Toward targeted prevention: risk factors for prediabetes defined by impaired fasting glucose, impaired glucose tolerance and increased HbA1c in the population-based KORA study from Germany
Gespeichert in:
| Titel: | Toward targeted prevention: risk factors for prediabetes defined by impaired fasting glucose, impaired glucose tolerance and increased HbA1c in the population-based KORA study from Germany |
|---|---|
| Autoren: | Gregory G. Greiner, Karl M. F. Emmert-Fees, Jana Becker, Wolfgang Rathmann, Barbara Thorand, Annette Peters, Anne S. Quante, Lars Schwettmann, Michael Laxy |
| Quelle: | Acta Diabetol Acta Diabetol. 57, 1481-1491 (2020) |
| Verlagsinformationen: | Springer Science and Business Media LLC, 2020. |
| Publikationsjahr: | 2020 |
| Schlagwörter: | Prediabetes, Prevention, Igt, Ifg, Increased Hba1c, Epidemiology, Adult, Blood Glucose, Male, Prediabetic State, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Germany, Glucose Intolerance, Humans, Aged, Glycated Hemoglobin, 2. Zero hunger, ddc:610, Health Services Needs and Demand, Diabetes Mellitus, Type 2/epidemiology [MeSH], Diabetes Mellitus, Type 2/etiology [MeSH], Glucose Intolerance/diagnosis [MeSH], Aged [MeSH], IFG, Risk Factors [MeSH], Socioeconomic Factors [MeSH], Germany/epidemiology [MeSH], Health Services Needs and Demand/trends [MeSH], Original Article, Glucose Intolerance/etiology [MeSH], Male [MeSH], Glycated Hemoglobin A/analysis [MeSH], Preventive Medicine/methods [MeSH], Glucose Intolerance/blood [MeSH], Diabetes Mellitus, Type 2/diagnosis [MeSH], Prediabetic State/etiology [MeSH], Female [MeSH], Diabetes Mellitus, Type 2/prevention, Adult [MeSH], Fasting/blood [MeSH], Humans [MeSH], Glucose Intolerance/epidemiology [MeSH], Glycated Hemoglobin A/metabolism [MeSH], Middle Aged [MeSH], Prediabetic State/blood [MeSH], Preventive Medicine/trends [MeSH], Health Education and psycho-social aspects, Blood Glucose/analysis [MeSH], Prediabetic State/diagnosis [MeSH], IGT, Prediabetic State/epidemiology [MeSH], Young Adult [MeSH], Blood Glucose/metabolism [MeSH], Health Services Needs and Demand/organization, Increased HbA1c, Fasting, Middle Aged, ddc, 3. Good health, Diabetes Mellitus, Type 2, Socioeconomic Factors, 8. Economic growth, Female, Preventive Medicine |
| Beschreibung: | Aims To identify socioeconomic, behavioral and clinical factors that are associated with prediabetes according to different prediabetes definition criteria. Methods Analyses use pooled data of the population-based Cooperative Health Research in the Region of Augsburg (KORA) studies (n = 5312 observations aged ≥ 38 years without diabetes). Prediabetes was defined through either impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or elevated HbA1c according to thresholds of the American Diabetes Association. Explanatory variables were regressed on prediabetes using generalized estimating equations. Results Mean age was 58.4 years; 50% had prediabetes (33% had IFG, 16% IGT, and 26% elevated HbA1c, 10% fulfilled all three criteria). Age, obesity, hypertension, low education, unemployment, statutory health insurance, urban residence and physical inactivity were associated with prediabetes. Male sex was a stronger risk factor for IFG (OR = 2.5; 95%–CI: 2.2–2.9) than for IGT or elevated HbA1c, and being unemployed was a stronger risk factor for IGT (OR = 3.2 95%–CI: 2.6–4.0) than for IFG or elevated HbA1c. Conclusions The overlap of people with IFG, IGT and elevated HbA1c is small, and some factors are associated with only one criterion. Knowledge on sociodemographic and socioeconomic risk factors can be used to effectively target interventions to people at high risk for type 2 diabetes. |
| Publikationsart: | Article Other literature type |
| Dateibeschreibung: | application/pdf |
| Sprache: | English |
| ISSN: | 1432-5233 0940-5429 |
| DOI: | 10.1007/s00592-020-01573-x |
| DOI: | 10.25673/108803 |
| Zugangs-URL: | https://link.springer.com/content/pdf/10.1007/s00592-020-01573-x.pdf https://pubmed.ncbi.nlm.nih.gov/32748175 https://europepmc.org/article/MED/32748175 https://link.springer.com/content/pdf/10.1007/s00592-020-01573-x.pdf https://pubmed.ncbi.nlm.nih.gov/32748175/ https://www.ncbi.nlm.nih.gov/pubmed/32748175 https://link.springer.com/article/10.1007/s00592-020-01573-x https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=59840 https://repository.publisso.de/resource/frl:6467168 https://mediatum.ub.tum.de/1575219 |
| Rights: | CC BY |
| Dokumentencode: | edsair.doi.dedup.....4b2daf5616bf7a5e5a70535329481f11 |
| Datenbank: | OpenAIRE |
| Abstract: | Aims To identify socioeconomic, behavioral and clinical factors that are associated with prediabetes according to different prediabetes definition criteria. Methods Analyses use pooled data of the population-based Cooperative Health Research in the Region of Augsburg (KORA) studies (n = 5312 observations aged ≥ 38 years without diabetes). Prediabetes was defined through either impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or elevated HbA1c according to thresholds of the American Diabetes Association. Explanatory variables were regressed on prediabetes using generalized estimating equations. Results Mean age was 58.4 years; 50% had prediabetes (33% had IFG, 16% IGT, and 26% elevated HbA1c, 10% fulfilled all three criteria). Age, obesity, hypertension, low education, unemployment, statutory health insurance, urban residence and physical inactivity were associated with prediabetes. Male sex was a stronger risk factor for IFG (OR = 2.5; 95%–CI: 2.2–2.9) than for IGT or elevated HbA1c, and being unemployed was a stronger risk factor for IGT (OR = 3.2 95%–CI: 2.6–4.0) than for IFG or elevated HbA1c. Conclusions The overlap of people with IFG, IGT and elevated HbA1c is small, and some factors are associated with only one criterion. Knowledge on sociodemographic and socioeconomic risk factors can be used to effectively target interventions to people at high risk for type 2 diabetes. |
|---|---|
| ISSN: | 14325233 09405429 |
| DOI: | 10.1007/s00592-020-01573-x |
Full Text Finder
Nájsť tento článok vo Web of Science