TY - JOUR A1 - Schmiemann, Guido A1 - Greser, Alexandra A1 - Maun, Andy A1 - Bleidorn, Jutta A1 - Schuster, Angela A1 - Miljukov, Olga A1 - Rücker, Viktoria A1 - Klingeberg, Anja A1 - Mentzel, Anja A1 - Minin, Vitalii A1 - Eckmanns, Tim A1 - Heintze, Christoph A1 - Heuschmann, Peter A1 - Gágyor, Ildikó T1 - Effects of a multimodal intervention in primary care to reduce second line antibiotic prescriptions for urinary tract infections in women: parallel, cluster randomised, controlled trial JF - BMJ N2 - Objectives To evaluate whether a multimodal intervention in general practice reduces the proportion of second line antibiotic prescriptions and the overall proportion of antibiotic prescriptions for uncomplicated urinary tract infections in women. Design Parallel, cluster randomised, controlled trial. Setting General practices in five regions in Germany. Data were collected between 1 April 2021 and 31 March 2022. Participants General practitioners from 128 randomly assigned practices. Interventions Multimodal intervention consisting of guideline recommendations for general practitioners and patients, provision of regional data for antibiotic resistance, and quarterly feedback, which included individual first line and second line proportions of antibiotic prescribing, benchmarking with regional or supra-regional practices, and telephone counselling. Participants in the control group received no information on the intervention. Main outcome measures Primary outcome was the proportion of second line antibiotics prescribed by general practices, in relation to all antibiotics prescribed, for uncomplicated urinary tract infections after one year between the intervention and control group. General practices were randomly assigned in blocks (1:1), with a block size of four, into the intervention or control group using SAS version 9.4; randomisation was stratified by region. The secondary outcome was the prescription proportion of all antibiotics, relative within all cases (instances of UTI diagnosis), for the treatment of urinary tract infections after one year between the groups. Adverse events were assessed as exploratory outcomes. Results 110 practices with full datasets identified 10 323 cases during five quarters (ie, 15 months). The mean proportion of second line antibiotics prescribed was 0.19 (standard deviation 0.20) in the intervention group and 0.35 (0.25) in the control group after 12 months. After adjustment for preintervention proportions, the mean difference was −0.13 (95% confidence interval −0.21 to −0.06, P<0.001). The overall proportion of all antibiotic prescriptions for urinary tract infections over 12 months was 0.74 (standard deviation 0.22) in the intervention and 0.80 (0.15) in the control group with a mean difference of −0.08 (95% confidence interval −0.15 to −0.02, P<0.029). No differences were noted in the number of complications (ie, pyelonephritis, admission to hospital, or fever) between the groups. Conclusions The multimodal intervention in general practice significantly reduced the proportion of second line antibiotics and all antibiotic prescriptions for uncomplicated urinary tract infections in women. Trial registration German Clinical Trials Register (DRKS), DRKS00020389 KW - urinary tract infections KW - women KW - multimodal intervention KW - second line antibiotics Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349395 SN - 1756-1833 VL - 383 ER - TY - JOUR A1 - Helmer, Philipp A1 - Rodemers, Philipp A1 - Hottenrott, Sebastian A1 - Leppich, Robert A1 - Helwich, Maja A1 - Pryss, Rüdiger A1 - Kranke, Peter A1 - Meybohm, Patrick A1 - Winkler, Bernd E. A1 - Sammeth, Michael T1 - Evaluating blood oxygen saturation measurements by popular fitness trackers in postoperative patients: a prospective clinical trial JF - iScience N2 - Summary Blood oxygen saturation is an important clinical parameter, especially in postoperative hospitalized patients, monitored in clinical practice by arterial blood gas (ABG) and/or pulse oximetry that both are not suitable for a long-term continuous monitoring of patients during the entire hospital stay, or beyond. Technological advances developed recently for consumer-grade fitness trackers could—at least in theory—help to fill in this gap, but benchmarks on the applicability and accuracy of these technologies in hospitalized patients are currently lacking. We therefore conducted at the postanaesthesia care unit under controlled settings a prospective clinical trial with 201 patients, comparing