To propose a simplified tool to recognize subjects with a moderate risk to develop type 2 diabetes mellitus (Type 2 DM): this method would take into account only variables from metabolic syndrome definitions which are cheaply assessable. A total of 3,003 employees without diabetes in Italy who attended one annual health examination between 2009 and 2012 were enrolled in this cross-sectional study. A questionnaire was administered along with the annual health examination to record personal and familiar anamnesis. To identify Type 2 DM-prone individuals, the diabetes predictive model by Stern MP et al. was used. Then a multiple logistic regression model was developed using the predicted probability 20 \%+ of developing Type 2 DM as the outcome variable and a panel of easily measurable continuous baseline characteristics as explanatory variables (waist circumference, WC; body mass index, BMI; and systolic blood pressure, SBP). The optimism-adjusted area under the curve of the proposed model receiver-operating characteristic (ROC) is 0.90. The effects of the explanatory variables on the presumed Type 2 DM risk are summarized by the following adjusted odds ratio values: 2.65 for SBP (P < 0.001), 2.01 for WC (P = 0.04) and 4.64 for BMI (P < 0.001). The satisfactory ROC of the proposed model suggests the importance of simple assessments in the prognostic information on Type 2 DM risk. Such ease of use may be particularly relevant in populations facing the transition from traditional to industrial food who do not have a sophisticated health service yet.

A simplified indication of metabolic syndrome to recognize subjects with a moderate risk to develop type 2 diabetes mellitus in a large Italian sample.

COMELLI, MARIO ANGELO;
2014-01-01

Abstract

To propose a simplified tool to recognize subjects with a moderate risk to develop type 2 diabetes mellitus (Type 2 DM): this method would take into account only variables from metabolic syndrome definitions which are cheaply assessable. A total of 3,003 employees without diabetes in Italy who attended one annual health examination between 2009 and 2012 were enrolled in this cross-sectional study. A questionnaire was administered along with the annual health examination to record personal and familiar anamnesis. To identify Type 2 DM-prone individuals, the diabetes predictive model by Stern MP et al. was used. Then a multiple logistic regression model was developed using the predicted probability 20 \%+ of developing Type 2 DM as the outcome variable and a panel of easily measurable continuous baseline characteristics as explanatory variables (waist circumference, WC; body mass index, BMI; and systolic blood pressure, SBP). The optimism-adjusted area under the curve of the proposed model receiver-operating characteristic (ROC) is 0.90. The effects of the explanatory variables on the presumed Type 2 DM risk are summarized by the following adjusted odds ratio values: 2.65 for SBP (P < 0.001), 2.01 for WC (P = 0.04) and 4.64 for BMI (P < 0.001). The satisfactory ROC of the proposed model suggests the importance of simple assessments in the prognostic information on Type 2 DM risk. Such ease of use may be particularly relevant in populations facing the transition from traditional to industrial food who do not have a sophisticated health service yet.
2014
The Endocrinology, Metabolism & Nutrition category is concerned with resources on the growth and regulation of the human body. Coverage focuses on disorders associated with endocrine glands such as diabetes, osteoporosis, and obesity. Nutrition resources focus on topics such as diagnosis, treatment, and management of nutritional and metabolic disorders. Reproductive endocrinology is excluded and is placed in the Reproductive Medicine category.
Esperti anonimi
Inglese
Internazionale
STAMPA
51
35
41
7
logistic regression; type 2 diabetes
http://dx.doi.org/10.1007/s00592-013-0463-0
6
info:eu-repo/semantics/article
262
S., Sacco; Comelli, MARIO ANGELO; V., Molina; P. L., Montrasio; E., Giani; F., Cavanna
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/849046
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