1
|
Weber A, van Hees VT, Stein MJ, Gastell S, Steindorf K, Herbolsheimer F, Ostrzinski S, Pischon T, Brandes M, Krist L, Marschollek M, Greiser KH, Nimptsch K, Brandes B, Jochem C, Sedlmeier AM, Berger K, Brenner H, Buck C, Castell S, Dörr M, Emmel C, Fischer B, Flexeder C, Harth V, Hebestreit A, Heise JK, Holleczek B, Keil T, Koch-Gallenkamp L, Lieb W, Meinke-Franze C, Michels KB, Mikolajczyk R, Kluttig A, Obi N, Peters A, Schmidt B, Schipf S, Schulze MB, Teismann H, Waniek S, Willich SN, Leitzmann MF, Baurecht H. Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO). Sci Rep 2024; 14:7927. [PMID: 38575636 PMCID: PMC10995156 DOI: 10.1038/s41598-024-58461-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/29/2024] [Indexed: 04/06/2024] Open
Abstract
Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.
Collapse
Affiliation(s)
- Andrea Weber
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
| | | | - Michael J Stein
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Sylvia Gastell
- NAKO Study Center, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Karen Steindorf
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - Florian Herbolsheimer
- Division of Physical Activity, Prevention and Cancer, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - Stefan Ostrzinski
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Mirko Brandes
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Lilian Krist
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10098, Berlin, Germany
| | - Michael Marschollek
- Hannover Medical School, Peter L. Reichertz Institute for Medical Informatics, Carl-Neuberg-Strasse 1, 30625, Hannover, Germany
| | - Karin Halina Greiser
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120, Heidelberg, Germany
| | - Katharina Nimptsch
- Molecular Epidemiology Research Group, Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Berit Brandes
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Carmen Jochem
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Anja M Sedlmeier
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christoph Buck
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Stefanie Castell
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Brunswick, Germany
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Carina Emmel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Beate Fischer
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Claudia Flexeder
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Volker Harth
- Institute for Occupational and Maritime Medicine Hamburg (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Seewartenstraße 10, 20459, Hamburg, Germany
| | - Antje Hebestreit
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Jana-Kristin Heise
- Department for Epidemiology, Helmholtz Centre for Infection Research (HZI), Brunswick, Germany
| | | | - Thomas Keil
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10098, Berlin, Germany
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany
- State Institute of Health I, Bavarian Health and Food Safety Authority, Erlangen, Germany
| | - Lena Koch-Gallenkamp
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Claudia Meinke-Franze
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Karin B Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Rafael Mikolajczyk
- Institute for Medical Epidemiology, Biometrics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexander Kluttig
- Institute for Medical Epidemiology, Biometrics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Nadia Obi
- Institute for Occupational and Maritime Medicine Hamburg (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), Seewartenstraße 10, 20459, Hamburg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Sabine Schipf
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Henning Teismann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Sabina Waniek
- Institute of Epidemiology, Kiel University, Kiel, Germany
| | - Stefan N Willich
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10098, Berlin, Germany
| | - Michael F Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany
| |
Collapse
|
2
|
Haueise T, Schick F, Stefan N, Schlett CL, Weiss JB, Nattenmüller J, Göbel-Guéniot K, Norajitra T, Nonnenmacher T, Kauczor HU, Maier-Hein KH, Niendorf T, Pischon T, Jöckel KH, Umutlu L, Peters A, Rospleszcz S, Kröncke T, Hosten N, Völzke H, Krist L, Willich SN, Bamberg F, Machann J. 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:eadd0433. [PMID: 37172093 PMCID: PMC10181183 DOI: 10.1126/sciadv.add0433] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This research addresses the assessment of adipose tissue (AT) and spatial distribution of visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic resonance imaging at 3 T, thereby demonstrating the feasibility of deep learning (DL)-based image segmentation in a large population-based cohort in Germany (five sites). Volume and distribution of AT play an essential role in the pathogenesis of insulin resistance, a risk factor of developing metabolic/cardiovascular diseases. Cross-validated training of the DL-segmentation model led to a mean Dice similarity coefficient of >0.94, corresponding to a mean absolute volume deviation of about 22 ml. SAT is significantly increased in women compared to men, whereas VAT is increased in males. Spatial distribution shows age- and body mass index-related displacements. DL-based image segmentation provides robust and fast quantification of AT (≈15 s per dataset versus 3 to 4 hours for manual processing) and assessment of its spatial distribution from magnetic resonance images in large cohort studies.
