

Aims: To describe dispensation patterns of glucose-lowering drugs in newly diagnosed type 2 diabetes in Germany., Materials and Methods: Based on claims data from four statutory health insurances (German Pharmacoepidemiological Research Database,>25 million insurants), all individuals with newly diagnosed type 2 diabetes were identified. Eligible patients had a first diagnosis for type 2 diabetes between January 2012 and December 2016. We analyzed the dispensation patterns of first-line glucose-lowering therapies initiated in the year after diabetes diagnosis and patterns of second-line therapies dispensed one year after first-line treatment., Results: A total of 356,647 individuals with newly diagnosed type 2 diabetes were included (average age [SD]: 63.5 [13.4] years; 49.3% males). Of the 31.6% of individuals who were pharmacologically treated in the year after diagnosis, metformin monotherapy was most frequently dispensed (73.1%), followed by dual therapy of metformin and dipeptidyl peptidase-4 inhibitors (DPP-4is) (6.4%), and monotherapy with DPP-4is (2.9%). From 2012 through 2016, sulfonylurea dispensations were reduced by more than 50%. Dispensations for combination therapies with DPP-4is increased up to 10.6%. Glucagon-like peptide-1 receptor agonists and sodium-glucose co-transporter-2 inhibitors contributed to 2% of all treatments. After a median of 5 months, 20.0% of individuals on pharmacological therapy initiated second-line glucose-lowering treatment., Conclusions: Data from German statutory health insurances (2012 to 2016) showed that most individuals with newly diagnosed type 2 diabetes were dispensed metformin monotherapy in line with diabetes care guidelines. A substantial decrease in the use of sulfonylureas was observed after the introduction of DPP-4i and GLP-1 receptor agonists., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Background: In recent years, there has been an increasing demand for the reuse of research data in accordance with the so-called FAIR principles. This would allow researchers to conduct projects on a broader data basis and to investigate new research questions by linking different data sources., Objectives: We explored if nationwide linking of claims data from statutory health insurances (SHI) with data from population-based cancer registries can be used to obtain additional information on cancer that is missing in claims data and to assess the validity of SHI tumour diagnoses. This paper focuses on describing the specific requirements of German federal states for such data linkage., Materials and Methods: The Pharmacoepidemiological Research Database GePaRD at the Leibniz Institute for Prevention Research and Epidemiology - BIPS and six cancer registries were used as data sources. The logistically complex direct linkage was compared with a less complex indirect linkage. For this purpose, permission had to be obtained for GePaRD and for each cancer registry from the respective responsible authority., Results: Regarding the linkage of cancer registry data with GePaRD, the cancer registries showed profound differences in the modalities for data provision, ranging from a complete rejection to an uncomplicated implementation of linkage procedures., Discussion: In Germany, a consistent legal framework is needed to adequately enable the reuse and record linkage of personal health data for research purposes according to the FAIR principles. The new law on the consolidation of cancer registry data could provide a remedy regarding the linkage of cancer registry data with other data sources., (© 2021. The Author(s).)