BACKGROUND: Within the context of the obesity epidemic identifying young adults at risk for type 2 diabetes and cardiovascular disease is important. A practical approach is based on the identification of metabolic syndrome (MetS). Our objective was to develop a simple and efficient stepwise strategy to identify MetS in young adults. METHODS: Subjects were part of a birth cohort (n = 2599) in Terneuzen, The Netherlands, born in 1977-86. In 2004-05: 642 of these young adults participated in a physical examination and blood tests. Tree regression was used to determine the optimal decision strategy to identify MetS. RESULTS: Overall prevalence of MetS, defined according to the NCEP ATPIII, was 7.5%. The tree regression yielded an optimal stepwise strategy that eliminated the need for blood tests for the diagnosis of MetS in 50-90% of the cases, depending on the accepted level of error. A large group (52% of the total) with BMI <35 had a normal waist circumference (WC) and normal blood pressure (BP). None of them had MetS. Subjects with BMI > or =35 all had MetS. If BMI <30, 38% had an increased WC or increased BP with a risk of MetS of only 6%. So for them the omission of blood tests could also be considered. CONCLUSION: In most young adults MetS can be identified or excluded without blood tests by a simple and stepwise strategy, based on the measurement of BMI, WC and BP. This makes it possible to develop simple prevention strategies for young adults at risk for type 2 diabetes and cardiovascular disease.
BACKGROUND: Within the context of the obesity epidemic identifying young adults at risk for type 2 diabetes and cardiovascular disease is important. A practical approach is based on the identification of metabolic syndrome (MetS). Our objective was to develop a simple and efficient stepwise strategy to identify MetS in young adults. METHODS: Subjects were part of a birth cohort (n = 2599) in Terneuzen, The Netherlands, born in 1977-86. In 2004-05: 642 of these young adults participated in a physical examination and blood tests. Tree regression was used to determine the optimal decision strategy to identify MetS. RESULTS: Overall prevalence of MetS, defined according to the NCEP ATPIII, was 7.5%. The tree regression yielded an optimal stepwise strategy that eliminated the need for blood tests for the diagnosis of MetS in 50-90% of the cases, depending on the accepted level of error. A large group (52% of the total) with BMI <35 had a normal waist circumference (WC) and normal blood pressure (BP). None of them had MetS. Subjects with BMI > or =35 all had MetS. If BMI <30, 38% had an increased WC or increased BP with a risk of MetS of only 6%. So for them the omission of blood tests could also be considered. CONCLUSION: In most young adults MetS can be identified or excluded without blood tests by a simple and stepwise strategy, based on the measurement of BMI, WC and BP. This makes it possible to develop simple prevention strategies for young adults at risk for type 2 diabetes and cardiovascular disease.
Authors: Marlou L A De Kroon; Carry M Renders; Jacobus P Van Wouwe; Stef Van Buuren; Remy A Hirasing Journal: PLoS One Date: 2010-02-11 Impact factor: 3.240
Authors: Marlou L A de Kroon; Carry M Renders; Jacobus P van Wouwe; Stef van Buuren; Remy A Hirasing Journal: PLoS One Date: 2010-11-12 Impact factor: 3.240
Authors: Marlou L A De Kroon; Carry M Renders; Michelle P J Buskermolen; Jacobus P Van Wouwe; Stef van Buuren; Remy A Hirasing Journal: BMC Pediatr Date: 2011-05-10 Impact factor: 2.125
Authors: Loretta Dipietro; Yuqing Zhang; Meghan Mavredes; Samuel J Simmens; Jessica A Whiteley; Laura L Hayman; Jamie Faro; Steven K Malin; Ginger Winston; Melissa A Napolitano Journal: Med Sci Sports Exerc Date: 2020-05
Authors: Marieke Welten; Marlou L A de Kroon; Carry M Renders; Ewout W Steyerberg; Hein Raat; Jos W R Twisk; Martijn W Heymans Journal: Diagn Progn Res Date: 2018-02-13
Authors: Manuel Romero-Saldaña; Pedro Tauler; Manuel Vaquero-Abellán; Angel-Arturo López-González; Francisco-José Fuentes-Jiménez; Antoni Aguiló; Carlos Álvarez-Fernández; Guillermo Molina-Recio; Miquel Bennasar-Veny Journal: BMJ Open Date: 2018-10-21 Impact factor: 2.692