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Anthropometric markers and their association with incident type 2 diabetes mellitus - which marker is best for prediction.pdf 1,09MB
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1000 Titel
  • Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study
1000 Autor/in
  1. Hartwig, Saskia |
  2. Kluttig, Alexander |
  3. Tiller, Daniel |
  4. Fricke, Julia |
  5. Müller, Grit |
  6. Schipf, Sabine |
  7. Völzke, Henry |
  8. Schunk, Michaela |
  9. Meisinger, Christa |
  10. Schienkiewitz, Anja |
  11. Heidemann, Christin |
  12. Moebus, Susanne |
  13. Pechlivanis, Sonali |
  14. Werdan, Karl |
  15. Kuss, Oliver |
  16. Tamayo, Teresa |
  17. Haerting, Johannes |
  18. Greiser, Karin Halina |
1000 Erscheinungsjahr 2016
1000 LeibnizOpen
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2016-01-20
1000 Erschienen in
1000 Quellenangabe
  • 6(1):e009266
1000 FRL-Sammlung
1000 Lizenz
1000 Verlagsversion
  • http://dx.doi.org/10.1136/bmjopen-2015-009266 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4735317/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • OBJECTIVE: To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. METHODS: Data of 10 258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. RESULTS: Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥65 years). CONCLUSIONS: We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged.
1000 Fachgruppe
  1. Medizin |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/SGFydHdpZywgU2Fza2lh|https://frl.publisso.de/adhoc/creator/S2x1dHRpZywgQWxleGFuZGVy|https://frl.publisso.de/adhoc/creator/VGlsbGVyLCBEYW5pZWw=|https://frl.publisso.de/adhoc/creator/RnJpY2tlLCBKdWxpYQ==|https://frl.publisso.de/adhoc/creator/TcO8bGxlciwgR3JpdA==|https://frl.publisso.de/adhoc/creator/U2NoaXBmLCBTYWJpbmU=|https://frl.publisso.de/adhoc/creator/VsO2bHprZSwgSGVucnk=|https://frl.publisso.de/adhoc/creator/U2NodW5rLCBNaWNoYWVsYQ==|https://frl.publisso.de/adhoc/creator/TWVpc2luZ2VyLCBDaHJpc3Rh|https://frl.publisso.de/adhoc/creator/U2NoaWVua2lld2l0eiwgQW5qYQ==|https://frl.publisso.de/adhoc/creator/SGVpZGVtYW5uLCBDaHJpc3Rpbg==|https://frl.publisso.de/adhoc/creator/TW9lYnVzLCBTdXNhbm5l|https://frl.publisso.de/adhoc/creator/UGVjaGxpdmFuaXMsIFNvbmFsaQ==|https://frl.publisso.de/adhoc/creator/V2VyZGFuLCBLYXJs|http://orcid.org/0000-0003-3301-5869|https://frl.publisso.de/adhoc/creator/VGFtYXlvLCBUZXJlc2E=|https://frl.publisso.de/adhoc/creator/SGFlcnRpbmcsIEpvaGFubmVz|https://frl.publisso.de/adhoc/creator/R3JlaXNlciwgS2FyaW4gSGFsaW5h
1000 Förderer
  1. German Federal Ministry of Education and Research (BMBF) |
  2. Deutsche Forschungsgemeinschaft |
  3. Martin-Luther-University Halle-Wittenberg |
  4. Ministry of Education and Cultural Affairs of Saxony-Anhalt |
  5. Federal Employment Office of Saxony-Anhalt |
  6. Ministry for Education, Research, and Cultural Affairs of the Federal State of Mecklenburg–West Pomerania |
  7. Ministry for Social Affairs of the Federal State of Mecklenburg–West Pomerania |
  8. Heinz Nixdorf Foundation (Germany) |
  9. German Ministry of Education and Science |
  10. Helmholtz Zentrum München—German Research Center for Environmental Health |
  11. State of Bavaria |
1000 Fördernummer
  1. 01GI1110C; 01GI1121B; 01ZZ0403
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1000 Förderprogramm
  1. Competence Network Diabetes Mellitus; Competence Network Obesity
  2. Collaborative Research Center 598 “Heart failure in the elderly—cellular mechanisms and therapy”
  3. Wilhelm-Roux Programme
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1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer German Federal Ministry of Education and Research (BMBF) |
    1000 Förderprogramm Competence Network Diabetes Mellitus; Competence Network Obesity
    1000 Fördernummer 01GI1110C; 01GI1121B; 01ZZ0403
  2. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm Collaborative Research Center 598 “Heart failure in the elderly—cellular mechanisms and therapy”
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Martin-Luther-University Halle-Wittenberg |
    1000 Förderprogramm Wilhelm-Roux Programme
    1000 Fördernummer -
  4. 1000 joinedFunding-child
    1000 Förderer Ministry of Education and Cultural Affairs of Saxony-Anhalt |
    1000 Förderprogramm -
    1000 Fördernummer -
  5. 1000 joinedFunding-child
    1000 Förderer Federal Employment Office of Saxony-Anhalt |
    1000 Förderprogramm -
    1000 Fördernummer -
  6. 1000 joinedFunding-child
    1000 Förderer Ministry for Education, Research, and Cultural Affairs of the Federal State of Mecklenburg–West Pomerania |
    1000 Förderprogramm -
    1000 Fördernummer -
  7. 1000 joinedFunding-child
    1000 Förderer Ministry for Social Affairs of the Federal State of Mecklenburg–West Pomerania |
    1000 Förderprogramm -
    1000 Fördernummer -
  8. 1000 joinedFunding-child
    1000 Förderer Heinz Nixdorf Foundation (Germany) |
    1000 Förderprogramm -
    1000 Fördernummer -
  9. 1000 joinedFunding-child
    1000 Förderer German Ministry of Education and Science |
    1000 Förderprogramm -
    1000 Fördernummer -
  10. 1000 joinedFunding-child
    1000 Förderer Helmholtz Zentrum München—German Research Center for Environmental Health |
    1000 Förderprogramm -
    1000 Fördernummer -
  11. 1000 joinedFunding-child
    1000 Förderer State of Bavaria |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 @id frl:6407719.rdf
1000 Erstellt am 2018-04-18T09:39:46.234+0200
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