in total >1,000 oxygen blood saturation measurements by fitness trackers of three brands with the ABG gold standard and with pulse oximetry. Our results suggest that, despite of an overall still tolerable measuring accuracy, comparatively high dropout rates severely limit the possibilities of employing fitness trackers, particularly during the immediate postoperative period of hospitalized patients. Highlights •The accuracy of O2 measurements by fitness trackers is tolerable (RMSE ≲4%) •Correlation with arterial blood gas measurements is fair to moderate (PCC = [0.46; 0.64]) •Dropout rates of fitness trackers during O2 monitoring are high (∼1/3 values missing) •Fitness trackers cannot be recommended for O2 measuring during critical monitoring KW - multidisciplinary KW - health sciences KW - clinical measurement in health technology KW - bioelectronics KW - fitness trackers Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349913 SN - 2589-0042 VL - 26 IS - 11 ER - TY - THES A1 - Allgaier, Johannes T1 - Machine Learning Explainability on Multi-Modal Data using Ecological Momentary Assessments in the Medical Domain T1 - Erklärbarkeit von maschinellem Lernen unter Verwendung multi-modaler Daten und Ecological Momentary Assessments im medizinischen Sektor N2 - Introduction. Mobile health (mHealth) integrates mobile devices into healthcare, enabling remote monitoring, data collection, and personalized interventions. Machine Learning (ML), a subfield of Artificial Intelligence (AI), can use mHealth data to confirm or extend domain knowledge by finding associations within the data, i.e., with the goal of improving healthcare decisions. In this work, two data collection techniques were used for mHealth data fed into ML systems: Mobile Crowdsensing (MCS), which is a collaborative data gathering approach, and Ecological Momentary Assessments (EMA), which capture real-time individual experiences within the individual’s common environments using questionnaires and sensors. We collected EMA and MCS data on tinnitus and COVID-19. About 15 % of the world’s population suffers from tinnitus. Materials & Methods. This thesis investigates the challenges of ML systems when using MCS and EMA data. It asks: How can ML confirm or broad domain knowledge? Domain knowledge refers to expertise and understanding in a specific field, gained through experience and education. Are ML systems always superior to simple heuristics and if yes, how can one reach explainable AI (XAI) in the presence of mHealth data? An XAI method enables a human to understand why a model makes certain predictions. Finally, which guidelines can be beneficial for the use of ML within the mHealth domain? In tinnitus research, ML discerns gender, temperature, and season-related variations among patients. In the realm of COVID-19, we collaboratively designed a COVID-19 check app for public education, incorporating EMA data to offer informative feedback on COVID-19-related matters. This thesis uses seven EMA datasets with more than 250,000 assessments. Our analyses revealed a set of challenges: App user over-representation, time gaps, identity ambiguity, and operating system specific rounding errors, among others. Our systematic review of 450 medical studies assessed prior utilization of XAI methods. Results. ML models predict gender and tinnitus perception, validating gender-linked tinnitus disparities. Using season and temperature to predict tinnitus shows the association of these variables with tinnitus. Multiple assessments of one app user can constitute a group. Neglecting these groups in data sets leads to model overfitting. In select instances, heuristics outperform ML models, highlighting the need for domain expert consultation to unveil hidden groups or find simple heuristics. Conclusion. This thesis suggests guidelines for mHealth related data analyses and improves estimates for ML performance. Close communication with medical domain experts to identify latent user subsets and incremental benefits of ML is essential. N2 - Einleitung. Unter Mobile Health (mHealth) versteht man die Nutzung mobiler Geräte wie Handys zur Unterstützung der Gesundheitsversorgung. So können Ärzt:innen z. B. Gesundheitsinformationen sammeln, die Gesundheit aus der Ferne überwachen, sowie personalisierte Behandlungen anbieten. Man kann maschinelles Lernen (ML) als System nutzen, um aus diesen Gesundheitsinformationen zu lernen. Das ML-System versucht, Muster in den mHealth Daten zu finden, um Ärzt:innen zu helfen, bessere