Collapse
Affiliation(s)
- Tobias Haueise
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tuebingen, Germany
- Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany
| | - Fritz Schick
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tuebingen, Germany
- Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany
| | - Norbert Stefan
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tuebingen, Germany
- Department of Internal Medicine, Division of Diabetology, Endocrinology and Nephrology, Eberhard-Karls University Tuebingen, Tuebingen, Germany
| | - Christopher L Schlett
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jakob B Weiss
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Johanna Nattenmüller
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Katharina Göbel-Guéniot
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Tobias Norajitra
- Division of Medical and Biological Informatics, German Cancer Research Center, Heidelberg, Germany
| | - Tobias Nonnenmacher
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Klaus H Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
- Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Tobias Pischon
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Molecular Epidemiology Research Group, Berlin, Germany
- Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association (MDC), Biobank Technology Platform, Berlin, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Core Facility Biobank, Berlin, Germany
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, Essen, Germany
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Annette Peters
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- German Center for Diabetes Research (DZD), Partner Site Neuherberg, Neuherberg, Germany
| | - Susanne Rospleszcz
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Thomas Kröncke
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Faculty of Medicine, University of Augsburg, Augsburg, Germany
- Centre for Advanced Analytics and Predictive Sciences (CAAPS), University Augsburg, Augsburg, Germany
| | - Norbert Hosten
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Lilian Krist
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Stefan N Willich
- Institute of Social Medicine, Epidemiology and Health Economics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Juergen Machann
- Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich at the University of Tuebingen, Tuebingen, Germany
- German Center for Diabetes Research (DZD), Tuebingen, Germany
- Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany
| |
Collapse
|
3
|
Schlett CL. Kommentar zu HERZ THORAX – Bauchmuskelmasse und kardiovaskuläre Ereignisse. ROFO-FORTSCHR RONTG 2023; 195:367. [PMID: 37100068 DOI: 10.1055/a-2018-1327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Affiliation(s)
- Christopher L Schlett
- Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Freiburg, Freiburg, Germany
| |
Collapse
|
4
|
Krueger F, Aigner CS, Hammernik K, Dietrich S, Lutz M, Schulz-Menger J, Schaeffter T, Schmitter S. Rapid estimation of 2D relative B 1 + -maps from localizers in the human heart at 7T using deep learning. Magn Reson Med 2023; 89:1002-1015. [PMID: 36336877 DOI: 10.1002/mrm.29510] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 10/11/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE Subject-tailored parallel transmission pulses for ultra-high fields body applications are typically calculated based on subject-specific B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps of all transmit channels, which require lengthy adjustment times. This study investigates the feasibility of using deep learning to estimate complex, channel-wise, relative 2D B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps from a single gradient echo localizer to overcome long calibration times. METHODS 126 channel-wise, complex, relative 2D B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps of the human heart from 44 subjects were acquired at 7T using a Cartesian, cardiac gradient-echo sequence obtained under breath-hold to create a library for network training and cross-validation. The deep learning predicted maps were qualitatively compared to the ground truth. Phase-only B 1 + $$ {\mathrm{B}}_1^{+} $$ -shimming was subsequently performed on the estimated B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps for a region of interest covering the heart. The proposed network was applied at 7T to 3 unseen test subjects. RESULTS The deep learning-based B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps, derived in approximately 0.2 seconds, match the ground truth for the magnitude and phase. The static, phase-only pulse design performs best when maximizing the mean transmission efficiency. In-vivo application of the proposed network to unseen subjects demonstrates the feasibility of this approach: the network yields predicted B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps comparable to the acquired ground truth and anatomical scans reflect the resulting B 1 + $$ {\mathrm{B}}_1^{+} $$ -pattern using the deep learning-based maps. CONCLUSION The feasibility of estimating 2D relative B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps from initial localizer scans of the human heart at 7T using deep learning is successfully demonstrated. Because the technique requires only sub-seconds to derive channel-wise B 1 + $$ {\mathrm{B}}_1^{+} $$ -maps, it offers high potential for advancing clinical body imaging at ultra-high fields.
