AIMS/HYPOTHESIS: The aim of this study was to examine the association between age at menarche and prediabetes as well as diabetes, considering confounding factors and the possible mediating role of adult obesity. METHODS: This cross-sectional study analysed data on 1,503 women aged 32-81 years from the German population-based KORA (Cooperative Health Research in the Region of Augsburg, South Germany) F4 Study (2006-2008). Data were collected by standardised interviews, physical examinations, and whole blood and serum measurements, including administration of an OGTT in non-diabetic participants. RESULTS: Of the 1,503 women, 226 showed a prediabetic state (impaired fasting glucose and/or impaired glucose tolerance) and 140 persons had diabetes (45 participants with previously undiagnosed diabetes and 95 with known diabetes). In Poisson regression analysis, age at menarche was significantly inversely associated with prediabetes or diabetes after adjustment for year of birth (RR 0.88; 95% CI 0.82, 0.94, p < 0.0001 per additional year of menarche) and after additional adjustment for a number of confounding factors (RR 0.88; 95% CI 0.83, 0.94, p = 0.0001). Further adjustment for current BMI slightly attenuated the association with prediabetes or diabetes (RR 0.89; 95% CI 0.83, 0.95, p = 0.0009), but the association remained clearly significant. CONCLUSIONS/ INTERPRETATION: Age at menarche seems to be inversely associated with prediabetes and diabetes independent of confounding factors including current BMI. Women at risk for diabetes might be identified by a history of young age at menarche.
AIMS/HYPOTHESIS: The aim of this study was to examine the association between age at menarche and prediabetes as well as diabetes, considering confounding factors and the possible mediating role of adult obesity. METHODS: This cross-sectional study analysed data on 1,503 women aged 32-81 years from the German population-based KORA (Cooperative Health Research in the Region of Augsburg, South Germany) F4 Study (2006-2008). Data were collected by standardised interviews, physical examinations, and whole blood and serum measurements, including administration of an OGTT in non-diabeticparticipants. RESULTS: Of the 1,503 women, 226 showed a prediabetic state (impaired fasting glucose and/or impaired glucose tolerance) and 140 persons had diabetes (45 participants with previously undiagnosed diabetes and 95 with known diabetes). In Poisson regression analysis, age at menarche was significantly inversely associated with prediabetes or diabetes after adjustment for year of birth (RR 0.88; 95% CI 0.82, 0.94, p < 0.0001 per additional year of menarche) and after additional adjustment for a number of confounding factors (RR 0.88; 95% CI 0.83, 0.94, p = 0.0001). Further adjustment for current BMI slightly attenuated the association with prediabetes or diabetes (RR 0.89; 95% CI 0.83, 0.95, p = 0.0009), but the association remained clearly significant. CONCLUSIONS/ INTERPRETATION: Age at menarche seems to be inversely associated with prediabetes and diabetes independent of confounding factors including current BMI. Women at risk for diabetes might be identified by a history of young age at menarche.
Authors: E A Andersson; K Pilgaard; C Pisinger; M N Harder; N Grarup; K Faerch; P Poulsen; D R Witte; T Jørgensen; A Vaag; T Hansen; O Pedersen Journal: Diabetologia Date: 2010-05-20 Impact factor: 10.122
Authors: Chunyan He; Cuilin Zhang; David J Hunter; Susan E Hankinson; Germaine M Buck Louis; Mary L Hediger; Frank B Hu Journal: Am J Epidemiol Date: 2009-12-21 Impact factor: 4.897
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Authors: J G Dreyfus; P L Lutsey; R Huxley; J S Pankow; E Selvin; L Fernández-Rhodes; N Franceschini; E W Demerath Journal: Diabetologia Date: 2012-07-04 Impact factor: 10.122
Authors: Lindsay Fernández-Rhodes; Ellen W Demerath; Diana L Cousminer; Ran Tao; Jill G Dreyfus; Tõnu Esko; Albert V Smith; Vilmundur Gudnason; Tamara B Harris; Lenore Launer; Patrick F McArdle; Laura M Yerges-Armstrong; Cathy E Elks; David P Strachan; Zoltán Kutalik; Peter Vollenweider; Bjarke Feenstra; Heather A Boyd; Andres Metspalu; Evelin Mihailov; Linda Broer; M Carola Zillikens; Ben Oostra; Cornelia M van Duijn; Kathryn L Lunetta; John R B Perry; Anna Murray; Daniel L Koller; Dongbing Lai; Tanguy Corre; Daniela Toniolo; Eva Albrecht; Doris Stöckl; Harald Grallert; Christian Gieger; Caroline Hayward; Ozren Polasek; Igor Rudan; James F Wilson; Chunyan He; Peter Kraft; Frank B Hu; David J Hunter; Jouke-Jan Hottenga; Gonneke Willemsen; Dorret I Boomsma; Enda M Byrne; Nicholas G Martin; Grant W Montgomery; Nicole M Warrington; Craig E Pennell; Lisette Stolk; Jenny A Visser; Albert Hofman; André G Uitterlinden; Fernando Rivadeneira; Peng Lin; Sherri L Fisher; Laura J Bierut; Laura Crisponi; Eleonora Porcu; Massimo Mangino; Guangju Zhai; Tim D Spector; Julie E Buring; Lynda M Rose; Paul M Ridker; Charles Poole; Joel N Hirschhorn; Joanne M Murabito; Daniel I Chasman; Elisabeth Widen; Kari E North; Ken K Ong; Nora Franceschini Journal: Am J Epidemiol Date: 2013-04-04 Impact factor: 4.897