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.
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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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