Publications

Here you will find all national and international specialist publications of the German National Cohort (NAKO).
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Schmiedek F, Kroehne U, Goldhammer F, et al. General cognitive ability assessment in the German National Cohort (NAKO) – The block-adaptive number series task. The World Journal of Biological Psychiatry. 2023;24(10):924-935. http://doi.org/10.1080/15622975.2021.2011407
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Streit F, Zillich L, Frank J, et al. Lifetime and current depression in the German National Cohort (NAKO). The World Journal of Biological Psychiatry. 2023;24(10):865-880. http://doi.org/10.1080/15622975.2021.2014152
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Huemer MT, Kluttig A, Fischer B, et al. Grip strength values and cut-off points based on over 200,000 adults of the German National Cohort - a comparison to the EWGSOP2 cut-off points. Age and Ageing. 2023;52(1):afac324. http://doi.org/10.1093/ageing/afac324
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Ortmann J, Heise JK, Janzen I, et al. Suitability and user acceptance of the eResearch system “Prospective Monitoring and Management App (PIA)”—The example of an epidemiological study on infectious diseases. Page K, ed. PLoS ONE. 2023;18(1):e0279969. http://doi.org/10.1371/journal.pone.0279969
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Merz S, Jaehn P, Pischon T, et al. Investigating people’s attitudes towards participating in longitudinal health research: an intersectionality-informed perspective. Int J Equity Health. 2023;22(1):23. http://doi.org/10.1186/s12939-022-01807-0
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Gatidis S, Kart T, Fischer M, et al. Better Together: Data Harmonization and Cross-Study Analysis of Abdominal MRI Data From UK Biobank and the German National Cohort. Invest Radiol. 2023;58(5):346-354. http://doi.org/10.1097/RLI.0000000000000941
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Haueise T, Schick F, Stefan N, et al. Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort. Sci Adv. 2023;9(19):eadd0433. http://doi.org/10.1126/sciadv.add0433
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Streit F, Völker MP, Klinger-König J, et al. The interplay of family history of depression and early trauma: associations with lifetime and current depression in the German national cohort (NAKO). Front Epidemiol. 2023;3:1099235. http://doi.org/10.3389/fepid.2023.1099235
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Ewendt F, Schmitt M, Kluttig A, et al. Association between vitamin D status and eryptosis–results from the German National Cohort Study. Ann Hematol. 2023;102(6):1351-1361. http://doi.org/10.1007/s00277-023-05239-w
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Vonneilich N, Becher H, Bohn B, et al. Associations of Migration, Socioeconomic Position and Social Relations With Depressive Symptoms – Analyses of the German National Cohort Baseline Data. Int J Public Health. 2023;68:1606097. http://doi.org/10.3389/ijph.2023.1606097
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Fischer M, Küstner T, Pappa S, et al. Identification of radiomic biomarkers in a set of four skeletal muscle groups on Dixon MRI of the NAKO MR study. BMC Med Imaging. 2023;23(1):104. http://doi.org/10.1186/s12880-023-01056-9
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Koschig M, Conrad I, Berger K, et al. The mediating role of personality traits in the association between childhood trauma and depressive symptoms in young adulthood. Journal of Affective Disorders. 2023;338:373-379. http://doi.org/10.1016/j.jad.2023.06.027
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Erhardt A, Gelbrich G, Klinger-König J, et al. Generalised anxiety and panic symptoms in the German National Cohort (NAKO). The World Journal of Biological Psychiatry. 2023;24(10):881-896. http://doi.org/10.1080/15622975.2021.2011409
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Kleineidam L, Stark M, Riedel-Heller SG, et al. The assessment of cognitive function in the German National Cohort (NAKO) – Associations of demographics and psychiatric symptoms with cognitive test performance. The World Journal of Biological Psychiatry. 2023;24(10):909-923. http://doi.org/10.1080/15622975.2021.2011408
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Klinger-König J, Streit F, Erhardt A, et al. The assessment of childhood maltreatment and its associations with affective symptoms in adulthood: Results of the German National Cohort (NAKO). The World Journal of Biological Psychiatry. 2023;24(10):897-908. http://doi.org/10.1080/15622975.2021.2011406