Entschei- dungen zu treffen. Zur Datensammlung wurden zwei Methoden verwendet: Einerseits trugen zahlreiche Personen zur Sammlung von umfassenden Informationen mit mo- bilen Geräten bei (sog. Mobile Crowdsensing), zum anderen wurde den Mitwirkenden digitale Fragebögen gesendet und Sensoren wie GPS eingesetzt, um Informationen in einer alltäglichen Umgebung zu erfassen (sog. Ecologcial Momentary Assessments). Diese Arbeit verwendet Daten aus zwei medizinischen Bereichen: Tinnitus und COVID-19. Schätzungen zufolge leidet etwa 15 % der Menschheit an Tinnitus. Materialien & Methoden. Die Arbeit untersucht, wie ML-Systeme mit mHealth Daten umgehen: Wie können diese Systeme robuster werden oder neue Dinge lernen? Funktion- ieren die neuen ML-Systeme immer besser als einfache Daumenregeln, und wenn ja, wie können wir sie dazu bringen, zu erklären, warum sie bestimmte Entscheidungen treffen? Welche speziellen Regeln sollte man außerdem befolgen, wenn man ML-Systeme mit mHealth Daten trainiert? Während der COVID-19-Pandemie entwickelten wir eine App, die den Menschen helfen sollte, sich über das Virus zu informieren. Diese App nutzte Daten der Krankheitssymptome der App Nutzer:innen, um Handlungsempfehlungen für das weitere Vorgehen zu geben. Ergebnisse. ML-Systeme wurden trainiert, um Tinnitus vorherzusagen und wie er mit geschlechtsspezifischen Unterschieden zusammenhängen könnte. Die Verwendung von Faktoren wie Jahreszeit und Temperatur kann helfen, Tinnitus und seine Beziehung zu diesen Faktoren zu verstehen. Wenn wir beim Training nicht berücksichtigen, dass ein App User mehrere Datensätze ausfüllen kann, führt dies zu einer Überanpassung und damit Verschlechterung des ML-Systems. Interessanterweise führen manchmal einfache Regeln zu robusteren und besseren Modellen als komplexe ML-Systeme. Das zeigt, dass es wichtig ist, Experten auf dem Gebiet einzubeziehen, um Überanpassung zu vermeiden oder einfache Regeln zur Vorhersage zu finden. Fazit. Durch die Betrachtung verschiedener Langzeitdaten konnten wir neue Empfehlun- gen zur Analyse von mHealth Daten und der Entwicklung von ML-Systemen ableiten. Dabei ist es wichtig, medizinischen Experten mit einzubeziehen, um Überanpassung zu vermeiden und ML-Systeme schrittweise zu verbessern. KW - Maschinelles Lernen KW - Explainable Artificial Intelligence KW - Mobile Health KW - Machine Learning KW - Explainable AI KW - Mobile Crowdsensing KW - Ecological Momentary Assessments Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-351189 ER - TY - JOUR A1 - Thong, Melissa S. Y. A1 - Doege, Daniela A1 - Weißer, Linda A1 - Koch-Gallenkamp, Lena A1 - Jansen, Lina A1 - Bertram, Heike A1 - Eberle, Andrea A1 - Holleczek, Bernd A1 - Nennecke, Alice A1 - Waldmann, Annika A1 - Zeissig, Sylke Ruth A1 - Brenner, Hermann A1 - Arndt, Volker T1 - Persisting deficits in health-related quality of life of colorectal cancer survivors 14–24 years post-diagnosis: a population-based study JF - Current Oncology N2 - (1) Background: The health-related quality of life (HRQOL) of colorectal cancer (CRC) survivors >10 years post-diagnosis is understudied. We aimed to compare the HRQOL of CRC survivors 14–24 years post-diagnosis to that of age- and sex-matched non-cancer controls, stratified by demographic and clinical factors. (2) Methods: We used data from 506 long-term CRC survivors and 1489 controls recruited from German population-based multi-regional studies. HRQOL was assessed with the European Organization for Research and Treatment of Cancer Quality of Life Core-30 (EORTC QLQ-C30) questionnaire. We estimated differences in the HRQOL of CRC survivors and controls with multiple regression, adjusted for age at survey, sex, and education, where appropriate. (3) Results: CRC survivors reported poorer social functioning but better health status/QOL than controls. CRC survivors, in general, had higher levels of symptom burden, and in particular diarrhea and constipation, regardless of demographic or clinical factors. In stratified analyses, HRQOL differed by age, sex, cancer type, and having a permanent stoma. (4) Conclusions: Although CRC survivors may have a comparable health status/QOL to controls 14–24 years after diagnosis, they still live with persistent bowel dysfunction that can negatively impact aspects of functioning. Healthcare providers should provide timely and adapted follow-up care to ameliorate potential long-term suffering. KW - colorectal cancer KW - long-term survivors KW - health-related quality of life KW - population-based KW - non-cancer controls Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-311084 SN - 1718-7729 VL - 30 IS - 3 SP - 3373 EP - 3390 ER - TY - JOUR A1 - Kirikkayis, Yusuf A1 - Gallik, Florian A1 - Winter, Michael A1 - Reichert, Manfred T1 - BPMNE4IoT: a framework for modeling, executing and monitoring IoT-driven processes JF - Future Internet N2 - The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart manufacturing, and smart city. By enhancing Business Process Management Systems with IoT capabilities, the execution and monitoring of business processes can be significantly improved. Providing a holistic support for modeling, executing and monitoring IoT-driven processes, however, constitutes a challenge. Existing process modeling and process execution languages, such as BPMN 2.0, are unable to fully meet the IoT characteristics (e.g., asynchronicity and parallelism) of IoT-driven processes. In this article, we present BPMNE4IoT—A holistic framework for modeling, executing and monitoring IoT-driven processes. We introduce various artifacts and events based on the BPMN 2.0 metamodel that allow realizing the desired IoT awareness of business processes. The framework is evaluated along two real-world scenarios from two different domains. Moreover, we present a user study for comparing BPMNE4IoT and BPMN 2.0. In particular, this study has confirmed that the BPMNE4IoT framework facilitates the support of IoT-driven processes. KW - IoT KW - BPM KW - BPMN KW - IoT-driven processes Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304097 SN - 1999-5903 VL - 15 IS - 3 ER - TY - JOUR A1 - Haarmann, Axel A1 - Vollmuth, Christoph A1 - Kollikowski, Alexander M. A1 - Heuschmann, Peter U. A1 - Pham, Mirko A1 - Stoll, Guido A1 - Neugebauer, Hermann A1 - Schuhmann, Michael K. T1 - Vasoactive soluble endoglin: a novel biomarker indicative of reperfusion after cerebral large-vessel occlusion JF - Cells N2 - Now that mechanical thrombectomy has substantially improved outcomes after large-vessel occlusion stroke in up to every second patient, futile reperfusion wherein successful recanalization is not followed by a favorable outcome is moving into focus. Unfortunately, blood-based biomarkers, which identify critical stages of hemodynamically compromised yet reperfused tissue, are lacking. We recently reported that hypoxia induces the expression of endoglin, a TGF-β co-receptor, in human brain endothelium in vitro. Subsequent reoxygenation resulted in shedding. Our cell model suggests that soluble endoglin compromises the brain endothelial barrier function. To evaluate soluble endoglin as a potential biomarker of reperfusion (-injury) we analyzed its concentration in 148 blood samples of patients with acute stroke due to large-vessel occlusion. In line with our in vitro data, systemic soluble endoglin concentrations were significantly higher in patients with successful recanalization, whereas hypoxia alone did not induce local endoglin shedding, as analyzed by intra-arterial samples from hypoxic vasculature. In patients with reperfusion, higher concentrations of soluble endoglin additionally indicated larger infarct volumes at admission. In summary, we give translational evidence that the sequence of hypoxia and subsequent reoxygenation triggers the release of vasoactive soluble endoglin in large-vessel occlusion stroke and can serve as a biomarker for severe ischemia with ensuing recanalization/reperfusion. KW - endoglin KW - brain endothelium KW - stroke KW - shedding KW - mechanical thrombectomy KW - hypoxia KW - reperfusion injury KW - biomarker Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304995 SN - 2073-4409 VL - 12 IS - 2 ER - TY - JOUR A1 - Gelbrich, Götz A1 - Morbach, Caroline A1 - Deutschbein, Timo A1 - Fassnacht, Martin A1 - Störk, Stefan A1 - Heuschmann, Peter U. T1 - The population comparison index: an intuitive measure to calibrate the extent of impairments in patient cohorts in relation to healthy and diseased populations JF - International Journal of Environmental Research and Public Health N2 - We assume that a specific health constraint, e.g., a certain aspect of bodily function or quality of life that is measured by a variable X, is absent (or irrelevant) in a healthy reference population (Ref0), and it is materially present and precisely measured in a diseased reference population (Ref1). We further assume that some amount of this constraint of interest is suspected to be present in a population under study (SP). In order