Collapse
Affiliation(s)
- Felix Krueger
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany.,Technische Universität Berlin, Biomedical Engineering, Berlin, Germany
| | | | - Kerstin Hammernik
- Technical University of Munich, Munich, Germany.,Imperial College London, London, United Kingdom
| | | | - Max Lutz
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany
| | - Jeanette Schulz-Menger
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Experimental Clinical Research Center, Berlin, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany.,Department of Cardiology and Nephrology, HELIOS Hospital Berlin-Buch, Berlin, Germany
| | - Tobias Schaeffter
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany.,Technische Universität Berlin, Biomedical Engineering, Berlin, Germany.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Sebastian Schmitter
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| |
Collapse
|
5
|
Al Masri F, Müller M, Straka D, Hahn A, Schuchardt JP. Nutritional and health status of adult Syrian refugees in the early years of asylum in Germany: a cross-sectional pilot study. BMC Public Health 2022; 22:2217. [PMID: 36447164 DOI: 10.1186/s12889-022-14684-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 11/21/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Migration is usually accompanied by changes in the social, cultural, and religious environment, socioeconomic status, and housing conditions, all of which affect nutritional health. In a cross-sectional study, we assessed the dietary intake as well as nutritional and health situation in a population of Syrian refugees who have resided in Germany for at least six months up to four years since 2015. The primary aim of this pilot study was to evaluate the nutritional and health status in comparison to reference values. METHODS Between December 2018 and March 2020, 114 adult Syrian refugees were included in the study. The subjects filled out questionnaires on sociodemographic variables, exercise, and nutrition behavior (three-day nutrition record). After a fasting blood draw, the subjects were examined for anthropometric parameters (height, weight, body mass index, waist circumference, waist-hip ratio, and body composition via a bioelectrical impedance analyzer). Various blood markers including iron status, hematological parameters, Vitamin D status, lipid metabolism, glucose metabolism, and total homocysteine (tHcy) were measured. RESULTS About half of the participants (71 male, 43 female) had lived in Germany for less than three years. Over 60% of men and 30% of women were overweight (BMI 25-30 kg/m2) or obese (BMI > 30 kg/m2), while 79% of men and 74% of women observed an elevated body fat mass. The evaluation of the three-day nutrition records revealed an unfavorable supply situation for numerous critical nutrients. More than half of the women (53.5%) had depleted iron stores (serum ferritin < 15 µg/l). The 25-OH-Vitamin D blood levels showed a high prevalence of Vitamin D insufficiency (25-49.9 nmol/l: 38% of men and 21% of women) and deficiency (< 25 nmol/l: 44% of men and 70% of women). 83% of men and 67% of women showed tHcy levels in plasma > 10 nmol/l. Fasting insulin levels and the HOMA-IR index indicate a risk for insulin resistance. Hyperlipidemia was prevalent, especially in males with 24% showing hypertriglyceridemia (> 150 mg/dl) and LDL-hypercholesterolemia (> 130 mg/dl). CONCLUSIONS The nutritional and health status of the cohort of Syrian refugees in Germany examined in this study is unsatisfactory, and many of the investigated refugees are at risk for developing cardiovascular disease and type 2 diabetes mellitus. Further studies are required to investigate the nutritional and health situation of refugees. This is obligatory to find ways to avoid malnutrition with all its associated health, sociodemographic, and economic consequences.