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Hassenstein MJ, Pischon T, Karch A, et al. Seropositivity of Borrelia burgdorferi s.l. in Germany—an analysis across four German National Cohort (NAKO) study sites. Sci Rep. 2023;13(1):21087. http://doi.org/10.1038/s41598-023-47766-6
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Schuppert C, Rospleszcz S, Hirsch JG, et al. Automated image quality assessment for selecting among multiple magnetic resonance image acquisitions in the German National Cohort study. Sci Rep. 2023;13(1):22745. http://doi.org/10.1038/s41598-023-49569-1
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Bosquillon De Jarcy L, Akbil B, Mhlekude B, et al. 90K/LGALS3BP expression is upregulated in COVID-19 but may not restrict SARS-CoV-2 infection. Clin Exp Med. 2023;23(7):3689-3700. http://doi.org/10.1007/s10238-023-01077-2
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Kettlitz R, Harries M, Ortmann J, et al. Association of known SARS-CoV-2 serostatus and adherence to personal protection measures and the impact of personal protective measures on seropositivity in a population-based cross-sectional study (MuSPAD) in Germany. BMC Public Health. 2023;23(1):2281. http://doi.org/10.1186/s12889-023-17121-5
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Berger K, Rietschel M, Rujescu D. The value of ‘mega cohorts’ for psychiatric research. The World Journal of Biological Psychiatry. 2023;24(10):860-864. http://doi.org/10.1080/15622975.2021.2011405
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Fay L, Cobos E, Yang B, Gatidis S, Küstner T. Avoiding Shortcut-Learning by Mutual Information Minimization in Deep Learning-Based Image Processing. IEEE Access. 2023;11:64070-64086. http://doi.org/10.1109/ACCESS.2023.3289397
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Reuter M, Rigó M, Formazin M, et al. Authors’ response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health. 2022;48(7):588-590. http://doi.org/10.5271/sjweh.4061
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Rickmann AM, Senapati J, Kovalenko O, Peters A, Bamberg F, Wachinger C. AbdomenNet: deep neural network for abdominal organ segmentation in epidemiologic imaging studies. BMC Med Imaging. 2022;22(1):168. http://doi.org/10.1186/s12880-022-00893-4
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Streckenbach F, Leifert G, Beyer T, et al. Application of a Deep Learning Approach to Analyze Large-Scale MRI Data of the Spine. Healthcare. 2022;10(11):2132. http://doi.org/10.3390/healthcare10112132
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Tanoey J, Baechle C, Brenner H, et al. Birth Order, Caesarean Section, or Daycare Attendance in Relation to Child- and Adult-Onset Type 1 Diabetes: Results from the German National Cohort. IJERPH. 2022;19(17):10880. http://doi.org/10.3390/ijerph191710880
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Wienbergen H, Boakye D, Günther K, et al. Lifestyle and metabolic risk factors in patients with early-onset myocardial infarction: a case-control study. European Journal of Preventive Cardiology. 2022;29(16):2076-2087. http://doi.org/10.1093/eurjpc/zwac132
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Hahn T, Ernsting J, Winter NR, et al. An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling. Sci Adv. 2022;8(1):eabg9471. http://doi.org/10.1126/sciadv.abg9471
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Kuss O, Becher H, Wienke A, et al. Statistical Analysis in the German National Cohort (NAKO) – Specific Aspects and General Recommendations. Eur J Epidemiol. 2022;37(4):429-436. http://doi.org/10.1007/s10654-022-00880-7
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Schuppert C, Krüchten RV, Hirsch JG, et al. Whole-Body Magnetic Resonance Imaging in the Large Population-Based German National Cohort Study: Predictive Capability of Automated Image Quality Assessment for Protocol Repetitions. Invest Radiol. 2022;57(7):478-487. http://doi.org/10.1097/RLI.0000000000000861
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Reuter M, Rigó M, Formazin M, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health. 2022;48(6):446-456. http://doi.org/10.5271/sjweh.4037
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Jaeschke L, Becher M, Velásquez IM, et al. The bias from heaping on risk estimation: effect of age at diagnosis of hypertension on risk of subsequent cardiovascular comorbidities. Annals of Epidemiology. 2022;74:84-96. http://doi.org/10.1016/j.annepidem.2022.07.012