to quantify this issue, we propose the introduction of an intuitive measure, the population comparison index (PCI), that relates the mean value of X in population SP to the mean values of X in populations Ref0 and Ref1. This measure is defined as PCI[X] = (mean[X|SP] − mean[X|Ref0])/(mean[X|Ref1] − mean[X|Ref0]) × 100[%], where mean[X|.] is the average value of X in the respective group of individuals. For interpretation, PCI[X] ≈ 0 indicates that the values of X in the population SP are similar to those in population Ref0, and hence, the impairment measured by X is not materially present in the individuals in population SP. On the other hand, PCI[X] ≈ 100 means that the individuals in SP exhibit values of X comparable to those occurring in Ref1, i.e., the constraint of interest is equally present in populations SP and Ref1. A value of 0 < PCI[X] < 100 indicates that a certain percentage of the constraint is present in SP, and it is more than in Ref0 but less than in Ref1. A value of PCI[X] > 100 means that population SP is even more affected by the constraint than population Ref1. KW - reference data KW - normal values KW - disease severity KW - disease score KW - comparability Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304933 SN - 1660-4601 VL - 20 IS - 3 ER - TY - JOUR A1 - Ungethüm, K. A1 - Wiedmann, S. A1 - Wagner, M. A1 - Leyh, R. A1 - Ertl, G. A1 - Frantz, S. A1 - Geisler, T. A1 - Karmann, W. A1 - Prondzinsky, R. A1 - Herdeg, C. A1 - Noutsias, M. A1 - Ludwig, T. A1 - Käs, J. A1 - Klocke, B. A1 - Krapp, J. A1 - Wood, D. A1 - Kotseva, K. A1 - Störk, S. A1 - Heuschmann, P. U. T1 - Secondary prevention in diabetic and nondiabetic coronary heart disease patients: insights from the German subset of the hospital arm of the EUROASPIRE IV and V surveys JF - Clinical Research in Cardiology N2 - Background Patients with coronary heart disease (CHD) with and without diabetes mellitus have an increased risk of recurrent events requiring multifactorial secondary prevention of cardiovascular risk factors. We compared prevalences of cardiovascular risk factors and its determinants including lifestyle, pharmacotherapy and diabetes mellitus among patients with chronic CHD examined within the fourth and fifth EUROASPIRE surveys (EA-IV, 2012–13; and EA-V, 2016–17) in Germany. Methods The EA initiative iteratively conducts European-wide multicenter surveys investigating the quality of secondary prevention in chronic CHD patients aged 18 to 79 years. The data collection in Germany was performed during a comprehensive baseline visit at study centers in Würzburg (EA-IV, EA-V), Halle (EA-V), and Tübingen (EA-V). Results 384 EA-V participants (median age 69.0 years, 81.3% male) and 536 EA-IV participants (median age 68.7 years, 82.3% male) were examined. Comparing EA-IV and EA-V, no relevant differences in risk factor prevalence and lifestyle changes were observed with the exception of lower LDL cholesterol levels in EA-V. Prevalence of unrecognized diabetes was significantly lower in EA-V as compared to EA-IV (11.8% vs. 19.6%) while the proportion of prediabetes was similarly high in the remaining population (62.1% vs. 61.0%). Conclusion Between 2012 and 2017, a modest decrease in LDL cholesterol levels was observed, while no differences in blood pressure control and body weight were apparent in chronic CHD patients in Germany. Although the prevalence of unrecognized diabetes decreased in the later study period, the proportion of normoglycemic patients was low. As pharmacotherapy appeared fairly well implemented, stronger efforts towards lifestyle interventions, mental health programs and cardiac rehabilitation might help to improve risk factor profiles in chronic CHD patients. KW - coronary heart disease KW - diabetes mellitus KW - secondary prevention KW - EUROASPIRE Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324037 VL - 112 IS - 2 ER - TY - JOUR A1 - Kist, Markus A1 - Thomaschewski, Michael A1 - Keck, Yannick A1 - Abdalla, Thaer S. A. A1 - Zeissig, Sylke Ruth A1 - Kleihues-van Tol, Kees A1 - Wellner, Ulrich Friedrich A1 - Keck, Tobias A1 - Hoeppner, Jens A1 - Hummel, Richard T1 - Specifics of young gastric cancer patients: a population-based analysis of 46,110 patients with gastric cancer from the German Clinical Cancer Registry Group JF - Cancers N2 - Introduction: 2–8% of all gastric cancer occurs at a younger age, also known as early-onset gastric cancer (EOGC). The aim of the present work was to use clinical registry data to classify and