Collapse
|
6
|
Peters A, Peters A, Greiser KH, Göttlicher S, Ahrens W, Albrecht M, Bamberg F, Bärnighausen T, Becher H, Berger K, Beule A, Boeing H, Bohn B, Bohnert K, Braun B, Brenner H, Bülow R, Castell S, Damms-Machado A, Dörr M, Ebert N, Ecker M, Emmel C, Fischer B, Franzke CW, Gastell S, Giani G, Günther M, Günther K, Günther KP, Haerting J, Haug U, Heid IM, Heier M, Heinemeyer D, Hendel T, Herbolsheimer F, Hirsch J, Hoffmann W, Holleczek B, Hölling H, Hörlein A, Jöckel KH, Kaaks R, Karch A, Karrasch S, Kartschmit N, Kauczor HU, Keil T, Kemmling Y, Klee B, Klüppelholz B, Kluttig A, Kofink L, Köttgen A, Kraft D, Krause G, Kretz L, Krist L, Kühnisch J, Kuß O, Legath N, Lehnich AT, Leitzmann M, Lieb W, Linseisen J, Loeffler M, Macdonald A, Maier-Hein KH, Mangold N, Meinke-Franze C, Meisinger C, Melzer J, Mergarten B, Michels KB, Mikolajczyk R, Moebus S, Mueller U, Nauck M, Niendorf T, Nikolaou K, Obi N, Ostrzinski S, Panreck L, Pigeot I, Pischon T, Pschibul-Thamm I, Rathmann W, Reineke A, Roloff S, Rujescu D, Rupf S, Sander O, Schikowski T, Schipf S, Schirmacher P, Schlett CL, Schmidt B, Schmidt G, Schmidt M, Schöne G, Schulz H, Schulze MB, Schweig A, Sedlmeier AM, Selder S, Six-Merker J, Sowade R, Stang A, Stegle O, Steindorf K, Stübs G, Swart E, Teismann H, Thiele I, Thierry S, Ueffing M, Völzke H, Waniek S, Weber A, Werner N, Wichmann HE, Willich SN, Wirkner K, Wolf K, Wolff R, Zeeb H, Zinkhan M, Zschocke J; German National Cohort (NAKO) Consortium. Framework and baseline examination of the German National Cohort (NAKO). Eur J Epidemiol 2022. [PMID: 36260190 DOI: 10.1007/s10654-022-00890-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 06/14/2022] [Indexed: 11/25/2022]
Abstract
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.
Collapse
|
7
|
Hassan L, Efremov L, Großkopf A, Kartschmit N, Medenwald D, Schott A, Schmidt-Pokrzywniak A, Lacruz ME, Tiller D, Kraus FB, Greiser KH, Haerting J, Werdan K, Sedding D, Simm A, Nuding S, Kluttig A, Mikolajczyk R. Cardiovascular risk factors, living and ageing in Halle: the CARLA study. Eur J Epidemiol 2022; 37:103-116. [PMID: 34978665 PMCID: PMC8791893 DOI: 10.1007/s10654-021-00824-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 11/24/2021] [Indexed: 11/25/2022]
Abstract
The CARLA study (Cardiovascular Disease, Living and Ageing in Halle) is a longitudinal population-based cohort study of the general population of the city of Halle (Saale), Germany. The primary aim of the cohort was to investigate risk factors for cardiovascular diseases based on comprehensive cardiological phenotyping of study participants and was extended to study factors associated with healthy ageing. In total, 1779 probands (812 women and 967 men, aged 45–83 years) were examined at baseline (2002–2005), with a first and second follow-up performed 4 and 8 years later. The response proportion at baseline was 64.1% and the reparticipation proportion for the first and second follow-up was 86% and 77% respectively. Sixty-four percent of the study participants were in retirement while 25% were full- or partially-employed and 11% were unemployed at the time of the baseline examination. The currently running third follow-up focuses on the assessment of physical and mental health, with an intensive 4 h examination program, including measurement of cardiovascular, neurocognitive, balance and gait parameters. The data collected in the CARLA Study resulted in answering various research questions in over 80 publications, of which two thirds were pooled analyses with other similar population-based studies. Due to the extensiveness of information on risk factors, subclinical conditions and evident diseases, the biobanking concept for the biosamples, the cohort representativeness of an elderly population, and the high level of quality assurance, the CARLA cohort offers a unique platform for further research on important indicators for healthy ageing.