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Kart T, Fischer M, Winzeck S, et al. Automated imaging-based abdominal organ segmentation and quality control in 20,000 participants of the UK Biobank and German National Cohort Studies. Sci Rep. 2022;12(1):18733. http://doi.org/10.1038/s41598-022-23632-9
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Hassenstein M, Janzen I, Krause G, et al. Seroepidemiology of Borrelia burgdorferi s.l. among German National Cohort (NAKO) Participants, Hanover. Microorganisms. 2022;10(11):2286. http://doi.org/10.3390/microorganisms10112286
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Moreno Velásquez I, Jaeschke L, Steinbrecher A, et al. Association of general and abdominal adiposity with postural changes in systolic blood pressure: results from the NAKO pretest and MetScan studies. Hypertens Res. 2022;45(12):1964-1976. http://doi.org/10.1038/s41440-022-01029-5
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Peters A, German National Cohort (NAKO) Consortium, Peters A, et al. Framework and baseline examination of the German National Cohort (NAKO). Eur J Epidemiol. 2022;37(10):1107-1124. http://doi.org/10.1007/s10654-022-00890-5
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Dragano N, Reuter M, Berger K. Increase in mental disorders during the COVID-19 pandemic—the role of occupational and financial strains. An analysis of the German National Cohort (NAKO) Study. Deutsches Ärzteblatt international. 2022. http://doi.org/10.3238/arztebl.m2022.0133
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Westerman R. NAKO Gesundheitsstudie - Eine erste Bilanz - Eine Langzeituntersuchung mit großem Ziel. Bevölkerungsforschung. 2022;43(4):3-7. https://www.bib.bund.de/Publikation/2022/pdf/Bevoelkerungsforschung-Aktuell-4-2022.pdf?__blob=publicationFile&v=3.
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Heise JK, Dey R, Emmerich M, et al. Putting digital epidemiology into practice: PIA- Prospective Monitoring and Management Application. Informatics in Medicine Unlocked. 2022;30:100931. http://doi.org/10.1016/j.imu.2022.100931
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Formazin M, Liebers F, Reuter M, Rigó M, Dragano N, Latza U. Berufsbezogenes Risiko einer SARS-CoV-2-Infektion in der ersten Welle der COVID-19-Pandemie: Ergebnisse auf Basis der NAKO Gesundheitsstudie. 2022. http://doi.org/10.21934/BAUA:BERICHTKOMPAKT20220711
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Hahn T, Fisch L, Ernsting J, et al. From ‘loose fitting’ to high-performance, uncertainty-aware brain-age modelling. Brain. 2021;144(3):e31-e31. http://doi.org/10.1093/brain/awaa454
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Hepp T, Blum D, Armanious K, et al. Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study. Computerized Medical Imaging and Graphics. 2021;92:101967. http://doi.org/10.1016/j.compmedimag.2021.101967
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Kart T, Fischer M, Küstner T, et al. Deep Learning‐Based Automated Abdominal Organ Segmentation in the UK Biobank and German National Cohort Magnetic Resonance Imaging Studies. Invest Radiol. 2021;56(6):401-408. http://doi.org/10.1097/RLI.0000000000000755
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Krist L, Bedir A, Fricke J, Kluttig A, Mikolajczyk R. The effect of home visits as an additional recruitment step on the composition of the final sample: a cross-sectional analysis in two study centers of the German National Cohort (NAKO). BMC Med Res Methodol. 2021;21(1):176. http://doi.org/10.1186/s12874-021-01357-z
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Uekoetter K, Ebert N, Stoffels A, Wigmann C, Schikowski T. Validation of the TeleForm scan workflow in the GNC health study on the example of the questionnaire on physical activity. GMS Med Inform Biom Epidemiol. 2021:17(1):Doc03. http://doi.org/10.3205/MIBE000217
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Berger K, Riedel-Heller S, Pabst A, et al. Einsamkeit während der ersten Welle der SARS-CoV-2-Pandemie – Ergebnisse der NAKO-Gesundheitsstudie. Bundesgesundheitsbl. 2021;64(9):1157-1164. http://doi.org/10.1007/s00103-021-03393-y
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Fischer M, Walter SS, Hepp T, et al. Automated Morphometric Analysis of the Hip Joint on MRI from the German National Cohort Study. Radiology: Artificial Intelligence. 2021;3(5):e200213. http://doi.org/10.1148/ryai.2021200213