characterize the young cohort of patients with gastric cancer more precisely. Methods: German Cancer Registry Group of the Society of German Tumor Centers—Network for Care, Quality and Research in Oncology (ADT)was queried for patients with gastric cancer from 2000–2016. An approach that stratified relative distributions of histological subtypes of gastric adenocarcinoma according to age percentiles was used to define and characterize EOGC. Demographics, tumor characteristics, treatment and survival were analyzed. Results: A total of 46,110 patients were included. Comparison of different groups of age with incidences of histological subtypes showed that incidence of signet ring cell carcinoma (SRCC) increased with decreasing age and exceeded pooled incidences of diffuse and intestinal type tumors in the youngest 20% of patients. We selected this group with median age of 53 as EOGC. The proportion of female patients was lower in EOGC than that of elderly patients (43% versus 45%; p < 0.001). EOGC presented more advanced and undifferentiated tumors with G3/4 stages in 77% versus 62%, T3/4 stages in 51% versus 48%, nodal positive tumors in 57% versus 53% and metastasis in 35% versus 30% (p < 0.001) and received less curative treatment (42% versus 52%; p < 0.001). Survival of EOGC was significantly better (five-years survival: 44% versus 31% (p < 0.0001), with age as independent predictor of better survival (HR 0.61; p < 0.0001). Conclusion: With this population-based registry study we were able to objectively define a cohort of patients referred to as EOGC. Despite more aggressive/advanced tumors and less curative treatment, survival was significantly better compared to elderly patients, and age was identified as an independent predictor for better survival. KW - gastric cancer in young patients KW - german clinical cancer registry group KW - early-onset gastric cancer patients Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-297473 SN - 2072-6694 VL - 14 IS - 23 ER - TY - JOUR A1 - Tanoey, Justine A1 - Baechle, Christina A1 - Brenner, Hermann A1 - Deckert, Andreas A1 - Fricke, Julia A1 - Günther, Kathrin A1 - Karch, André A1 - Keil, Thomas A1 - Kluttig, Alexander A1 - Leitzmann, Michael A1 - Mikolajczyk, Rafael A1 - Obi, Nadia A1 - Pischon, Tobias A1 - Schikowski, Tamara A1 - Schipf, Sabine M. A1 - Schulze, Matthias B. A1 - Sedlmeier, Anja A1 - Moreno Velásquez, Ilais A1 - Weber, Katharina S. A1 - Völzke, Henry A1 - Ahrens, Wolfgang A1 - Gastell, Sylvia A1 - Holleczek, Bernd A1 - Jöckel, Karl-Heinz A1 - Katzke, Verena A1 - Lieb, Wolfgang A1 - Michels, Karin B. A1 - Schmidt, Börge A1 - Teismann, Henning A1 - Becher, Heiko T1 - Birth order, Caesarean section, or daycare attendance in relation to child- and adult-onset type 1 diabetes: results from the German National Cohort JF - International Journal of Environmental Research and Public Health N2 - (1) Background: Global incidence of type 1 diabetes (T1D) is rising and nearly half occurred in adults. However, it is unclear if certain early-life childhood T1D risk factors were also associated with adult-onset T1D. This study aimed to assess associations between birth order, delivery mode or daycare attendance and type 1 diabetes (T1D) risk in a population-based cohort and whether these were similar for childhood- and adult-onset T1D (cut-off age 15); (2) Methods: Data were obtained from the German National Cohort (NAKO Gesundheitsstudie) baseline assessment. Self-reported diabetes was classified as T1D if: diagnosis age ≤ 40 years and has been receiving insulin treatment since less than one year after diagnosis. Cox regression was applied for T1D risk analysis; (3) Results: Analyses included 101,411 participants (100 childhood- and 271 adult-onset T1D cases). Compared to “only-children”, HRs for second- or later-born individuals were 0.70 (95% CI = 0.50–0.96) and 0.65 (95% CI = 0.45–0.94), respectively, regardless of parental diabetes, migration background, birth year and perinatal factors. In further analyses, higher birth order reduced T1D risk in children and adults born in recent decades. Caesarean section and daycare attendance showed no clear associations with T1D risk; (4) Conclusions: Birth order should be considered in both children and adults’ T1D risk assessment for early detection. KW - perinatal KW - adult-onset KW - late-onset KW - autoimmune KW - delivery mode KW - sex KW - offspring KW - NAKO Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-286216 SN - 1660-4601 VL - 19 IS - 17 ER -