Collapse
Affiliation(s)
- Lamiaa Hassan
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Ljupcho Efremov
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Department of Radiation Oncology, University Hospital Halle (Saale), Halle (Saale), Germany
- Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Anne Großkopf
- University Clinic and Outpatient Clinic for Cardiac Surgery, Middle German Heart Centre at the University Hospital Halle, Halle, Germany
| | - Nadja Kartschmit
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Daniel Medenwald
- Department of Radiation Oncology, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Artjom Schott
- Department of Internal Medicine III, University Hospital, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Andrea Schmidt-Pokrzywniak
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Maria E Lacruz
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Daniel Tiller
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Clinical Computing Center - Data Integration Center, University Hospital Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | | | - Karin H Greiser
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Johannes Haerting
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Karl Werdan
- Department of Internal Medicine III, University Hospital, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Daniel Sedding
- Department of Internal Medicine III, University Hospital, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Andreas Simm
- University Clinic and Outpatient Clinic for Cardiac Surgery, Middle German Heart Centre at the University Hospital Halle, Halle, Germany
| | - Sebastian Nuding
- Department of Internal Medicine III, University Hospital, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Alexander Kluttig
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany.
- Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany.
| | - Rafael Mikolajczyk
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
- Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| |
Collapse
|
8
|
Probst-Hensch N, Bochud M, Chiolero A, Crivelli L, Dratva J, Flahault A, Frey D, Kuenzli N, Puhan M, Suggs LS, Wirth C. Swiss Cohort & Biobank - The White Paper. Public Health Rev 2022; 43:1605660. [PMID: 36619237 PMCID: PMC9817110 DOI: 10.3389/phrs.2022.1605660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- *Correspondence: Nicole Probst-Hensch,
| | - Murielle Bochud
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Department of Epidemiology and Health Systems (DESS), University Center for General Medicine and Public Health (Unisanté), Lausanne, Switzerland
| | - Arnaud Chiolero
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Population Health Laboratory (#PopHealthLab), University of Fribourg, Fribourg, Switzerland
- Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
| | - Luca Crivelli
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Department of Business Economics, Health and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Manno, Switzerland
- Institute of Public Health Università della Svizzera Italiana, Lugano, Switzerland
| | - Julia Dratva
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Institute of Public Health, Department of Health Sciences, ZHAW Zürich University of Applied Sciences, Winterthur, Switzerland
| | - Antoine Flahault
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Daniel Frey
- Swiss Society for Public Health, Bern, Switzerland
| | - Nino Kuenzli
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute (Swiss TPH), Allschwil, Switzerland
- University of Basel, Basel, Switzerland
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
| | - Milo Puhan
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, Zurich, Switzerland
| | - L. Suzanne Suggs
- Swiss School of Public Health (SSPH+), Zürich, Switzerland
- Swiss Society for Public Health, Bern, Switzerland
- Institute of Public Health Università della Svizzera Italiana, Lugano, Switzerland
| | - Corina Wirth
- Swiss Society for Public Health, Bern, Switzerland
| |
Collapse
|